Full condensation is obtained at minimal reaction times of only 2 h at 200 °C. The PI networks are obtained as monoliths and feature thermal stabilities of >500 °C, and in several cases even up to 595 °C. The monoliths are built up by networks of densely packed, near-monodisperse spherical particles and annealed microfibers, and show three types of porosity: (i) intrinsic inter-segment ultramicroporosity (<0.8 nm) of the PI networks composing the particles (∼3–5 μm), (ii) interstitial voids between the particles (0.1–2 μm), and (iii) monolith cell porosity (∽10–100 μm), as studied via low pressure gas physisorption and Hg intrusion porosimetry analyses. This unique hierarchical porosity generates an outstandingly high specific pore volume of 7250 mm3 g−1. A large-scale micromorphological study screening the reaction parameters time, temperature, and the absence/presence of the additive acetic acid was performed. Through expert interpretation of hundreds of scanning electron microscopy (SEM) images of the products of these experiments, we devise a hypothesis for morphology formation and evolution: a monomer salt is initially formed and subsequently transformed to overall eight different fiber, pearl chain, and spherical morphologies, composed of PI and, at long reaction times (>48 h), also PI/SiO2 hybrids that form through reaction with the reaction vessel. Moreover, we have developed a computational image analysis pipeline that deciphers the complex morphologies of these SEM images automatically and also allows for formulating a hypothesis of morphology development in HTP that is in good agreement with the manual morphology analysis. Finally, we upscaled the HTP of PI(TAPB–PMA) and processed the resulting powder into dense cylindrical specimen by green solvent-free warm-pressing, showing that one can follow the full route from the synthesis of these PI networks to a final material without employing harmful solvents.We report on the hydrothermal polymerization (HTP) of polyimide (PI) networks using the medium H 2O and the comonomers 1,3,5-tris(4-aminophenyl)benzene (TAPB) and pyromellitic acid (PMA).We report on the hydrothermal polymerization (HTP) of porous polyimide (PI) networks using the medium H Depending on the connectivity and topology of the building blocks and the degree or absence of network interpenetration, different segment lengths and sizes of voids between the segments result. Networks are amorphous, i.e. do not exhibit long-range order, in contrast to their crystalline counterparts frameworks. For instance, amorphous silica (SiO2) is an inorganic network composed of the covalently-linked building blocks Si (f = 4) and O (f = 2), and quartz is one of its framework counterparts. Compared to the corresponding framework, a network architecture often engenders materials properties such as mechanical strength , elasticity, a broader range of pore sizes (vs. a narrow pore size distribution in frameworks), and malleability e.g. through solvent swelling at increased T.1 Fully organic networks are typically referred to as polymer networks, and their crystalline counterparts as covalent organic frameworks (COFs). Both polymer networks and COFs are on a molecular scale “infinite” and therefore virtually insoluble in any solvents, and furthermore thermoset, with the exception of systems featuring chemical moieties able to undergo bond exchange reactions within the segments ).3 This limits their analysis to solid-state characterization techniques. Synthetically speaking, there are two major ways of generating a polymer network: (i) linear polymer chains are post-synthetically connected via crosslinking and (ii) direct construction of the network from multifunctional monomers (aka multitopic monomers).2 One particular type of polymer networks typically generated from multitopic monomers are so-called polyheterocyclics networks. Polyheterocyclics are exclusively composed of aromatic building blocks linked via heterocyclic moieties. Polyheterocyclic networks are interesting, because they combine porosity with high thermal and chemical stabilities (imparted through being built up of exclusively strong bonds) with functionality (imparted through the heteroatoms and conjugation). Examples of networks of the polyheterocyclics-type comprise polyimides,5–7 triazine-comprising polyimides,8,9 polybenzimidazoles,10–12 and poly(thiazolo thiazole)s.13,14Networks are three-dimensional molecular structures built up by covalently-linked building blocks, where at least one building block has a functionality via cyclocondensation reactions between dianhydrides and diamines (in the linear case) employing toxic condensation catalysts like isoquinoline , or mesitylene.15 The cyclization proceeds via two steps (2H functions and subsequent condensation reaction (liberation of H2O). Related routes and polymeric intermediates are used for all other types of polyheterocyclics, such as polybenzimidazoles, polybenzoxazoles, or polybenzthiazoles.4The major downside of polyheterocyclics is their synthesis, which is harsh and harmful, expensive, and tedious. For example for polyimides, which lie at the center of this contribution, the conventional synthetic route proceeds uinoline . The arowo steps : first, 2O as solvent: hydrothermal polymerization (HTP).16 HTP generates highly crystalline PIs and has therefore been described as a geomimetic approach imitating natural hydrothermal (HT) mineral formation processes, specifically HT crystallization of network minerals such as metal oxides , aluminosilicates (e.g. zeolites), and silicates (e.g. olivine).17–21 In striking analogy, both PIs and the latter network minerals form through polycyclocondensations, i.e. through the formation of a cyclic moiety connecting the monomeric units, accompanied by the release of a low-molecular weight by-product . Aside PIs, HTP has recently been shown to be also amenable to the synthesis of polyamide networks, which in the reported example are, however, linked by linear amide functions (and hence no heterocyclic linkages), and based on both aromatic and also alicyclic moieties,22 polyazomethines  linkages),23 and polybenzimidazoles and benzoyl-imidazole polymers (aka BBB – benzimidazolebenzophenanthroline-type semiladder polymers).24 HT cyclocondensations can also be used for generating small organic molecules, the technique is then rather termed hydrothermal synthesis (HTS), with examples comprising rylene bisimides,25 benzimidazoles,26 quinoxalines,76 and the fused bisbenzoylimidazole perinone.27 HTS/HTP relies on superheated liquid H2O as medium, generated through heating H2O above its boiling point in a closed vessel . High-temperature water features physicochemical properties from which cyclocondensations profit, e.g., decreased polarity and enhanced autoprotolysis leading to simultaneously increased acidity and basicity. Lower polarity enhances the solubility of organic molecules and enhanced autoprotolysis equips H2O itself with the ability to act as acidic/basic catalyst. HTS/HTP bears two major advantages: (i) the technique is environmentally friendly, especially in contrast to the conventional routes towards compounds built-up by mainly aromatic and heterocyclic functions, and (ii) the technique is straightforward to implement: the starting compounds are suspended in H2O at r.t., and the mixture is sealed in a commercially available steel autoclave and subsequently heated to the desired Tr, e.g., by placing it in an oven for the desired reaction time tr. After tr, the autoclave is cooled back to r.t. and hence the medium water becomes polar again, leading to the phase separation of the rather apolar reaction products, which can then be collected by simple filtration (if solid) or decantation (if liquid).28 HT conditions have been shown to promote crystallinity in small molecules,27,29 linear polyimides,16,28,30,31 polyamide networks,22 or at least semi-crystallinity in PI/SiO2 hybrid materials and linear polybenzimidazoles and BBB.24,31 To date, monomers used in HTP were mainly difunctional aromatic monomers, i.e., aromatic dianhydrides,16,28,31 aromatic diamines,16,23,28 and aromatic dialdehydes.23 Some reports employ tetrafunctional aromatic monomers, such as tetraamines,24 or in the case of PIs the free tetracarboxylic acids instead of the corresponding dianhydrides.31 In these cases however, the 1,2-difunctionality is in fact required to generate the heterocyclic linkages and thus does not lead to networks but linear polyheterocyclics. Only one publication has targeted the preparation of amorphous polymer networks by HTP, specifically a poly(amide imide) network, using mellitic  in combination with different aromatic diamines. However, the reported product is not a fully condensed network or framework, but rather consists of oligomers that can only be converted to a network-type higher molecular weight species by thermal annealing through solid-state postcondenzation at 340 °C.32Recently, we reported on a synthetic technique that does not require any toxic solvents or catalyst, but – beside the comonomers – solely Hvia the isolable multitopic monomer salt [H3TAPB3+]2[PMA2−]3  on all occasions reported to date,16,24,27,28,30,31,33–35 a multitopic MS has to date not been reported, including in the field of solid-state polymerizations of MS.36 For their insolubility, all PI(TAPB–PMA) networks where characterized via several solid-state techniques, including Fourier-transform infrared attenuated-total-reflection spectroscopy (FT-IR-ATR), X-ray diffractometry (XRD), thermogravimetric analysis (TGA), gas sorption (low-pressure CO2 physisorption), Hg porosimetry, and scanning electron microscopy (SEM). We show that and discuss why all PI networks are amorphous, despite both TAPB and PMA being rigid comonomers and HTP's propensity to generate crystalline products. Furthermore, through screening various reaction parameters and SEM analysis of all products, we find a wealth of distinct micromorphologies that occur in combination in the samples. We develop a hypothesis of the formation and underpinnings of these morphologies based on expert interpretation of hundreds of SEM images and cross-referencing with spectroscopic and diffraction data. Furthermore, we have devised a computational analysis pipeline that analyses these complex high-content images in an automated fashion. We believe that this approach is of great interest for the materials science/chemistry community, in light of the large analytical datasets generated nowadays, for instance by accelerated materials discovery through automation.37,38 Finally, we show that the HTP of PI(TAPB–PMA) can be upscaled, and that bulk materials can be generated through solvent-free warm-pressing.With this contribution, we have set out to, for the first time, hydrothermally prepare highly condensed aromatic PI networks. We chose the comonomers 1,3,5-tris(4-aminophenyl)benzene (TAPB) and pyromellitic acid (PMA) to synthesize the network PI(TAPB–PMA), see [PMA2−]3 , which f2.2O at r.t., transferred to an autoclave which was subsequently sealed, immediately heated to the reaction temperature Tr (200 or 250 °C), and kept there for the reaction time tr. Instead of first preparing the MS [H3TAPB3+]2[PMA2−]3, which is possible  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>O stretching vibrations, as well as the imide C–N stretching mode at ∼1365 cm−1 are clearly present and confirm the formation of the imide moiety. Additionally, the characteristic amine (∼3400–3300 cm−1), carboxylic acid CO (∼1850–1760 cm−1), and MS modes  are missing, which strongly points at both the absence of unreacted monomers and MS (cf. insets in i.e. to a point where end groups are not detectable anymore). Moreover, TGA of PI(TAPB–PMA), shows a high decomposition temperature Td of ∼550 °C and a small weight loss of around 4 wt% between r.t. and 200 °C and of in total ∼7 wt% until 560 °C (2O (which we expect to be mainly a reminiscence from the synthesis in water). While this value seems at first sight large for physisorbed H2O, both the amount and the temperatures of release significantly above 100 °C are in alignment with micro- and mesoporous hosts. Furthermore, TGA does not show a condensation step as one would expect for oligomers/monomers. Yet, full condensation cannot be claimed, and some extent of end-groups, albeit likely very small, cannot be excluded. Powder XRD (PXRD) measurements reveal that the PI(TAPB–PMA) network is amorphous with the diffractogram showing two broad features  fabricated by this initial synthesis was intriguing: a sponge-like polymer monolith was obtained . SEM ana2 as analyzing gas. The permanent porosity was evaluated by low-pressure carbon dioxide (CO2) sorption studies at 195 K and 273 K of the at 120 °C for 24 h evacuated PI(TAPB–PMA) sample (39 The Brunauer–Emmett–Teller surface area (SABET) calculated from the CO2 adsorption points at 195 K was found to be 207 m2 g−1. The pore size distribution (PSD) analysis derived by fitting a Monte Carlo model for carbon adsorbents to the collected isotherm at 273 K indicated the predominant presence of ultra-micropores with pore diameters below 0.8 nm . Finally, small relative amounts of mesoporosity (2–50 nm) can be identified from 3/0.0423 g), a very high specific pore volume of 7250 mm3 g−1 was calculated, which is in fact one order of magnitude larger than the specific pore volumes of PI(TAPB–PMA) synthesized by classical polycondensations using organic solvents and catalysts (670 and 310 mm3 g−1 (ref. 40 and 41); ESI Table S2BET of PI(TAPB–PMA) from HTP is smaller than from conventional synthesis  Table S243 The PSD  is less swollen by solvent molecules from HTP than when synthesized in organic solvents. A further contrast to the conventionally synthesized analoga is that they exclusively feature micropores, while PI(TAPB–PMA) from HTP instead exhibits ultramicropores, and additionally mesopores and macropores, imparted through the unique morphology obtained by HTP.The macroscopic appearance as monolith and the intriguing micromorphology from SEM prompted us to investigate PI(TAPB–PMA)'s porosity. Therefore, gas sorption experiments were carried out using CO) sample . A typic) sample  and is iw 0.8 nm . Note thlyzed ESI, and alllyzed ESI, corresp The PSD  reflectstr = 24 h and Tr = 200 °C. From this starting point, we were curious to determine the effects of employing different reaction parameters, which we discuss in the following.So far, we have demonstrated through the initial benchmark HTP of PI (TAPB–PMA), that an amorphous, highly condensed network monolith exhibiting hierarchical porosity and the – to date – largest cumulative specific pore volume reported for this PI can be obtained in nothing but hot water from a stoichiometric mixture of the comonomers at 2.2Tr, tr, and the use of the additive acetic acid (HOAc), for the following reasons: (i) Tr was varied as previous organic HTS have shown that in some cases a minimum Tr is necessary,25 and that increasing Tr can speed up HT cyclocondensations.27 (ii) tr was varied since it can affect condensation and crystallinity.31 (iii) We also chose to investigate the effects of the addition of HOAc, as its use as morphology modulator in HTP has been reported,31 and was thought to potentially also be able to alter the degrees of condensation and crystallinity. The washed and isolated products of all experiments . A small number of samples depicted differences in FT-IR-ATR spectra, notably when synthesized at 250 °C at long reaction times (tr > 60 h). Specifically, no matter if with or without HOAc, in samples synthesized at 250 °C, at tr = 60 h, the imide modes'  intensity is strongly decreased, and at tr = 72 h and 168 h (7 d) they are barely visible anymore  7 new peaks in the H-bonding region , (ii) a relatively weak but sharp mode appears ∼1700 cm−1, (iii) a strong broad mode at ∼1100 cm−1 that increases from tr = 60 to tr = 168 h, and (iv) a weak and broad mode at ∼900 cm−1 that is only present at tr = 60 h and 72 h, but absent at 168 h. The strong broad mode nicely fits—both in shape and wavenumber—to the asymmetric siloxane (Si–O–Si) vibration, reported in the literature to occur at 1180 cm−1.44 The weak mode at ∼900 cm−1 (only found at tr = 60 and 72 h) as well as the modes in the H-bonding region both nicely fit to silanol (Si–OH) groups (Si–OH bonding is reported in the literature as to occur at 3500–3000 cm−1).44 Therefrom, we infer that at long tr > 60 h at sufficiently high Tr of 250 °C, small parts of the glass liners in which the reactions are performed dissolve and form SiO2. From the absence of imide modes in the IR spectra that otherwise do not point at decomposition, we infer that the cyclic imides are opened up. Opening of the imide moieties should happen trough C–N bond hydrolysis of R–C(O)–N–R′, hence generating RCO2−/RCO2H and RNH2/RNH3+ moieties. Yet, there are no modes characteristic for MS or monomers, which prompted us to wonder if the imide moieties had not only opened up, but in fact reacted with Si–OH functions towards a covalently linked hybrid material. We hypothesize that the covalent linking to occur by condensation of amic acid intermediates R–C(O)N–CO2H , dissolve as silicic species, and, most intriguingly, in fact react with PI(TAPB–PMA) to form a covalently-linked hybrid material.To determine if the properties of PI(TAPB–PMA) could be tuned through the reaction parameters, we screened various reaction conditions. Specifically, we probed s cf. ESI: a high ymore ESI. While tTr = 250 °C. These samples additionally show 3–5 weak but relatively sharp reflections , corresponding to dhkl = 5.5 Å (n = 1); (ii) 17.5° , corresponding to dhkl = 5 Å (n = 1); (iii) 18.6° , corresponding to dhkl = 4.8 Å (n = 1); (iv) 25.2° , corresponding to dhkl = 3.5 Å (n = 1); (v) 27.9° , corresponding to dhkl = 3.2 Å (n = 1). All five are present in the sample with HOAc at Tr = 250 °C and tr = 7 d, and only (ii), (iv), and (v) are present with HOAc at Tr = 250 °C and tr = 2 h, and without HOAc at Tr = 250 °C and tr = 48 h, 60 h, 72 h, and 7 d. We initially suspected that these reflections would correspond to the SiO2 polymorph quartz. Yet an overlay of the diffractograms of our samples synthesized at Tr = 250 °C for long tr, shown in the ESI,2 polymorphs found in the ICDD database  shows no matching reflections. Based on not matching to any SiO2 crystal structure in combination with FT-IR-ATR pointing at covalent linking through Si–O–R, Si–N–R, and SiO–(CO)R, we suspect that the 3–5 new reflections found correspond to a somewhat ordered hybrid material. Interestingly, in a recent work on the HTS of covalently linked SiO2-PI hybrids (hybrids prepared on purpose through employing the linker compound 3-(aminopropyl)triethoxysilane), we found similar reflections.31The XRD patterns of all samples exhibit the two amorphous features discussed earlier  both with and without HOAc, conversion and crystallinity are also not observably affected. Hence, one can conclude that HTP of PI(TAPB–PMA) is a fairly robust process under these conditions. Yet, at 250 °C and long tr (≥48 h), silica species seem to dissolve from the glass liner and in fact appear to react with PI(TAPB–PMA) towards a somewhat ordered hybrid material.In summary from all FT-IR-ATR and XRD results, we conclude that neither the conversion of monomers nor the degree of condensation of the PI network, including its order, are significantly affected by tr (<48 h) elastic, spongy monoliths are obtained. Beyond tr = 48 h, we first obtain brittle monoliths, and subsequently mixtures of macroscopic pieces of different sizes with fine powders. Notably, at tr = 72 h and 168 h, such mixtures are obtained exclusively. The most intact monoliths are also the most elastic ones, and are obtained after 12–24 h at 200 °C. The monoliths are generally more intact and elastic in the absence of HOAc.Macromorphologically, the samples differ relatively strongly. The observed macromorphologies range from elastic, sponge-like monoliths to brittle monoliths and powders, and correlate with the HTP conditions. At short Td) and char yields might also allow for drawing conclusions with respect to chemical composition. In terms of thermal stability, we find Td ∼ 560 ± 35 °C  thus exceeds the reported classically prepared analoga by up to 70 °C using the tangents method  by HTP).41,42 As becomes clear from plotting all determined Td against tr  that are undetected within the limits of FT-IR-ATR, but still have consequences for Td. For tr > 60 h at 250 °C, the Td values decrease drastically (∼250 °C), which points at a disintegration of the networks to oligomers or monomers. The char yields  vary between 42 and 59 wt%, except for samples obtained at 250 °C for long tr, which show considerably higher values  become clear:We observed several distinct micromorphological features that co-exist to different degrees throughout the samples. Specifically, we found eight distinct morphologies. The distinct morphologies, plus that of the MS, are summarized in Tr = 200 °C|no HOAc): (1) thin fibers are found only briefly, at short tr of 2–4 h. For their matching dimensions, we believe that the thin fibers result from MS crystals , compared to corresponding HTP (same Tr) with HOAc (there they are found at 8–168 h). The relative amounts of both thick and thin fibers decrease with increasing tr. (3) Spherical microparticles start to appear at tr = 8 h and persist until the longest tr of 168 h. Their relative amount increases with tr. We think that the degree of condensation increases from the thin fibers to the thick fiber to the sphere morphologies  and neither in large amounts nor repeatedly . We think that they are somewhat a snapshot of the thicker fibers softening and separating into the spherical particles. Therefore, they would be short-lived, and we hence do not find them in many samples. (5) We additionally find “seed” nanoparticles at long tr = 72 and 168 h.