When it is assembled with the iron oxychloride/lithium electrode system, reversible electrochemical redox reactions of FeOCl/FeO at the cathode side and Li/LiCl at the anode side are realized, demonstrating the first all‐solid‐state rechargeable chloride ion battery.The chloride ion battery has been developed as one of the alternative battery chemistries beyond lithium ion, toward abundant material resources and high energy density. Its application, however, is limited by the dissolution of electrode materials and side reactions in the liquid electrolyte. Herein, a solid polymer electrolyte allowing chloride ion transfer and consisting of poly(ethylene oxide) as the polymer matrix, tributylmethylammonium chloride as the chloride salt, and succinonitrile as the solid plasticizer is reported. The as‐prepared polymer electrolyte shows conductivities of 10 However, the dissolution and shuttle of metal chloride cathodes in this liquid electrolyte led to severe capacity decay of the CIB.2 electrode systems, which showed poor electrochemical properties that were inferior to those of the electrode systems using lithium metal anode, although the magnesium composite anode materials were used.2 at the anode side in the liquid electrolyte, and also the side reactions between magnesium metal and large TFSI− anion of the solvent in the liquid electrolyte,The concept of CIB was first realized by employing the Lewis‐acid metal chloride as cathode, the alkali or alkaline metal as anode, and the binary ionic liquids as electrolyte, in which the chloride ionic liquid was dissolved in the other ionic liquid solvent with the similar organic cation and another anion such as BF2, SrCl2, LaCl3, and LaOCl polycrystalline materials with relatively high electrochemical stability require a high temperature of above 500 K to achieve an ionic conductivity of about 10−6 S cm−1.2‐based materials possess a high ionic conductivity of above 10−5 S cm−1 at room temperature,−4 S cm−1 at room temperature has been obtained for the ternary cubic CsSnCl3 material, as one of the perovskite‐type chlorides.3 as the electrolyte is not possible due to its semiconducting feature.−5 S cm−1 at room temperature,−4 S cm−1 by adding a quaternary ammonium chloride salt.n‐pentylphthalate.One possible solution to dissolve the problems concerning electrode dissolution and side reactions between electrode material and solvent/liquid electrolyte is the use of solid electrolyte, which has been proved to be very effective in lithium ion batteries and metal–sulfur batteries.2Figure1‐TBMACl2). The addition of SN in the binary PEO‐TBMACl system contributes to a further decrease in crystallinity, as indicated by the evidently weakened and broadened diffraction peaks.−1 (PEO1‐TBMACl1), indicating a decrease of the crystallinity, which was reduced continuously with the subsequent introduction of SN. Much lower melting enthalpies of 103.2 and 84.2 J g−1 were obtained for the PEO1‐TBMACl1‐SN1 and PEO1‐TBMACl1‐SN3 SPEs, respectively. Similar variation tendency of the melting point , which was reduced from 72.6 (PEO) to 59.3 °C (PEO1‐TBMACl1‐SN3), was also observed. Figure 1‐TBMACl1). The TBMACl exhibits similar thermal stability of about 180 °C in both the pure sample and the binary PEO1‐TBMACl1 SPE. The pure SN has the lowest thermal stability and it began to lose weight at about 120 °C, which is similar to that in the previous report.Differential scanning calorimetry (DSC) analysis, as shown in Figure Figure1‐TBMACl1‐SN3 samples display similar optical morphology with integrated structure and good flexibility. A much smoother surface was obtained for the PEO1‐TBMACl1‐SN3 SPE film , which has a thickness of about 80 µm , the as‐prepared SPE film lost its structural integrity and many holes were formed in the film . This was caused by volatilization of excess SN in the ternary SPE film during the vacuum drying.m Figure c and a uFigure1‐SN3 mixture exhibits its biphasic nature due to appearance of bands belonging to both TBMACl and SN. However, evident peak shifting was observed. The bands at 2990 and 2952 cm−1, which are related to CH2 stretching vibration of SN,−1 after the addition of TBMACl. The bands corresponding to CH2 twsiting and rocking vibrations show a similar shifting. Meanwhile, a loss of electrons for the —C≡N occurs,−1. The bands of C—CN stretching at 967 and 922 cm−1 also shift to lower wavenumbers. This may be ascribed to the solvation of TBMACl by SN through the interactions of —C≡N/quaternary ammonium cation (TBMA+) and −CH2/chloride ion, which are beneficial to dissociate the TBMACl. Similar solvation process has been reported in the mixtures of tetramethylammonium chloride/acetonitrile (ACN) and tetrabutylammonium chloide/acetonitrile.