(i) s SEM in  serving ogies cf.. (4) PeaTr = 200 °C|with HOAc): the morphologies found and the overall trends with respect to their appearance and abundance are similar to the samples prepared at the same Tr but in the absence of HOAc. Yet, several morphologies are present over slightly different timescales. (1) The thin fiber morphologies appear earlier and persist for longer times, i.e., 2 h ≤ tr ≤ 20 h (compared to 2 h ≤ tr ≤ 4 h in the absence of HOAc). (2) The spherical particles also appear earlier and persist for longer times, i.e., 4 h ≤ tr ≤ 168 h (compared to 8 h ≤ tr ≤ 4 h in the absence of HOAc). As for HTP in the presence of HOAc, their abundance increases with increasing tr. The observation that thin fiber morphologies appear earlier in the presence than in the absence of HOAc points at HOAc initially speeding up the MS dissolution and initial reaction to oligomers. However, the observation that these morphologies persist for longer tr points at HOAc slowing down the subsequent polymerization. (3) In contrast, the thick fibers appear later and persist for longer, i.e., 8 h ≤ tr ≤ 20 h (compared to 2 h ≤ tr ≤ 4 h without HOAc). Again, this points at HOAc slightly slowing down the polymerization at 200 °C. The thick fibers' abundance also increases with increasing tr, as for (Tr = 200 °C|no HOAc). (4) Pearl-chain morphologies are not found at all. As previously discussed, we believe the pearl-chain morphologies to be short-lived, and hence not finding them in SEM images is in our opinion merely coincidental. (5) Seed particles are found significantly earlier, i.e. at tr = 12, 20, and 60 h. We believe that these small particles (≤100 nm in diameter) correspond to SiO2. We do not find indications of SiO2 in FT-IR-ATR or PXRD for these reaction times, and in SEM we only find them in very small relative amounts. Hence, the absence of indication for SiO2 at the corresponding tr, in FT-IR-ATR and PXRD is likely explained through both techniques sensitivity (in PXRD for amorphous structures). That these SiO2 nanoparticle morphologies appear earlier in the presence of HOAc is consistent with the literature: geochemical studies have shown that, e.g., quartz can dissolve in H2O in small quantities,48 and that such dissolution is up to one order of magnitude faster in the presence of (organic) acids.49–51(ii) Tr = 250 °C|no HOAc): (1) no thin fibers are found at any tr, pointing at HTP being much more rapid at 250 °C, which is expected. (2) Thick fibers are found in 3 instances and in low amounts, i.e., at tr = 2, 12, and 60 h. (3) Spherical particles are present through the entire tr span studied, and their abundance decreases with increasing tr. Again, this points at HTP being much faster at the higher tr of 250 °C. (4) Seeds are also present through the entire time span studied, at low but constant abundance. This is consistent with the literature on SiO2 dissolution in H2O and its re-precipitation being faster with increased Tr.48 (5) Pearl-chain morphologies are only found in one sample, at the lowest tested tr of 2 h. (6) Additionally, we find a “wrinkle-covered sphere” morphology at tr = 60 h. We think that this intriguing morphology is also corresponding to SiO2/SiO2-PI hybrids. In fact, such morphologies have been described by Oehler in a geochemical study on the hydrothermal crystallization of silica gels.52 Oehler describes them as “honeycomb-textured microspheres”, likely for the particles' surface textures resembling honeycomb-weathering in sandstone, and explains these morphologies as the result of a complex crystallization process of subsequent steps with different growth rates. (7) Finally, we find spherulitic objects at tr = 72 and 168 h. These are composed of twisted fibers ∼5–10 μm in diameter and ∼50 μm in length. We think that these fibers are composed of the ordered SiO2/PI(TAPB–PMA) hybrid of which we have hypothesized its existence in Section 2.2 from FT-IR-ATR and PXRD data. Spherulitic structures are the most common crystal habit across all crystalline substances, and numerous naturally solution-grown minerals form spherulites.53 In fact, chalcedony, i.e. fibrous quartz, is the most well-known spherulite-forming mineral.53 Fibrous quartz is often consisting of twisted fibers, and is typically generated hydrothermally.54 Hence, finding spherulites of twisted fibers at long tr at the higher Tr of 250 °C is in agreement with our hypothesis of silica-rich SiO2/PI(TAPB–PMA) hybrids.(iii) Tr = 250 °C|with HOAc): the observed micromorphologies are similar to those found at 250 °C without HOAc, but are found over different time spans. Morphologies related to PI(TAPB–PMA) are found later than without HOAc at 250 °C, suggesting, once more, that the presence of HOAC slows down HTP. At the same time, morphologies related to SiO2 or SiO2/PI(TAPB–PMA) seem to be favorably formed in the presence of HOAc. (1) Thin fibers are found at tr = 2 h and 16 h. Since these are related to the early stages of HTP, i.e., an initial polymer deposition on external MS nuclei, their existence points at HOAc slowing down the HTP (compared to 250 °C no HOAC). (2) Thick fibers are only found in one sample, at tr = 8 h. (3) Spherical particles are found at 2 h ≤ tr ≤ 72 h, and interestingly, their amount increases with increasing tr. Again, this further substantiates the hypothesis that HOAc at 250 °C slows down HTP. Without HOAc at 250 °C, spherical particles are present from the beginning and their abundance decreases with tr. (4) We do not find pearl-chain morphologies. (5) Seed particles are present at 2 h ≤ tr ≤ 60 h, and their abundance stays constant throughout that time span. (6) Wrinkle-covered spheres are found at tr = 60 h, and (7) fibrous spherulites are found at the highest tr of 72 h and 168 h. Finally, (8) we observe hollow sphere morphologies. Hollow morphologies are often generally pointing at the dissolution of an object's interior rather than its exterior, because the outer surface is already covered with another material acting as barrier for dissolution. Such morphologies are known for various solution-synthesized materials, e.g. CaCO3.55(iv) tr, the MS [H3TAPB3+]2[PMA2−]3 forms as angular needle-like crystallites. Second, some MS dissolves in high-temperature water (HTW) and starts polymerizing to PI(TAPB–PMA). Third, these initial PI(TAPB–PMA) fragments (suspected to be oligomeric) deposit onto not yet dissolved MS crystals and hence, we find thin needles that roughly match the dimensions of MS crystals. Fourth, thick fibers form by both further polymerization and softening and merging of the thin fibers. Fifth, the thick fibers soften and, driven by minimizing their interface with H2O, start splitting into more roundish morphologies. The pearl-chain morphologies are a snapshot of this splitting. Sixth, the morphologies resulting from the splitting of thick fibers are near-monodisperse spherical PI(TAPB–PMA) particles. Seventh, at prolonged reaction times at 200 °C (tr > 60 h) and at 250 °C right from the beginning, silica (likely in the form of silicic acids) dissolves from the glass liners and starts reprecipitating as nanoparticles, which we refer to as “seeds”. Eighth, SiO2-rich hybrids form through reaction of SiO2 seeds and further silicic acid species with the present PI(TAPB–PMA). The morphologies related to hybrid formation include wrinkle-covered spheres, fibrous spherulites, and hollow spheres (which we speculate to arise from PI leaching out/depolymerizing before subsequently forming hybrids).We have summarized the overall morphological transformation in Tr and long tr were related to SiO2 dissolution and reprecipitation in the form of a hybrid material, we performed EDX analyses , especially considering that all aromatic modes of PI(TAPB–PMA) in ATR-FT-IR are still present and that we also find amide modes. At this point, we cannot tell if Al and B are also incorporated in what we suspect to be hybrids, or form boro-/aluminosilicate species that coexist with the presumed PI(TAPB–PMA)/SiO2 hybrid.To ascertain our hypothesis that several morphologies obtained at high s see ESI. EDX res3TAPB3+]2[PMA2−]3 to check if any of the morphologies in the HTP of PI(TAPB–PMA) correspond. It is conceivable, and has been previously reported, that monomer salts can undergo SSP under HT conditions when they are not soluble, i.e., SSP of MS particles occurs in dispersion in high-temperature water. However, SEM analysis clearly evinces that PI(TAPB–PMA) from SSP appears as shape copies of the MS crystals  experiments of [Hs see ESI. This is2.4cf. Section 2.3) was ensured through manual expert interpretation of 437 SEM images. Our images are complex through often featuring several of the identified distinct morphologies in one and the same picture. Since manual interpretation is tedious, we were wondering if images as complex as ours could be analyzed more efficiently in an automated fashion. This interest is in line with current major efforts of the chemistry community: recent examples to best profit from machine support include e.g., employing robotics,38 predicting compounds,57 discovering reactions,58 and performing and analyzing physicochemical characterizations.59 Computational SEM image analysis, notably automated image recognition and categorization, has been recently reported.60–63 Yet, the images analyzed in these prior reports are significantly less complex than our images. In fact, most computational SEM image analyses show low accuracy when confronted with images containing elements of multiple categories.60 Here, we aimed at automatedly clustering our SEM images by the morphologies they contain, specifically through using artificial neural networks (ANNs), a type of machine-learning methods.64 ANNs comprise an input layer, one or many hidden layers, and an output layer, each containing hundreds or thousands of so-called nodes. Nodes are computational devices performing a weighted simple function on a set of inputs and the outputs of the nodes are fed as inputs to other nodes.65 In an ANN computation, the weights of the nodes are changed iteratively , and in the end an overall output (harvested at the output layer) results from a somewhat black box (the hidden layers) in response to the initial input (fed in at the input layer).65 ANN approaches are well suited for image analysis in general, and to our knowledge, all reports on automated SEM image analysis employ ANN approaches.60–63 To implement ANNs for analyzing our SEM images, we decided to use pre-trained ANNs. Furthermore, as conventionally done for image clustering, we cut away the output layer of the used ANNs, since output layers are conventionally used for prediction . Consequently, we analyzed the last connected hidden layer instead of the output layer. The numerical values harvested at the last hidden layer don't have any physical meaning and are therefore termed pseudo-features. Despite pseudo-features not containing any physical meaning, the input of two similar images should result in similar pseudo-feature values, which allows for clustering the input images as recently shown for the classification of cell microscopy images.66 The employed image treatment and analysis pipeline is displayed in i.e., out of the focused area of the image). Areas that do not contain any morphology arise from the sample preparation: our samples for SEM imaging are prepared by sprinkling a dry powder of the sample onto a carbon-tape coated sample holder prior to sputtering with a conductive alloy. Hence, there are areas of the sample which do not contain any object and display just the bare, sputtered carbon tape. Both areas devoid of objects and areas depicting objects in the far background were removed after identifying them computationally using the Otsu threshold , 1024 (MobileNet), or 2048 . The pseudo-features’ numerical values were normalized . In n-dimensional pseudo-feature space , while maximizing the distance between two dissimilar images. As benchmark test, we decided to calculate the intra-image (tiles of same image) as well as the inter-image (tiles of different images) Euclidean distances and calculated the Cohen's D (effect size indicating the standardized difference between two means) between the two distributions . We found that using the original pseudo-feature vectors resulted in better results than any of the normalization methods. Especially the scaling methods Robust and MaxAbs have a detrimental impact on SEM image classification, and result in Cohen's D ≤ 0.25 for all six ANNs , outside of the cluster, or between clusters (separation). The silhouette value can range from −1 to +1, where a high value indicates good cohesion. Hence, an appropriate clustering methodis reflected in high silhouette values, while low/negative values indicate a subpar clustering . Applying the silhouette method, we identified an ideal number of clusters k between 3 and 6 clusters  during HTP , use of HOAc (yes vs. no), and reaction time (short ≤ 24 h and long > 24 h), see Tr stages of the HTP of PI(TAPB–PMA), while “seed”-decorated morphologies are characteristic for silica/hybrid formation at high Tr and long tr. Regarding the presence of HOAc  and thin fibers (cluster 4) are predominantly found at tr ≤ 24 h, while seed-covered morphologies (cluster 2) predominantly form at long tr. This is again in agreement with our manual interpretation. Finally, we compiled these results into proposed reaction trajectories , offering an easy scalable unbiased analysis for such complex SEM images. The automated analysis detects only part of the morphologies that we have manually identified, yet, this is likely to be surmountable by an increased fine-graining (higher number of image tiles), and a full analysis of all images in appropriate subgroups subdivided by magnification ranges.Taken together we could show that ANNs are indeed capable of detecting the subtle differences that lie within morphologically complex SEM images, managing to differentiate such mixed morphologies. We identified that the unnormalized space of ResNet50 pseudovectors as for our research question best way to analyze these morphologies. Furthermore, we have shown that while certain ranges in magnification can be compensated by this technology, too large differences cannot. Also, the use of dimensional reduction technologies such as PCA and t-SNE as well as standard clustering techniques such as agglomerative clustering offer fast and easy tools to successfully automatically detect clusters of morphologies. We moreover showed how once successfully identified, one can investigate the role of reaction parameters on the formation of such morphologies, even potentially inferring reaction trajectories. While manual annotation of these morphologies of SEM images is time consuming the automated analysis manages to detect clusters of images that are based on the morphologies within several minutes  and microfibers (minor component). Therefore, we expected that employing stirring during HTP would exclusively generate microspheres. To test this hypothesis, we performed several HTP experiments at Tr = 200 °C, without HOAc, and at tr = 4 h in a stirred microwave (MW) reactor (V(H2O) = 10 mL, V (vessel) = 30 mL, see ESItr = 4 h as being sufficient, since (i) MW-assisted heating is generally more efficient than heating batch autoclaves by placing them in ovens, and (ii) our reaction parameter screening had shown that tr = 2 h was sufficient to form PI(TAPB–PMA). The thereby synthesized PI(TAPB–PMA) was reproducibly obtained as powders of exclusively near-monodisperse spherical microparticles  discussed in Section 2.3, we speculated that PI(TAPB–PMA) features some degree of flexibility on a molecular level, which might allow for creep at increased temperatures in the dry state. Therefore, sintering into bigger objects should be possible. For this, the near-monodisperse particles obtained through MW-assisted HTP would provide nicely homogeneous starting powders. As bigger amounts are necessary for sintering, we scaled the stirred MW-assisted HTP up by moving from 30 mL to 100 mL vials in an MW reactor featuring a carousel for simultaneously running 4 experiments  as fine brown powder. SEM analysis (i.e. neither first order (peaks) nor higher order (deflection points) phase transitions  possesses the ability to soften. We attempted sintering by warm-pressing, a technique widely used for the compaction of powder-based polymers and polymer-derived materials.75 Therefore, the entire 7.364 g of PI(TAPB–PMA) powder were introduced into a steel cavity with an inner diameter of 40 mm and were uniaxially compacted at 80 MPa. As release agent between the steel punches and the powder, Kapton foil was used. The temperature of the die was increased to 350 °C (heating rate 6 K min−1), and the maximum temperature was held for 2 h. The pressure was adjusted accordingly when required. After cooling to room temperature, the pressure was reduced and the compacted part was removed from the mold. Thereby an intact, macroscopically highly homogenous and smooth cylindrical specimen of diameter of d = 39.96 mm and height h = 5.06 mm was obtained (−3 of the pellet. SEM images of the specimen's outer surface (2) sorption measurements at 195 K s intrinsic ultramicroporosity is not affected by the processing via sintering. Finally, we tested the pellet mechanical performance by flexural strength measurements using a three-point flexural test setup, following EN ISO 178  and benign (through using solely water as the reaction medium). The synthesized PI network shows high thermal stabilities of >550 °C. At relatively short tr the products are obtained as sponge-like monoliths, and at longer tr as powders. We studied the sorption properties of PI(TAPB–PMA) using CO2 and N2 as analyzing gases, as well as employing Hg porosimetry measurements. These analyses revealed a trimodal porosity, comprising (i) ultra-micropores (<0.8 nm), (ii) a small amount of mesopores (<50 nm), and (iii) a majority of macropores (1 μm–100 μm) resulting in a surprisingly high specific pore volume of 7250 mm3 g−1. Furthermore, we observed a complex micromorphological evolution that manifests as a function of the studied reaction parameters . Observed morphologies comprise fiber-like structures and near monodisperse spherical particles as well as intermediate structures such as pearl-chain morphologies. At long tr (>48 h at 250 °C), silica dissolves from the glass liners in which the reactions were performed, and as we hypothesize, at even longer tr reacts with the present PI networks towards hybrid materials. We furthermore developed an automated computational image analysis pipeline, which confirmed the morphology evolution determined previously by manual expert interpretation of ∼450 SEM images. Finally, using MW-assisted stirred HTP, we show that PI(TAPB–PMA)'s morphology can be controlled towards obtaining exclusively near-monodisperse microparticles. Upscaling these stirred MW- assisted HTP experiments, we could prepare a sufficient amount of microspheres to process them into a dense cylindrical specimen by warm-pressing. Compared to conventional PI processing, which uses harsh and armful solvents such as NMP or cresols, warm-pressing is benign for using solely heat and pressure. The specimen from warm-pressing retained PI(TAPB–PMA)'s intrinsic micro- and ultramicroporosity, while the majority of macropores are lost through compacting.With this contribution we show for the first time that HTP can generate fully condensed PI networks. The process is a fast (full condensation achieved in as short as 2 h), easy (the synthesis consists of nothing but mixing the comonomers in water, heating that dispersion in an autoclave to This project was designed by MMU. ML performed all small-scale syntheses as well as all PXRD, TGA, and ATR-FT-IR measurements, and part of the SEM analyses. HM performed part of the SEM analyses as well as EDX analyses. DACI performed upscaling syntheses, as well as ATR-FT-IR and DSC analyses of the upscaled samples. TK performed and analyzed Hg porosimetry, performed processing by warm-pressing, and mechanical characterization of the specimen. JR and AT performed gas sorption measurements and analyzed the data. MC and JM performed the computational image analysis. MMU and ML wrote the manuscript, with input from all coauthors. ML, DACI and MMU prepared the figures. All authors have given approval to the final version of the manuscript.There are no conflicts to declare.TA-009-D1TA01253C-s001


Argania spinosa (L.) Skeels is an endangered plant species endemic to Morocco. In recent years, attempts to develop in vitro regeneration systems for this species were made. However, rooting and acclimatization of in vitro plants have been a bottleneck for successful propagation. In the present study, the effects of different concentrations of auxins, putrescine, silver nitrate (AgNO3) and ammonium nitrate on the in vitro rooting of adventitious shoots of two argan genotypes “Mejji” and “R’zwa”, were evaluated. The highest rooting percentages (86.6% in “Mejji” and 84.4% in “R’zwa”) were observed on Murashige and Skoog (MS) medium modified by reducing the ammonium nitrate concentration and supplemented with 1.5 mg L−1 indole-3-butyric acid (IBA), 0.5 mg L−1 1-naphthalene acetic acid (NAA), 2 mg L−1 AgNO3 and 160 mg L−1 putrescine. This medium resulted in the development of a good root system after only 10 days of culture. Plantlet acclimatization was carried out using different substrate mixtures, and high survival rates (100%) were observed when the substrate contained either peat alone or a sand–peat mixture . The high percentages of rooting and acclimatization reported in the present study are of high importance for rapid and large-scale propagation of this endangered species. Argania spinosa (L.) Skeels) is a forest species belonging to the family Sapotaceae growing endemically in Morocco [Argan  and M (MS without NH4NO3) media. However, the shoots cultured on RM medium showed the highest average number of roots after 75 days of culture (4.6 in “Mejji” and 4.4 in “R’zwa”). In the M medium, significantly lower rooting percentages were observed  plus putrescine and/or AgNO3  resulted in the highest rooting percentages (86.6% in “Mejji” and 84.4% in “R’zwa”), an average root length of 3.5 cm in “Mejji” and 3.4 cm in “R’zwa”, and an average number of roots per shoot of 6.3 in “Mejji” and 6.7 in “R’zwa”. This combination showed root emergence within the first 10 days of culture  and putrescine (160 mg L−1). The beneficial effects of polyamines in general and putrescine in particular on rooting were reported in many other plant species, such as olive [−1 NAA. Moreover, the roots initiated from calli were fragile and easily detachable.Argan tree is one of the most recalcitrant species in tissue culture. Indeed, the adventitious root formation is very difficult to achieve, while it is critical for successful vegetative propagation of this species . The devas olive ,33, hazeas olive , almond as olive  and teakas olive . Cristofas olive  showed tas olive ; Weiss aas olive ; Saini eas olive ) reporteas olive  reportedas olive ,42. Accoas olive  and Hartas olive , root fo−1 NAA and 1 mg L−1 IBA inhibited adventitious rooting in seedling-derived shoots. However, in shoots produced vegetatively from microcuttings, Lamaoui et al. [−1 IBA and 1 mg L−1 NAA for root induction, whereas Koufan et al. [−1 NAA and 0.5 mg L−1 6-benzylaminopurine (BAP). On the other hand, Benbya et al. [Our results also showed that combining IBA and NAA resulted in a higher rooting frequency than that observed when IBA was used alone. However, increasing NAA concentration decreased the rooting percentage. This highlights the specific requirement of argan shoots in terms of auxin types and concentrations for efficient in vitro rooting. The effects of NAA and IBA on root induction have been evaluated by different researchers during both in vitro and conventional propagation of argan. Justamante et al.  reportedi et al.  recommenn et al.  recommena et al.  found th3 on in vitro rhizogenesis were also investigated. The findings of the present study showed that