−1 related to CH3 symmetric streching vibration moves to a higher wavenumber for 8 cm−1,−1 shifts to a higher wavenumber of 13 cm−1.2 stretching vibration at 2960 and 1471 cm−1 shift to lower wavenumbers for about 4 cm−1.3 at 1471 cm−1 moves to a higher wavenumber for 22 cm−1 with a drastic decrease in peak intensity. The C—C—C symmetric streching peak at 800 cm−1 appears at a lower wavenumber of 792 cm−1 in the binary SPE film.2 and CH3 rocking vibration at 889 cm−1 disappearred,−1 were formed in the binary SPE film, in which the width of the band ascribed to the C—O—C stretching tripliet of PEO at 1046, 1095, and 1060 cm−1 was decreased,−1 showed a sharp reduced intensity. The intensity of the CH2 symmetric rocking peak of PEO at 945 cm−1 was also weakened.−1 of the CH2 stretching of PEO was narrowed.2 of SN and the oxygen of the PEO,2 of SN. The ternay PEO‐TBMACl‐SN SPE film shows a similar FTIR pattern with the binary PEO‐TBMACl SPE film. However, several changes can be noted. A futher decrease of the width of the CH2 stretching peak at 2840–2925 cm−1 was observed. The C—O—C stretching peak at around 1100 cm−1 and the CH2 twisting peak at 1279 cm−1 were further weakened. The cyanide peak of SN at 2257 cm−1 was significanly reduced, associated with a further red‐shift to 2248 cm−1. Accordingly, both TBMACl and SN are well coordinated in the PEO matrix. The solvation interactions between the TBMA+ cation and unshared electron pairs of the —C≡N in SN and the ether group in PEO dissociate the TBMA+‐Cl− ion pairs and decrease the crystallinity of the ternary SPE. Furthermore, the CH2 of SN prefers to coordinate with the ether group in PEO, which not only further reduces the crystallinity of PEO, but also induces the decrease of the interaction between chloride ion and the CH2 of SN. As a result, the chloride ions interact weakly with their environment, and high chloride ion mobility between the PEO chains with enhanced free volume by the above interactions is anticipated. In contrast, the migration of the large TBMA+ cation along and between PEO chains is constrained by its significant interaction with the polymer chains.Fourier transform infrared spectroscopy (FTIR) was carried out to further elucidate the interaction of the PEO, TBMACl, and SN components in the SPE films, as shown in R and a constant phase element CPE1, in series with the CPE2 (the straight lines), fits the measured spectra well. The ionic conductivity σ values of the electrolytes can be calculated by using the equation of σ = L/(S × R), where L is the membrane thickness and S is the effective electrode area, as listed in Table S4 in the Supporting Information. For all the binary and ternary samples, the ionic conductivity increases linearly with the temperature. The temperature dependence of the electrolytes can be described by an Arrhenius‐like behavior. Figure5‐TBMACl1 SPE shows a very low concuctivity of 1.7 × 10−8 S cm−1 at 298 K. The conductivity of this binary SPE system increases with the increase of the TBMACl concentration, which provides more charge carriers for transport. Meanwhile, the crystallinity of the PEO‐TBMACl decreases, as indicated by the evident decrease of the melting enthalpy from 174.0 (PEO) to 134.4 J g−1 (PEO1‐TBMACl1) derived from the DSC result, facilitating the ion transport. The conductivity reaches a maximum value of 3.1 × 10−7 S cm−1 at 50% TBMACl (PEO1‐TBMACl1), that is, ≈20 times the value of the PEO5‐TBMACl1 SPE, followed by a decrease with further increase of the TBMACl content (PEO1‐TBMACl2). This decrease is ascribed to the “inactive” pure TBMACl that segregated from the PEO matrix, as shown in the XRD pattern  blocking electrodes at different temperatures. Figure S2 in the Supporting Information shows the Nyquist plots of the binary PEO‐TBMACl and ternary PEO‐TBMACl‐SN SPEs at various temperatures. The spectra are composed of a depressed semicircle