AgNO3 promotes root formation and the development of vigorous roots within 30 days of culture, with no callus formation. The optimal concentration of AgNO3 was 2 mg L−1. This concentration improved the root system of shoots, which results in increased plantlet survival and better growth and development. In many plant species, such as Prosopis cineraria [Vanilla planifolia [Coffea arabica, C. canephora [Rotula aquatica [3 has improved in vitro rooting. Silver nitrate is known to be an ethylene inhibitor. In fact, Ag+ ions produced in the culture medium play the role of an ethylene receptor, thus ensuring easy assimilation of the energy available in the culture medium, which improves cell division and growth. Venkatachalam et al. [3 on rooting of the recalcitrant medicinal tree Prosopis cineraria. Klíma et al. [Arabidopsis seedling roots. They also demonstrated that silver ions could block ethylene-induction in auxin changes. Bais [3 exerts a feedback inhibition on ethylene synthesis and stimulates polyamine biosynthesis by an enhanced use of S-adenosylmethionine. Ethylene can also influence callus formation [The effects of AgNOineraria , Vanillaanifolia , Coffea anephora , and Rotaquatica , AgNO3 hm et al.  reporteda et al.  showed ta et al.  reporteda et al. , silver a et al.  indicatees. Bais  reportedormation . These cormation .4NO3 concentration was reduced to 825 mg L−1, and the culture medium was supplemented with auxins (IBA and NAA), putrescine and AgNO3. This results in vigorous root development within only 10 days of culture. This reflects the specific requirements of argan microshoots for root induction. In fact, some components of the culture medium allow more cells to be used for root induction, which improves the rooting ability of shoots [4NO3 concentration on in vitro rooting was first demonstrated in apple [4NO3 concentration reduced the rooting ability of Persian walnut. In Lavandula spp., rooting was promoted by reducing the concentration of MS micronutrients to ½ or ¼ and by adding NAA to the culture medium [Rosa spp [The findings of the present investigation showed that successful in vitro rooting and development of vigorous roots in argan shoots was obtained when NHf shoots . Similarin apple . Vahdatiin apple  found the medium . SimilarRosa spp .Plantlet acclimatization is a crucial step that determines the efficiency of the whole micropropagation process. During acclimatization, regenerants are exposed to new growth conditions causing biotic and abiotic stresses, such as water loss, tissue dehydration and synthesis process reduction . Accordi4NO3 concentration to 825 mg L−1; and M, Murashige and Skoog basal medium modified by omitting NH4NO3. All media were supplemented with 30 g L−1 sucrose and 8 g L−1 agar. The medium pH was adjusted to 5.8 before autoclaving at 120 °C and 103 kPa for 20 min. The chemicals used in this study were purchased from Sigma .The basal medium used in the present study was that of MS medium  containiMature seeds of argan genotypes “Mejji” and “R’zwa” were harvested from trees located in Essaouira province, Morocco. The seeds of the genotype “R’zwa” were collected from a tree located approximately 7 km southeast of Essaouira city (31°26′48.17″ N 9°43′43.74″ W), while those of the genotype “Mejji” were collected from a tree located about 45 km east of Essaouira city (31°32′49.71″ N 9°22′32.44″ W). From each tree, 100 seeds were collected.Both the trees are characterized by high fruit yield. However, they are morphologically different. Genotype “Mejji” has a bigger size and produces round-shaped fruits, while genotype “R’zwa” produces ellipsoid-shaped fruits .−1 GA3 for 12 h and then cultured for 35 days on sucrose-free 1/2MS medium modified by omitting ammonium nitrate [The seeds were surface-sterilized by immersion in 70% ethanol for 2 min, followed by immersion in 30% sodium hypochlorite solution containing a few drops of Tween-20 for 15 min. The seeds were then immersed in 0.1% mercury chloride for 10 min, followed by 3 rinses with sterile distilled water, then by immersion in 0.2% polyvinylpyrrolidone solution for 60 min . To prom nitrate .−1 BAP for 4 weeks under dark conditions to induce organogenesis. The organogenesis rate was 79.1% (1.8 shoot buds per explant) in “Mejji” and 62.5% (1.9 shoot buds per explant) in “R’zwa” [−1 BAP and 2 mg L−1 gibberellic acid (GA3) for 4 weeks under a 16 h photoperiod [The epicotyl explants were excised from in vitro germinated seedlings and cultured on semi-solid MS medium supplemented with 2 mg L “R’zwa” . For shotoperiod . The adv−1), NAA , putrescine (160 mg L−1) and/or AgNO3  (−2 s−1 provided by cool white fluorescent tubes). This experiment lasted for 100 days, and the cultures were transferred to fresh medium at 4-week intervals. The percentage of shoots forming roots, the mean number of roots per shoot and the average length of roots were recorded every 5 days of culture. Moreover, the amount of callus formed was visually estimated as follows: 0C: no callus, C+: low amount of callus, C++: moderate callogenesis, C+++: high amount of callus. The time required for root induction was determined by visually inspecting the cultures every 5 days. The experiment was performed in three replicates, with 30 shoots per treatment, and was repeated twice.Healthy shoots (2–3 cm long) of argan genotypes “Mejji” and “R’zwa”, obtained through direct organogenesis as previously described, were singled out and cultured on PGR-free MS medium for 2 weeks. Subsequently, the shoots were transferred to different rooting media (MS or modified MS media) supplemented with various concentrations of IBA (0 or 1.5 mg L mg L−1) . The expw/w/w) and placed in the growth room. To maintain high humidity, the pots were covered with transparent polyethylene bags. After 2 weeks, the plantlets were transferred to the glasshouse. They were maintained at 25 ± 2 °C under light conditions and regularly irrigated with Hoagland and Arnon’s nutrient solution [The rooted plantlets obtained from the best treatment were removed from the rooting medium, and their roots were carefully washed with distilled water to remove adhered agar. The plantlets were then transferred to plastic pots (one plant per pot) containing autoclaved mixtures of sand, peat and forest soil in different proportions 1:0:0, 0:1:0, 1:1:1, and 1:1:0 (solution . MeanwhiData are expressed as means and standard deviations (SD). All experiments were set up in a completely randomized block design. One-way analysis of variance (ANOVA I) was performed to test for significant differences among the different treatments. The least significant difference test (LSD) was used for post hoc mean separation at the 5% significance level. Tests for normality and homogeneity of variance were performed before ANOVA. Before analysis, all percentage data were arcsine transformed.4NO3 concentration to 825 mg L−1) supplemented with 160 mg L−1 putrescine, 2 mg L−1 AgNO3, 1.5 mg L−1 IBA and 0.5 mg L−1 NAA. In this medium, rooting started after only five days of culture. Moreover, the development of a healthy and vigorous root system was observed, with no or low callus formation. In fact, adding putrescine, NAA, IBA and AgNO3 promoted root formation, inhibited callogenesis and reduced the time required to produced rooted plantlets ready for acclimatization. AgNO3 had an inhibitory effect on callus formation and improved the quality of the root system. The addition of NAA at low concentration increased the percentage of rooting and the number and length of roots. Regarding acclimatization, a high survival rate of 100% and normal growth and development of plants were observed in the peat–sand mixture or when peat was used alone. The reported results will be used for rapid and large-scale propagation of this endangered plant species and to rehabilitate the argan ecosystem. Further studies are currently undertaken to test the developed protocol’s suitability on other superior argan genotypes characterized by high fruit yield and high oil content.We described an efficient protocol for in vitro rooting and acclimatization of micropropagated argan shoots. The optimal medium for shoot rooting was RM medium (MS medium modified by reducing NH


Age, gender, education status, and occupation significantly differed among increased substance users, regular substance users, and nonsubstance users. Time spent on the Internet was significantly longer during the pandemic (p < 0.001) and 72% of participants reported increased dependence on the Internet. Compared to regular Internet users, increased users were more likely to be younger and female. Multiple logistic regression analysis revealed that age <33 years , increased substance use , and increased Internet use  were significantly associated with depression. Moreover, anxiety was significantly related to female gender , “unmarried” status , nonstudents , and increased substance use . Although there was a significant decrease in social substance use during the pandemic, more attention should be paid to increased Internet use. Increased Internet use was significantly associated with both anxiety and depression, and increased substance use was related to depression. Professional support should be provided to vulnerable individuals to prevent addiction.The coronavirus disease 2019 (COVID-19) has adversely influenced human physical and mental health, including emotional disorders and addictions. This study examined substance and Internet use behavior and their associations with anxiety and depression during the COVID-19 pandemic. An online self-report questionnaire was administered to 2196 Chinese adults between February 17 and 29, 2020. The questionnaire contained the seven-item Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9), questions on demographic information, and items about substance and Internet use characteristics. Our results revealed that males consumed less alcohol ( Since December 2019, COVID-19 has emerged and spread rapidly across the globe. The World Health Organization declared COVID-19 a pandemic on March 11, 2020 , the preSubstance use and COVID-19 are closely related. Individuals with substance use have an increased risk of COVID-19 infection and of developing severe symptoms . SmokingDuring the pandemic, to slow down the spread of the virus, people were advised to stay at home, and outdoor social activities were drastically reduced. Empirical evidence suggests increased consumption of online entertainment. An online survey of the general population in China showed that during the pandemic, 46.8% of participants reported increased dependence on Internet use, while 16.6% reported longer Internet use duration . AnotherPsychological distress has become a significant public health issue during the pandemic and has attracted the attention of researchers and the public alike. A nationwide multicenter cross-sectional study on 19372 participants in China reported that 11–13.3% had anxiety, depressive, or insomnia symptoms, and these were associated with working as frontline medical staff, living in Hubei Province, having close contact with patients with COVID-19, being 35–49 years old, and not engaging in outdoor activities for 2 weeks , 22. HowDue to the interactive impact of the pandemic on substance use, the changing trend of substance use deserves further clarification. Most studies have focused on gaming or certain specific Internet use behavior during the pandemic, but few have comprehensively investigated the full spectrum of Internet use behavior. Few