at high frequencies due to ion conduction and a straight line at low frequencies due to electrode polarization. The typical equivalent circuit consisting of a parallel R‐CPE circuit (the semicircles) with the bulk resistance 1‐TBMACl1 SPE, there was a mild increase of the ionic conductivity from 3.1 × 10−7 (PEO1‐TBMACl1) to 6.7 × 10−7 S cm−1 (PEO1‐TBMACl1‐SN1), although a large melting enthalpy change from 134.4 to 103.2 J g−1 was obtained. This may indicate that the SN at low concentration in the ternary SPE plays a dominant role in the decrease in crystallinity , instead of the dissociation of TBMACl. When a high concentration of SN was added (PEO1‐TBMACl1‐SN3), a remarkable enhancement of the ionic conductivity to 1.2 × 10−5 S cm−1, which is about 40 times of 3.1 × 10−7 (PEO1‐TBMACl1), together with a medium variation of the melting enthalpy from 103.2 to 84.2 J g−1, is received. This conductivity enhancement mainly comes from the further effective dissociation of TBMACl by SN, associated with an increase of the amorphous fraction, promoting the ion transport in the SPE.With the addition of SN at low concentration in the binary PEO1‐TBMACl1‐SN3 SPE was obtained.The further increase of the SN content in the ternary SPE led to the formation of inactive SN, which would be volatilized during the vacuum drying and consequently brought about the formation of inhomogeneous film . The activation energies calculated from the Arrhenius plots in the temperature range from 298 to 333 K are also marked in Figure 1‐TBMACl1‐SN3 SPE using the SS/SS and SS/Li electrode couples, as shown in Figure 1‐TBMACl1‐SN3 SPE shows the anodic and cathodic potentials of 2.31 and −1.94 V (vs SS), respectively, i.e., an electrochemical window of 4.25 V at 298 K. The anodic stability of the as‐prepared PEO1‐TBMACl1‐SN3 SPE has also been evaluated in a SS/PEO1‐TBMACl1‐SN3/Li cell. A high value of 4.24 V relative to lithium metal was obtained at 298 K. This means that the cut‐off voltage for the charging process of CIBs with lithium metal as anode could be set at 4.24 V, which provides a stable environment for the electrochemical reactions in metal chlorides/metal, metal oxychlorides/metal, and chloride ion–doped conducting polymer/metal electrode systems that have been proposed for CIBs. Moreover, this value is higher than those of the liquid electrolytes such as the binary ionic liquids (4.0 V) and the mixture of chloride ionic liquid/propylene carbonate (3.2 V),1‐TBMACl1‐SN3 SPE. The electrochemical stability is almost unchanged with the increase of the temperature to 323 K .Besides the ionic conductivity, the electrochemical window (EW) is also a determining factor for achieving high performance CIBs. The linear sweep voltammetry (LSV) was measured for the as‐prepared PEO1‐TBMACl1 or ternary PEO1‐TBMACl1‐SN3 film as the electrolyte, which was sandwiched between the FeOCl cathode and the lithium metal anode. Figure1‐TBMACl1 SPE shows a very low initial discharge capacity, which is calculated based on the active material of FeOCl cathode, of 18 mAh g−1, which can be increased to more than 40 mAh g−1 at the elevated temperatures. However, a large voltage gap between discharge and charge of about 1.25 V still exists. When the ternary PEO1‐TBMACl1‐SN3 SPE is used, a much higher discharge capacity of 73 mAh g−1 is obtained at 298 K. A further enhancement in discharge capacity (87 mAh g−1), as well as the reversiblity of discharge and charge, is received as the operating temperature increases to 313 K  measurement was performed . The EIS curves exhibit a semicircle at high frequency followed by a further semicircle and a straight line at low frequency, indicating a mixed rate‐determining electrochemical process containing charge transfer and ion diffusion. The former semicircle is related to the interface resistance, the latter semicircle is considered to be the charge transfer resistance, and the straight line is associated with the Warburg impedance by ion diffusion. The measured EIS plots can be fitted well using the equivalent circuit in Figure S5b in the Supporting Information. It is clear that both the interface resistance and charge transfer resistance, as well as the Warburg impedance, are significantly reduced using the ternary PEO1‐TBMACl1‐SN3 SPE, indicating its superior electrochemical properties.To further understand the reasons for the better battery performance by using the ternary PEO1‐TBMACl1‐SN3 SPE, microstructural characterizations were carried out. FigureN‐methyl‐2‐pyrrolidinone (NMP),b‐axis direction was greatly expanded before cycling. Our previous theoretical and experimental results suggested that both organic molecule (NMP or acetonitrile) and ionic compound in the electrolyte (1‐butyl‐1‐methylpiperidinium chloride) could be readily intercalated into the FeOCl interlayer at room temperature.1‐TBMACl1‐SN3 SPE in the FeOCl interlayers was investigated through the immersion test in the acetonitrile solutions  of FeOCl. The following charge to 4.2 V did not change the peak position, but increased the peak intensity, accompanied by the peak broadening. A weak peak at 11.2° was also observed. This indicates a recovery of the FeOCl species with a reduced grain size. The energy‐dispersive spectroscopy (EDS) analysis for the FeOCl cathodes washed with ACN in Figure S7 in the Supporting Information demonstrated the decrease and recovery of the chlorine content during discharge and the subsequent charge, respectively. This suggests the chloride ion transfer occurs at the FeOCl cathode side during cycling. The transmission electron microscopy (TEM) analysis was implemented to gain an insight into the phase transformation of the FeOCl cathode in the first cycle. Figure3O4 phases with poor crystallinity are formed, as reflected by the characteristic lattice planes of (111), (200), and (220) for FeO (PDF card no. 6‐615), and (220), (311), (400), and (422) for Fe3O4 (PDF card no. 75‐1372). The HRTEM and the corresponding fast Fourier transform (FFT) results , it is clear that the iron species exist only at the cathode side and the lithium species are found only at the anode side regardless of the different electrochemical states, suggesting the high stability between the electrodes and the SPE, and the cation transfer is not included in the battery. More detailed and definite information is provided in the XPS region spectra  and 725.1 eV (Fe 2p1/2), and Cl 2p peaks at 198.8 (Cl 2p3/2) and 200.4 eV (Cl 2p1/2). Those values are identical to the binding energies (BEs) of the Fe 2p and Cl 2p of the as‐prepared FeOCl powders , indicating that the phase structure of the FeOCl was not changed by the abovementioned chemical intercalations. Upon discharge, new Fe 2p peak doublet located at lower binding energies of 709.8 and 723.5 eV was found and can be assigned to Fe2+ species (FeO), which confirms the TEM result. In the following charge, the Fe 2p signals belonging to the FeOCl phase were recovered. The corresponding chlorine content in the FeOCl cathode decreased after discharge and then increased by the recharge . These observations support the above reaction mechanism proposed for the FeOCl cathode. For the region spectra of the PEO1‐TBMACl1‐SN3 SPE  and 199.5 eV (Cl 2p1/2), occurred, providing the proof for the formation of lithium chloride. This discharge product was reduced to the pristine lithium state, as indicated by the return of the Li 1s peak. The EDS analysis for all the components in the all‐solid‐state battery, as shown in Figures S10–S12 in the Supporting Information, was also investigated, and the results showed that the chlorine element appeared at the Li anode side after discharge and disappeared upon the following charge. Furthermore, the iron element exists only at the cathode side. As demonstrated by the above observations and analysis, we propose the chloride ion transfer reaction mechanism for the FeOCl/ PEO1‐TBMACl1‐SN3/Li all‐solid‐state battery, namely, the all‐solid‐state rechargeable chloride ion battery, in which redox reactions of FeOCl/FeO and Li/LiCl occurred at the cathode and anode, respectively. The as‐prepared SPE balances the battery reactions by allowing the chloride ion shuttle between the cathode and anode, as illustrated in FigureAlthough chloride ion transfer is involved in both the FeOCl cathode and the SPE, lithium ion transfer in the all‐solid‐battery is not precluded as the lithium metal was used as the anode, in which the electrochemical reaction mechanism also needs to be clarified. Therefore, further investigation was performed. 