studies have reported on the relationship between addiction behavior and emotions during the pandemic. This study examined substance and Internet use behavior and their associations with anxiety and depression during the COVID-19 pandemic. We hypothesized that there has been a decrease in substance use and an increase in Internet use during the pandemic, and that increases both in substance use and Internet use are related to anxiety and depression.The present study was an anonymous online survey of the general population in China. It was conducted from February 17 to 29, 2020. Participants were recruited through the widely used Chinese questionnaire survey website, “Questionnaire Star Platform.” The QR code and link to the survey were shared in group chats and in the “Moments” section of the authors’ WeChat. Participants were instructed to complete the questionnaire online. At the beginning of the web page, a brief introduction was presented that included a detailed background, purposes of the study, and study procedures. Individuals who provided consent for participation and met the following criteria were recruited: of Chinese nationality, at least 18 years old, living in China, and Chinese speaker. Individuals who were infected with COVID-19 and those who did not complete the questionnaire were excluded.The Ethics Committee of the Second Xiangya Hospital of Central South University approved the study protocol. All participants answered a yes–no question to indicate their voluntary participation in the study prior to completing the questionnaire.The questionnaire consisted of four parts: demographics, substance use, Internet use, and emotion (depression and anxiety). Demographic variables included gender, age, education, occupation, marital status, and residence (Hubei vs. other provinces of China).Participants provided information concerning their use of alcohol, tobacco, sedative-hypnotic, areca nut, illicit drugs , and other substances. Example questions were asked: “One month before the COVID-19 outbreak, which of the following substances did you use?” and “After the COVID-19 outbreak, which of the following substances did you use?” Answer options included “none,” “alcohol,” “tobacco,” “sedative-hypnotic,” “areca nut,” “heroin,” “methamphetamine,” “ketamine,” “cocaine,” “cannabis,” and “others” (as specified by the responders). Individuals should choose one or more options. Participants were also asked, “How did your main substance use behavior change after the COVID-19 outbreak?” Responses were scored on a 5-point scale: 1 = using a lot more, 2 = using a little more, 3 = no change, 4 = using a little less, and 5 = using much less. Participants who reported using “a lot more” or a “little more” since the outbreak were considered increased substance users. Participants who reported “no change” or “using less” were considered regular substance users, while participants who reported no substance use were considered non-drug users , 24.The following questions were asked to obtain information about Internet use: “How many hours did you spend on the Internet every day before and after the COVID-19 outbreak?” and “What was your main Internet use behavior before and after the COVID-19 outbreak?” Answer options included “Internet gaming,” “short videos,” “films and television,” “network novels,” “shopping online,” “browsing health information,” and “others” (as specified by the responders). Participants were then asked, “How did your main Internet use behavior change after the COVID-19 outbreak?” Responses were scored on a 5-point scale: 1= using a lot more, 2 = using a little more, 3 = no change, 4 = using a little less, and 5 = using much less. Participants who reported using a lot more or a little more Internet after the outbreak were considered increased Internet users, while participants reporting no or little change in Internet use were considered regular Internet users.The 7-item Generalized Anxiety Disorder Scale (GAD-7) was used to evaluate the presence and severity of general anxiety . All iteThe presence of depression in the past 2 weeks was assessed using the Chinese version of the Patient Health Questionnaire (PHQ-9) . All iteχ2) test. Differences in demographic characteristics among groups were compared using a chi-square (χ2) test, and differences in online time and PHQ-9 and GAD-7 scores among subgroups were examined by performing Wilcoxon rank-sum and Kruskal-Wallis H tests. To test whether increased addiction behavior was significantly associated with anxiety and depression, a multiple logistic regression with a backward stepwise method was used, which included depression and anxiety as predictors, and all significant factors in the univariate analysis as covariates. Odds ratios (ORs) and 95% confidence intervals (CIs) were generated for each variable. The significance level was set at P < 0.05 (two-sided). To adjust for the multiple post hoc tests, the significance level was set at P < 0.01 (two-sided). All statistical analyses were conducted using the SPSS 22.0.Self-reported substance and Internet use characteristics were described and compared by performing a chi-square , 1445 (65.8%) were women, and 89 (4.1%) were Hubei residents.p < 0.001); 3.2% reported that they used areca nut during the pandemic, which was significantly lower than the 3.9% reported before (p = 0.004). As shown in Table p < 0.001 for alcohol and p = 0.012 for areca-nut). There was no significant difference in the rates of tobacco use, sedative-hypnotics, and other substances used before and during the pandemic . Before the COVID-19 outbreak, the top four Internet use behaviors were films and television (21.4%), short videos (15.5%), shopping online (12.9%), and Internet gaming (12.3%). In contrast, during the pandemic, the top four Internet use behaviors were browsing health information (30.3%), films and television (20.6%), short videos (14.7%), and Internet gaming (12.8%). In addition, only browsing health information and Internet gaming use showed increases in percentages among all Internet use behaviors. More details are presented in Table Time spent on the Internet during the pandemic was found to be significantly longer than before . The increased Internet users’ scores on the PHQ-9 and GAD-7 were significantly higher than those of regular users .A total of 278 (12.7%) participants had depression (PHQ-9 score ≥ 10), and 190 (8.7%) had anxiety (GAD-7 score ≥ 10). The increased substance users’ scores on the PHQ-9 and GAD-7 were significantly higher than those of regular and non-users  and have increased substance (p < 0.001) and Internet use (p < 0.001). Anxiety was more prevalent among females (p = 0.038), nonstudents (p < 0.001), unmarried persons (p = 0.024), and increased substance users (p < 0.001) (see Table p < 0.001), increased substance use , and increased Internet use . Further, anxiety was significantly related to female gender , “unmarried” status , nonstudents , and increased substance use   and anxiety (8.7%) among the general population in the present study was lower than those reported in previous studies  –56. The There are several limitations to this study. First, as a cross-sectional survey, it could not determine the causal relationship between increased addiction behavior and mental health indicators. Second, self-reported changes in addiction behavior are arguably unstandardized and may be an unreliable and insufficient measure of the construct. Furthermore, pre-pandemic information may entail recall bias. Finally, the convenience sampling method and the limited sample representativeness limit the generalizability of our findings. Larger scale and longitudinal cohort studies should be conducted to investigate addictive behaviors during and after the pandemic.This study investigated changes in substance and Internet use during the COVID-19 pandemic. Our findings provide evidence of a significant association between increased addictive behaviors and psychological problems (such as depression and anxiety) during the pandemic. At this stage, addiction-related issues should be considered. Therefore, it is necessary to establish proper measures and support services for such vulnerable populations. The results also represent a preliminary step toward further understanding the relationship between increased addictive behaviors and potentially related factors (gender and age) during the pandemic. Nevertheless, due to the cross-sectional design and limited generalizability of this study, more studies are warranted to investigate these associations.


Reduced integrity of neural pathways from frontal to sensory cortices has been suggested as a potential neurobiological basis of attention-deficit hyperactivity disorder. Neurofeedback has been widely applied to enhance reduced neural pathways in attention-deficit hyperactivity disorder by repeated training on a daily temporal scale. Clinical and model-based studies have demonstrated that fluctuations in neural activity underpin sustained attention deficits in attention-deficit hyperactivity disorder. These aberrant neural fluctuations may be caused by the chaos–chaos intermittency state in frontal-sensory neural systems. Therefore, shifting the neural state from an aberrant chaos–chaos intermittency state to a normal stable state with an optimal external sensory stimulus, termed chaotic resonance, may be applied in neurofeedback for attention-deficit hyperactivity disorder. In this study, we applied a neurofeedback method based on chaotic resonance induced by “reduced region of orbit” feedback signals in the Baghdadi model for attention-deficit hyperactivity disorder. We evaluated the stabilizing effect of reduced region of orbit feedback and its robustness against noise from errors in estimation of neural activity. The effect of chaotic resonance successfully shifted the abnormal chaos-chaos intermittency of neural activity to the intended stable activity. Additionally, evaluation of the influence of noise due to measurement errors revealed that the efficiency of chaotic resonance induced by reduced region of orbit feedback signals was maintained over a range of certain noise strengths. In conclusion, applying chaotic resonance induced by reduced region of orbit feedback signals to neurofeedback methods may provide a promising treatment option for attention-deficit hyperactivity disorder. Attention-deficit hyperactivity disorder (ADHD) is a behavioral disorder underscored by inattention, impulsivity, and hyperactivity. ADHD is one of the most common neurobehavioral disorders presenting for treatment in both children and adolescents  feedback method, which reduces the absolute local maximum and minimum values of non-linear map functions in dynamical systems to induce attractor-merging bifurcation where chaotic resonance emerges   is regulated by the competition between excitatory and inhibitory neural populations ) represents the map function for x(n). w1 and A indicate the synaptic weights of input and output for inhibitory neural populations, respectively. w2 and B represent the synaptic weights of input and output for excitatory neural populations, respectively. The positive and negative values of x(n) correspond to neural activities in the activate and resting state for neural population, respectively. K is an attenuation coefficient of frontal neural activity. In the Baghdadi model, frontal neural dynamics x(n) is determined by output from the frontal cortex: B tanh(w2x(n)−A tanh(w1x(n)) and its feedback through sensory cortex with