3−5–10−4 S cm−1 in the temperature range of 298–343 K and a high electrochemical stability with the anodic potential of more than 4.2 V versus Li. The chemical interactions, as confirmed by XRD, DSC, and FTIR characterizations, among components of the SPE contributed to the dissociation of the chloride salt and thus bring about the notable increase of the conductivity, resulting in the evident increase of the reversible capacity of the ASS‐RCIB. The electrochemical reaction mechanism of the ASS‐RCIB using the SPE is based on the chloride ion shuttle via the redox reactions of FeOCl/FeO at the cathode side and Li/LiCl at the anode side, as validated by XRD, TEM, XPS and electrochemical measurements.In summary, we developed the first all‐solid‐state rechargeable chloride ion battery by employing a ternary solid polymer electrolyte, which is composed of a PEO polymer matrix, a quaternary ammonium chloride salt, and a solid SN plasticizer. The as‐prepared SPE shows conductivities of 104−1, SN (99%), anhydrous acetonitrile (99.8% and packaged under argon), and anhydrous NMP (99.5% and packaged under argon) were purchased from Alfa Aesar. TBMACl (99%) was obtained from Lanzhou Institute of Chemical Physics. PEO and TBMACl were vacuum dried at 313 and 353 K for 48 h before use, respectively. The SPE films were prepared by a solution casting method. For the binary PEO‐TBMACl series, the PEO and TBMACl with a mass ratio range from 5:1 to 1:2 were used. The optimized PEO‐TBMACl composition with a mass ratio of 1:1 was selected to prepare the ternary PEO‐TBMACl‐SN series. The PEO and TBMACl were dissolved in ACN, followed by the addition of different amounts of SN. The mixture was stirred for 48 h at 450 rpm to obtain a homogeneous viscous solution, which was casted onto Teflon plate and allowed to evaporate the ACN solvent in a nitrogen‐filled box for 48 h. Afterward, the samples were dried under vacuum at 323 K for 48 h and stored in an argon‐filled glove box. The schematic illustration for preparation of the SPE films is shown in Scheme S1 in the Supporting Information. The synthesis of the FeOCl cathode material was performed by a thermal decomposition of FeCl3·6H2O at 493 K for 1 h. Then, the product was thoroughly washed with acetone, followed by an overnight drying under vacuum at 333 K.PEO with an average molecular weight of 300 000 g mol−1 under a nitrogen atmosphere using the NETZSCH STA449F1instrument. FTIR spectra over the range of 400–4000 cm−1 were received using a Thermo Nicolet Nexus 670 FT‐IR spectrometer. XPS was recorded by an AXIS Ultra DLD spectrometer with Al Kα excitation. The C 1s line with a BE of 284.8 eV was used as a standard.Powder XRD patterns were collected on a Rigaku SmartLab diffractometer using Cu Kα radiation. SEM/EDS (Ultra55) and TEM/EDS results were obtained on the Field‐emission Ultra55 and Tecnai G2 F20 U‐TWIN microscopes, respectively. The samples were washed with anhydrous NMP and ACN to remove the poly(vinylidene difluoride) (PVDF) and the SPE in the glove box before the TEM test. DSC and TGA thermograms were acquired at a ramp rate of 10 °C min−1 using the SS/SS and SS/Li electrode couples at different temperatures on the Bio‐Logic (VMP3) electrochemical workstation, which was also employed to collect the EIS (100 kHz to 1 Hz) data of the SPEs in the Swagelok cells containing two polished SS blocking electrodes in the temperature range of 298–343 K. The battery testing was performed using the FeOCl cathode, SPE, and lithium metal (China energy lithium Co. Ltd.) anode in coin cells. The FeOCl cathode was fabricated by mixing the as‐prepared FeOCl powders, PVDF, and carbon black in the mass ratio of 60:10:30 and a subsequent slurry coating with graphite foil  as the current collector. Discharge and charge testing was implemented galvanostatically at 10 mA g−1 over a voltage range between 1.6 and 4.2 V by using Neware battery testing system (Neware Co. Ltd.) at 298, 313, or 323 K. The specific capacities were calculated according to the mass of the as‐prepared FeOCl powders in the electrodes. EIS (100 kHz to 10 mHz) data and CV  of the batteries using the FeOCl working electrode were all collected under a Bio‐Logic (VMP3) electrochemical workstation.LSV testing for the SPEs in the coin cells was carried out at the scan of 5 mV sThe authors declare no conflict of interest.SupplementaryClick here for additional data file.


The catalytic activity of nanotubular titanium dioxide films formed during the oxidation of acetone to carbon dioxide under the action of visible light with a wavelength of 450 nm was found to be approximately 2 times higher compared to standard titanium dioxide (Degussa P25). The nanotubular films were grown by the anodization of titanium foil using an original technique. Diffuse reflectance spectra of the films are attributed to enhanced activity in the visible spectrum by the nonstoichiometry of titanium dioxide near the interface between the nanotubular film and the titanium foil substrate. The optical gap width of stoichiometric TiO2 (>3.1 eV) determines its photocatalytic activity under the action of near -UV radiation, which constitutes only a small percent of the solar spectrum13. To shift the spectral response to the visible region and enhance the catalytic activity, it is reasonable to decrease the optical gap width of the material, in particular, from the generation of structural vacancies in the oxygen sublattice14.Nanostructural modifications of titanium dioxide are of great research interest, particularly in the development of promising functional media for renewable energy sources 16 or by sonoelectrochemical method17. In this case, deficiencies in oxygen can appear in the vicinity of the nonstoichiometric contact between titanium dioxide and titanium. Some indications of this phenomenon are apparent in the results of the photocatalytic activity of nanotubular films. Indeed, an enhancement of activity by 18% in comparison to Degussa P25 under the action of UV light was registered17. In16, a much higher activity level of nanotubes on Ti foil compared to than on Degussa P25 was also observed under visible light.The most promising possibility for generating oxygen vacancies in titanium dioxide is the growth of nanofilms from titanium foil, as has been achieved previously2.Therefore, the aim of the present work is to consider the growth of the nanotubular titanium dioxide film with nonstoichiometry near the interface with titanium foil in detail, and to study the photocatalytic activity of such films under visible light by a reliable technique – the oxidation of acetone to COFigures 18, the effective surface Seff and roughness factor H are described by equations  length, w is the thickness of the NT wall, Din is the inner diameter of the NT, and y denotes the voids between nanotubes.According toquations 1\documenSF of the nanotubular film was calculated using equation , an effective surface for the grown array of nanotubes reaches a maximum (Seff = 415 cm2) at this anodization time, and a maximum length of the nanotubes of about L = 2 μm was also achieved. According to equitation (3), the solid fraction SF of nanotubes at an anodization time of 120 min reaches a maximum value approximately 0.41.The solid fraction equation , as give2 layers with maximum values of the L and Seff parameters under the conditions indicated above is 120 min, which is necessary for enhancing catalytic activity.Therefore, an optimal anodization time to grow ordered nanotubular TiOθ angles (from 18 to 33°), the intensity of the signal increased, which manifests as a diffuse halo with a maximum marked by an arrow. In addition, Fig. 21.Figure 2 layer and the Degussa P25 TiO2 nanopowder. In the visible spectrum at approximately 450 nm, there is a broad reduction in diffuse reflection, which is related to the nonstoichiometry of amorphous titanium dioxide. The presence of nonstoichiometry is supported by thermodynamic calculations and experimental studies using energy dispersive X-ray spectroscopy19. Atomic defects represented by vacancies in the amorphous network lead to the formation of energy levels in the band gap of titanium dioxide, which in its turn results in the absorption of visible light with a wavelength near 450 nm, shown by an arrow in Fig. Figure 2 layer that was anodized for 120 min allowed us to determine the optical gap width by the following technique. It was assumed that the relationship between the band gap width of a semiconductor Eg and the optical absorption coefficient α has a Tauc function form23, as given by equation  is proportional to the coefficient λ25. In this situation, equation  and the Degussa P25 TiO2 nanopowder (bottom). The extrapolation with a linear function