attenuation K in Equation (2)   to the periodic state. A methodological chart of the system for this control method is shown in x(n) is controlled by RRO feedback signals Cu(x) and a periodic input signal S(n) = α sin(2πn/p), as follows:The conventional neurofeedback methods enhance the neural pathway by the repeated daily-temporal-scale training  is an example reference of the desired neural activity corresponding to the healthy condition, i.e., the neural activity observed as lower temporal fluctuation in electroencephalogram (EEG) ) and periodic input signal S(n) are implemented by an external sensory stimulus. In this study, we utilized xd = 0 and σ = 1.0, because the structure of return-map of Equation (1) has a point symmetry at around x = 0 with local maximum and minimum values of the map function located within the region −σ < x < σ (σ = 1.0) , we used the four p periods: 4, 8, 16, and 32.Here, n) :To develop the RRO feedback signals based on actual frontal neural activity, the influence of measurement errors on RRO feedback signals must be evaluated. Therefore, in addition to the noise-free condition, we evaluated the influence of measurement errors on RRO feedback signals using Gaussian white noise ξ was used. To evaluate the chaotic state of the Baghdadi model, the Lyapunov exponent was measured by the following  indicates M perturbed initial conditions to the orbit of x(n) applied at n = n0 + (k − 1)τ. The temporal development during tl ∈ [0 : τ] is x′(n) is an orbit-applied perturbation. The chaotic and periodic state of x(n) correspond to λ > 0 and λ < 0, respectively.Here, x(n) is induced by attractor-merging bifurcation. To detect this bifurcation, the conditions F(fmax) + Cu(fmax) and F(fmin) + Cu(fmin) were utilized. F + Cu = 0 corresponds to the attractor-merging bifurcation point; in the attractor-merging condition, F(fmax) + Cu(fmax) < 0 and F(fmin) + Cu(fmin) > 0 are satisfied  and S(n), we utilized their correlation coefficients with considering time delay τ:To evaluate the synchronization between n. X represents the binarized x(n) value, i.e., X(n) = 1 in x(n) ≥ 0 case and X(n) = − 1 in x(n) < 0 to focus on the CCI behavior. In this study, τ was set to the value for arg maxτ Corr(τ) in each time series of x(n). arg maxτ Corr(τ) was assessed among ten trials using different initial conditions of x(0).where 〈·〉 denotes the average in S(n) and RRO feedback signal Cu(x), the following perturbation was used:To evaluate the amount of perturbation for the applied signals consisting of input periodic signal n .where < · > is the average in A and attenuation coefficient of frontal neural activity K in the Baghdadi model. A and K and attractor-merging condition F = 0 in the case of . In the region for breaking the attractor-merging condition, i.e., F(fmax) < 0, F(fmin) > 0 and arising chaotic activity λ>0, CCI, which corresponds to abnormal neural activity in ADHD, emerges. The system behavior under the conditions of fixed K or A values is depicted in A at K = 1.0 and dependence on K at A = 13.0, respectively, by the bifurcation diagram of frontal neural activity x, Lyapunov exponent λ, and attractor-merging condition F. The results demonstrate that CCI (F(fmax) < 0, F(fmin) > 0, λ>0) corresponding to abnormal neural activity in ADHD, which was demonstrated by Baghdadi et al.   + Cu(fmax) > 0 and F(fmin) + Cu(fmin) < 0; consequently, x(n) stayed in either the positive or negative region of x(n). The dependence of the system behavior on RRO feedback strength C was evaluated in more detail. x, Lyapunov exponent λ, and attractor-merging condition F + Cu in attenuation K = 0.89, 0.9, 0.91. CCI behavior between positive and negative x regions (F(fmax) + Cu(fmax) < 0, F(fmin) + Cu(fmin) > 0, λ>0) was suppressed (F(fmax) + Cu(fmax) > 0, F(fmin) + Cu(fmin) < 0) in the region of feedback strength C ≳ 0.23, 0.28, 0.34 in the cases with K = 0.89, 0.9, 0.91, respectively. Additionally, the periodic windows appear at around C = 0.05, 0.1, 0.15, in the cases with K = 0.89, 0.9, 0.91. However, the RRO feedback signal does not always produce these periodic windows with lower temporal fluctuation corresponding to healthy condition. Therefore, the external periodic input S(n) is needed for the transition to the lower temporal fluctuation, which is dealt in section 3.3.To control CCI behaviors caused by the abnormal imbalance in excitatory and inhibitory neural activity and the weaker feedback of neural pathways from the frontal and sensory cortices shown in x(n) see  in the c 0.5 see . In the S(n) induced by RRO feedback signals. The top panel of τ Corr(τ) between x(n) and a periodic input signal S(n) on the strength of RRO feedback signals C  in cases of input signal strength α = 0.01, 0.15. In α = 0.15 and relatively long periods, such as p = 16, 32, the high synchronization (arg maxτ Corr(τ) ≈ 0.3, 0.5 in p = 16, 32, respectively) was produced by RRO feedback signals at its appropriate strength C = 0.2. This strength C = 0.2 corresponded to one for slightly weaker strength of attractor-merging bifurcation F + Cu = 0 at C = 0.28 under condition without the external periodic stimulus S(n) (see S(n), the attractor-merging bifurcation appears at its appropriate strength C = 0.2. That is, chaotic resonance was interpreted as being induced by RRO feedback signals and external stimulus S(n)  and Cu(x(n)) on the strength of RRO feedback signals C is shown in the bottom panels of x(n) shown in x(n), x(n) under RRO feedback signals Ku(x) and periodic input signal S(n) corresponding to the case of α = 0.15, p = 32 in C = 0.05), the frequency of CCI was too high; subsequently, CCI did not synchronize to S(n) (correlation coefficient arg maxτ Corr(τ) ≈ 0.23). In contrast, under the appropriate RRO feedback strength C = 0.2, the frequency of CCI was reduced. Using the appropriate CCI frequency, high synchronization was achieved (arg maxτ Corr(τ) ≈ 0.46). Under stronger RRO feedback strength (C = 0.4), CCI did not respond to S(n) (arg maxτ Corr(τ) ≈ 0.06) due to the CCI frequency being too low. In addition, at C = 0.4 under condition without S(n), the CCI does not appear (see K = 0.9 case in S(n) leads CCI, although its frequency is low in C = 0.4 case of We investigated synchronization against external periodic input S(n) see . Here, bK = 0.9, the dependences of arg maxτ Corr(τ) and Θ at different levels of attenuation K = 0.89, 0.91 were evaluated under the same setting for S(n)  shifts to smaller C region. At these attenuation levels, the perturbation Θ to induce peak of arg maxτ Corr(τ) is significantly smaller (Θ ≈ 0.02) than the temporal variation in x(n) shown in In addition to attenuation lues see ; subsequDξ(n) given by Equation (5). Here, RRO feedback strength C is fixed C = 0.2 where arg maxτ Corr(τ) exhibits a peak in τ Corr(τ) and perturbation Θ on noise strength D . The results indicated that arg maxτ Corr(τ) decreased with increasing noise strength D, maintaining Θ ≈ 0.02.When determining the RRO feedback signals estimated from actual frontal neural activity, measurement errors may affect the accuracy of producing RRO feedback signals. Therefore, we evaluated synchronization against external periodic input induced by RRO feedback signals under Gaussian white noise In this study, we developed an efficacious neurofeedback method based on chaotic resonance produced by RRO feedback signals in the Baghdadi model for abnormal neural activity in ADHD with E/I imbalance and impairment of neural pathway from the sensory cortex to the frontal cortex. We confirmed that the effect of chaotic resonance shifted aberrant neural activity caused by abnormal CCI of neural activity to healthy neural activity when the frequency of reference signals was relatively low. Moreover, we evaluated the influence of noise due to measurement errors and observed that the efficiency of chaotic resonance produced by RRO feedback signals was maintained over a certain range of noise strengths.First, we discuss why the synchronization of CCI against the external reference signal is enhanced at attractor-merging bifurcation induced by RRO feedback signals, i.e., why chaotic resonance arises. Near the attractor-merging bifurcation, the frequency of autonomous CCI is low. In this condition, the external signal plays a perturbative role and switches neural activity between positive and negative attractor regions even if its strength is weak. Therefore, the CCI induced by the external signal becomes dominant among all CCIs; subsequently, high CCI synchronization with the external signal is realized. This tendency is congruent with our previous findings on chaotic resonance induced by RRO feedback signals  and RRO feedback signals Cu(n) to the frontal and sensory cortices must be considered. Abnormal neural activity of dopaminergic neural networks in the frontal eye field (FEF) and visual area 4 (V4) are known to cause dysfunction in covert spatial attention and selective attention in ADHD ) where p is an odd number and F corresponds to the map functions for neural activity observed in the experimental condition (Ushio, To reduce abnormal CCI of neural activity, a synchronization mechanism was utilized through chaotic resonance produced by the RRO feedback method in this study. In addition to this approach, alternative methods to stabilize chaotic frontal neural activity should be discussed. Studies on non-linear feedback control theory have proposed various chaos-controlling methods, typified as the Ott–Grebogi–Yorke method (Ott et al., n Ushio, . To deten Ushio, ; generalSeveral limitations of this study should be considered. First, comparison of the results of model-based studies, such as this study, with empirical studies is crucial to validate the proposed method. However, in this study, we used a simple neural system consisting of frontal and sensory cortices. To reproduce the neural activity in ADHD underpinned by complex neural bases, more precise and realistic neural network models are required for comparison and validation. For these evaluations, the use of spiking neural networks to reproduce realistic neural activity (Nobukawa et al., In conclusion, this model-based study demonstrated that chaotic resonance controlled by the RRO feedback method induced the transition of dysfunctional frontal cortical neural activity underscoring attention deficits to approximate intended healthy activity. Although several limitations exist, our proposed neurofeedback method utilizing the mechanism of chaotic resonance produced by RRO feedback signals can be practically applied as a promising treatment option for ADHD.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.SN, NW, HN, and TT conceived the methods. SN analyzed the results, wrote the main manuscript text, and prepared all the figures. SN and HD conducted the experiments. All authors reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Scientific Reports 10.1038/s41598-020-79309-8, published online 17 December 2020Correction to: The original version of this Article contained a repeated error, where the Blackboard Bold 1 symbol did not display correctly in Equations 9, 17, 25, 26, and 33, and in the Results section.In addition, in the Introduction,“Note that if we define now reads:“Note that if we define Finally, in the Results section, under the subheading ‘Polyharmonic fields: exact operations’,“However any other coordinate of the fuzzy centre could suffer a drift now reads:“However any other coordinate of the fuzzy centre could suffer a drift The original Article has been corrected.