to zero absorption in the region of high photon energies shows that the maximum band gap width for a nanotubular TiO2 layer anodized for 120 min is Eg = 3.3 eV, while Eg = 3.0 eV for the Degussa P25 TiO2 nanopowder. An analysis of the Kubelka-Munk function in the region of low photon energies using a procedure reported in26 revealed that the nanotubular layer contains not only a titanium dioxide phase with a wide band gap, but also the nonstoichiometric phases have an essentially narrower optical gap width, which results in the absorption of visible light, in particular with the wavelength of 450 nm  to direct one (amorphous titanium dioxide).2 films prepared by anodization under similar conditions for 120 min. The length of the nanotubes synthesized by this method within this time vary from 1.4 to 2 μm, and are on average 1.7 μm; however, all nanotubular layers have a similar morphology. The typical morphology is shown on Fig. The Table m) of nanotubes linearly depends on their length (L) according to the formula given by equation  in comparison to standard P25 TiO2 (55 ± 5 m2/g).The average catalytic activity measured for titanium dioxide nanotubes is approximately 4.2 ± 0.8 μmol/(min·g), which is more than 2 times higher compared to standard titanium dioxide (Degussa P25) (see Table 2(NO3)2/TiO2) are more active for oxidizing acetone, and (Au@Ag)@Au/TiO2 and Au@Ag/TiO2 are more active for oxidizing a 2-propanol substrate  is approximately 2.8 eV. It is observed that more efficient absorption of visible light owing to an oxygen vacancy, leads to a pronounced enhancement of activity and the optical gap width decreases.A scheme that considers the expected band diagram of photooxidation is shown on Fig. 2p core-level spectrum of the surface of the film is presented on Fig. 2p3/2 -Ti2p1/2, corresponding to Ti in the different oxidation forms. The intense doublet Ti2p3/2- Ti2p1/2 with a Ti2p3/2 peak binding energy at 459.0 eV corresponds to Ti4+ in the structure of TiO2. The second doublet Ti2p3/2 -Ti2p1/2 with a Ti2p3/2 peak binding energy at 457.1 eV corresponds to Ti3+ in the defective structure of nonstoichiometric TiO2−x. The low intense doublet Ti2p3/2 -Ti2p1/2 with a Ti2p3/2 peak binding energy at 453.6 eV corresponds to Ti° in the structure of titanium foil substrate. In the literature, the values of binding energy of Ti2p3/2 in TiO2 are given in range of 458.7–459.2 eV, while the Ti3+ is in the range of 456.2–457.4 eV30. Therefore, XPS spectra of the films allow us to identify that the oxygen deficiency and the presence of Ti3+ contribute to nonstoichiometry in the titanium dioxide nanotubes31.A TiIn the present work, the nanotubular films with a nonstoichiometric layer in the vicinity of titanium foil were grown by the anodization of titanium foil using an original technique. The highest activity of approximately 4.2 ± 0.8 μmol/(min·g), which is nearly twofold greater compared to standard titanium dioxide (Degussa P25), was observed for nanotubular films prepared by anodization for a period of 120 min. Such a pronounced enhancement of activity may be attributed to a more efficient absorption of visible light by the films due to narrowing of the optical gap because of difference in the nonstoichiometry of titanium dioxide near the interface between nanotubular film and the titanium foil substrate. Oxygen deficiency in the titanium dioxide nanotubes are proven by XPS measurements.6. Anodic oxidation was carried out using a substrate made of 100 μm thick titanium foil. The surface of the titanium foil was preliminarily treated with acetone and an aqueous solution of acids mixed in a volumetric ratio of HNO3:HF:H2O = 6:1:18, and was then washed with distilled water. Primary anodization was performed in a 1% solution of hydrofluoric acid in ethylene glycol for 10 min at a temperature of 20 °C. This anodization was followed by etching of the titanium substrate in a solution of acids (HNO3:HF:H2O = 1:1:20) for 3 min, washing in distilled water and acetone, and finally drying at room temperature. Secondary anodization was carried out potentiostatically at a voltage of 20 V and anodization times of tA = 15, 30, 60, 120, 180 or 360 min. A solution of ethylene glycol and ammonium fluoride with a concentration equal to 1 wt. % was employed as the electrolyte. All the chemical