The lives of many children and adolescents are today increasingly influenced by new technological devices, including smartphones. The coronavirus disease 2019 (COVID-19) pandemic occurred in a time of outstanding scientific progress and global digitalization. Young people had relevant adverse psychological and behavioral effects due to the COVID-19 pandemic, mainly related to infection control measures, which led them to spend more time at home and with major use of technological tools. The goal this study proposes is to evaluate health and social outcomes of smartphone overuse among Italian children and adolescents during the COVID-19 pandemic, analyzing patterns and aims of utilization, as well as the eventual presence and degree of addiction.This study was based on a self-report and anonymous questionnaire, which was administered to 184 Italian school-age (6–18 years) children and adolescents during the second wave of the COVID-19 pandemic. The test was electronically  explained and sent by pediatricians either directly to older children (middle and high school), or indirectly, through the help of teachers, to younger ones (primary school). All participants spontaneously and voluntarily joined the present study. The survey was made by 4 sections, and designed to know and outline modalities  of smartphone use, adverse outcomes, and related parental behaviors, also in order to reveal the eventual occurrence and degree of addiction. The same information, related to the pre-epidemic period, was also investigated and analyzed.The data obtained revealed a significantly greater adhesion to the questionnaire by females, likely reflecting higher attention and interest than boys to initiatives relating to health education. Our study showed more frequent smartphone use among Italian children and adolescents during the COVID-19 pandemic, compared to the pre-epidemic period. This may be related to the social distancing measures adopted during the months under investigation. The present survey also outlined the changing patterns and aims in the use of smartphones among young people, which allowed to limit some effects of the crisis. Indeed, they were used for human connection, learning and entertainment, providing psychological and social support. Finally, it was observed a significant increase of overuse and addiction. This led to many clinical , psychological  and social  unfavorable outcomes.Pediatricians and health care professionals should be aware of the potential risks related to inappropriate use of smartphones. They should monitor, in cooperation with parents, possible associated adverse effects, in order to early recognize signs and symptoms suggestive, or at high risk, for addiction. They must carry out, as well, the necessary interventions to prevent and/or lower the detrimental impact of smartphone overuse on children and adolescents’ health, oriented to sustain adequate physical and psychological development as well as social relationships. The lives of many children and adolescents are today increasingly influenced by new technological devices and means of communication  . SpecifiCOVID-19, the acute respiratory syndrome related to the new coronavirus (SARS-CoV-2) infection, dramatically spread worldwide from China since the end of 2019. It reached Italy, first among European countries, on February 2020. The following further rapid diffusion to other continents on March 11th 2020, led the World Health Organization (WHO) to declare a pandemic. The study took place over a 2-month period, from December 2020 to January 2021. In that time Italy, within the second wave of the pandemic, was divided into three zones - red, orange, yellow- corresponding to three different scenarios of epidemiologic risk . SpecifiThis study was based on a self-report and anonymous questionnaire, which was administered to Italian school-age (6–18 years) children and adolescents during the second wave of the COVID-19 pandemic. The test was conceived and made by pediatricians of the Mother and Child Department of the University of Palermo . Questions were created in Google Forms. They were electronically  explained in detail, together with the aims of this study, and directly sent to older children (middle and high school), or indirectly, through the help of teachers, to younger ones (primary school). The forms were addressed in Sicily and in regions of northern Italy . Among around three hundred questionnaires homogeneously distributed between males and females of different age groups, a total of 185 students replied and participated in the study. All participants spontaneously and voluntarily joined the present survey. Lack of partial and/or total completion of the questionnaire was the only exclusion criterion. Their answers were recorded on a web-based Google sheet form, and then analyzed.The questionnaire was designed to understand modalities  of smartphone use, its impact (adverse effects) on everyday life, and related parental behaviors among children and adolescents, also in order to reveal the eventual occurrence and degree of addiction, before and during the COVID-19 pandemic. It was made by 4 sections.The first section was about demographic and socioeconomic characteristics, and included the following variables: age, gender, ethnicity, school year, region of residence, family status, parents’ educational level, occupation and income, age at onset of smartphone use.The second section concerned COVID-19 related questions: family members’ jobs linked to the epidemic (specific occupation), family members and/or friends infected by SARS-CoV-2 or dead due to COVID-19, degree of concern about the pandemic, implementation of preventive and infection control measures, eventual distance (online) learning and impact of the pandemic on education.The third section included questions on frequency of smartphone use , and about patterns and effects of their utilization before and during the pandemic, evaluated with the following items: “most frequently used functions”, “aim of use”, “adverse effects” and “parental attitude towards smartphone use”. The most frequently used functions included: “telephone call”, “social network ”, “game”, “education”, “online chat (Whatsapp)”, “photos”, “videos” and “music”. To analyze the aims of smartphone use, we included the following items: “boredom”, “habit”, “pleasure”, “game”, “communication”, “learning”, “stress relief” and “adaptation to others”. The answers on adverse effects included: “superficial approach to learning”, “distraction”, “mood modification”, “loss of interest”, “isolation”, “sleep disturbances”, “ocular alterations” and “musculoskeletal disorders”. Questions on parental attitude regarding smartphone use included the following items: “surveillance”, “restriction”, “punishment”, “permission” and “explanation”. Participants gave to each of these four items a score, ranging from 1 (never) to 5 .The fourth section was related to the evaluation of eventual occurrence and degree of smartphone addiction, measured by the Italian Smartphone Addiction Scale Short Version (SAS-SV) . It is aParticipants expressed their opinion for each item over a 6-point scale, ranging from 1 (strongly disagree) to 6 (strongly agree). A different normal range is identified for males and females. Males are considered addicted if scores are higher than 31. High risk of addiction is present with scores between 22 and 31. Females are addicted if scores are higher than 33, and at high risk with scores between 22 and 33 .p value lower than 0.05 was considered statistically significant.We used R version 4.0.4  for data analysis. Simple descriptive statistics were expressed as frequency and percentage for categorical variables, mean and standard deviation (SD) for continuous variables. Paired-samples t-test was used to compare data on patterns of smartphone use in the study population, before and during the COVID-19 pandemic. A Of the 185 study participants, one was excluded (0.5%) because he did not complete the questionnaire. Thus, 184 school-age children and adolescents were included. Among them, 52 (28.3%) were male and 132 (71.7%) female. Their mean age was 14.84 ± 2.73 years. The sample comprised 39 (21.2%) children aged 6–12 years, and 145 (78.8%) adolescents aged 13–18 years. Ten (5.4%) attended primary school, 48 (26.1%) lower secondary school (middle school) and 126 (68.5%) upper secondary school (high school). All study participants were Italian. They came from 3 different regions: 167 (90.8%) Sicily, 15 (8.1%) Piedmont and 2 (1.1%) Lombardy. 152 (82.6%) belonged to urban areas, and 32 (17.4%) to rural ones. One hundred seventy-two (93.5%) lived with married parents, 12 (6.5%) with only one parent, due to parental separation/divorce (7) or death (5). Seventy-one (38.6%) mothers were graduated, 86 (46.7%) had high school education, 26 (14.2%) lower secondary school, and one (0.5%) primary school. 59 (32.1%) fathers were graduated, 88 (47.8%) had high school education, 36 (19.6%) lower secondary school, and one (0.5%) primary school. One hundred participants (54.3%) belonged to double-income families (employed and independent workers), 84 (45.7%) to single-income ones (unemployed/housewives). All respondents owned a smartphone. The average age at owning smartphone was 10.57 ± 1.8 years (Table Twenty-four 13%) participants reported a work related to the epidemic emergency for their family members, 18 of whom referring health care professions .Seventy-six (41.3%) subjects stated that family members and/or friends were infected with SARS-CoV-2. Four (2.2%) adolescents lost a relative due to COVID-19. A total of 83 (45.1%) respondents reported to be very concerned about the pandemic, and 98 (53.3%) averagely worried. One hundred sixty-eight (87%) participants had strictly implemented preventive and control measures  against the epidemic spread. Furthermore, 132 (71.7%) children and adolescents reported that the COVID-19 pandemic affected their learning. A total of 176 (95.7%) students followed distance learning (Table % particiAverage time per day of smartphone use during the pandemic was higher than before: 122 (66.3%) participants spent more than 4 h per day during the COVID-19 pandemic, while those before the pandemic were 30 (16.3%). Time between wake up and start of use was lower during the pandemic, with 104 (56.5%) subjects reporting their first use within 5 min after wake up, compared to 47 (25.5%) during the pre-epidemic period. Frequency of night utilization during the pandemic was also increased than before: 103 (56%) children and adolescents used smartphone after midnight at least 3 times per week, while those during the pre-epidemic period were 56 (30.4%) ”, “game”, “education”, “online chat (Whatsapp)”, “music” and “videos”. Conversely, for “photos” a statistically significant difference was not observed Table .Table 5The respondents did not show a difference in the aims of use “pleasure” and “adaptation to others”, before and during the COVID-19 pandemic. Conversely, they indicated as aims of use more frequently reported the following ones: “boredom”, “habit”, “game”, “communication”, “learning” and “stress relief” Table .All of the following adverse effects  related to smartphone use were significantly more frequently reported in the study population during the COVID-19 pandemic, compared to the pre-epidemic period: “superficial approach to learning”, “distraction”, “mood modification”, “loss of interest”, “isolation”, “sleep disturbances”, “ocular alterations” and “musculoskeletal disorders” Table .There were no statistically significant differences, during and before the COVID-19 pandemic, for the following parental attitudes: “surveillance”, “restriction”, “punishment” and “explanation”.By converse, a “permissive” attitude was significantly more frequently observed during the pandemic Table .Before the COVID-19 pandemic, among the 184 study participants, 58 (31.5%) were found at high risk of addiction, and in 48 (26.1%) addiction has been documented. During the COVID-19 pandemic, addiction was outlined in 86 (46.7%) participants, while those at high risk were 50 (27.2%)  relating to health education. Furthermore, although distributed to subjects belonging to different Italian regions, a wider participation of Sicilian subjects occurred for reasons likely related to direct knowledge of the pediatricians promoting the study. Despite the limitations of an inhomogeneous representation of the population analyzed (either in gender or age or geographic origin), however, the validity of the results obtained may not be affected, also in light of the overlapping conditions of the different Italian regions, in terms of mortality/morbidity rates due to the COVID-19 pandemic, as well as of economic, social and school settings, during the period under investigation. Our study, indeed, showed that, during the pandemic, children and adolescents significantly increased their average daily smartphone use. This may be explained by the wide and multiple role played by smartphones during the epidemic. This is unsurprising, also considering the potential tasks of smartphones as source of communication, information and entertainment . They, iFinally, parents faced challenging difficulties during the pandemic in the control of their children’s screen time. This was partly likely due to their attempts in finding a complex balance between personal and working life, and family responsibilities . Indeed,Our study showed more frequent smartphone use among Italian children and adolescents during the COVID-19 pandemic, compared to the pre-epidemic period. This may be likely related to the social distancing measures adopted during the months under investigation. The present survey interestingly revealed the changing patterns and aims in the use of smartphones among young people, which allowed to limit some effects of the crisis. Indeed, they were exploited for many purposes such as human connection, learning and entertainment, providing psychological and social support. In the meantime, it was observed a significant increase of overuse and addiction. This led to many unfavorable clinical , psychological  and social  outcomes. Pediatricians and health care professionals should be aware of such potential risks related to inappropriate use of smartphones. They should monitor, in cooperation with parents, possible associated adverse effects, in order to early recognize signs and symptoms suggestive, or at high risk, for addiction –48. They