reagents used in the study were of analytical grade. The area of primary and secondary anodization for every sample was approximately 3.8 cm2.Nanotubular titanium dioxide films were synthesized on a Digma setup consisting of an electrochemical cell, thermostat and power supplyKα1,2 radiation on a Shimadzu XRD-7000 (Japan) diffractometer with the Bragg-Brentano recording geometry. XRD patterns were measured using the step-scan mode at Δ(2θ) = 0.02° in the 2θ angular range from 10 to 100° with a long exposure time at each step. The surface and side views of the synthesized samples were examined on a SIGMA VP (Carl Zeiss) scanning electron microscope (SEM) under high vacuum using an InLens detector. The obtained SEM images were processed with Clinker C7 software (SIAMS).XRD analysis of the films and substrate was performed using CuDRS measurements of the films and standard were recorded on a Lambda 35  UV-VIS spectrophotometer with a RSA-PE-20 (Labsphere) diffuse reflectance attachment.hν = 1486.74 eV) and a fixed analyser pass energy of 20 eV under ultra-high-vacuum conditions. The charge correction was performed by setting the Ti2p3/2 peak at 459.0 eV, corresponding to titanium in TiO2. For detailed analysis, the spectra were fitted into several peaks after background subtraction using the Shirley method. The fitting procedure was performed using CasaXPS software. The line shapes were approximated by the product of Gaussian and Lorentz functions.The XPS measurements were performed on a photoelectron spectrometer  equipped with a PHOIBOS-150 hemispherical electron energy analyzer, a FOCUS-500 X-ray monochromator, and a XR-50 M X-ray source with a double Al/Ag anode. The core-level spectra were obtained using monochromatic Al Kα radiation (S = 9 cm2) from aqueous suspensions, so that the surface density was 1 mg/cm2. The study was performed using a light-emitting diode with a maximum wavelength of 450 nm. The other reaction condition were as follows: T = 40 °C, relative humidity of 20%, an acetone concentration of 800 ppm, and a flow rate of 60 mL/min. Oxidation was performed using the oxygen in air.Photocatalytic activity of the films and the standard was measured in a flow reactor, and reactants were identified using an FTIR spectrometer. Standards – (titanium dioxide Degussa P25 and Kronos vlp7000) were uniformly deposited on a square glass slides (−1, and the concentration of carbon dioxide was found by integrating the area of the absorption band at 2200–2450 cm−1. The rate of photocatalytic oxidation was calculated from the accumulation of carbon dioxide, which was a sole product of the reaction:The concentration of acetone was found by integrating the area of the absorption band at 1160–1265 cm2 is the sole product of acetone photooxidation, the rate of acetone decomposition was one third of the rate of carbon dioxide formation rate.As CO


CTRP5/C1QTNF5 gene. To understand the mechanism underlying L‐ORD pathology, we used a human cDNA library yeast two‐hybrid screen to identify interacting partners of CTRP5. Additionally, we analyzed the Bruch's membrane/choroid (BM‐Ch) from wild‐type (Wt), heterozygous S163R Ctrp5 mutation knock‐in (S163R/wtCtrp5), and homozygous knock‐in S163R/S163R(Ctrp5) mice using mass spectrometry. Both approaches showed an association between CTRP5 and HTRA1 via its C‐terminal PDZ‐binding motif, stimulation of the HTRA1 protease activity by CTRP5, and CTRP5 serving as an HTRA1 substrate. The S163R‐CTRP5 protein also binds to HTRA1 but is resistant to HTRA1‐mediated cleavage. Immunohistochemistry and proteomic analysis showed significant accumulation of CTRP5 and HTRA1 in BM‐Ch of S163R/S163RCtrp5 and S163R/wtCtrp5 mice compared with Wt. Additional extracellular matrix (ECM) components that are HTRA1 substrates also accumulated in these mice. These results implicate HTRA1 and its interaction with CTRP5 in L‐ORD pathology.Late‐onset retinal degeneration (L‐ORD) is an autosomal dominant macular degeneration characterized by the formation of sub‐retinal pigment epithelium (RPE) deposits and neuroretinal atrophy. L‐ORD results from mutations in the C1q‐tumor necrosis factor‐5 protein (CTRP5), encoded by the  Clinically, it is characterized by the onset of sub‐retinal drusen‐like deposits and abnormal dark adaptation from the 5th decade of life, and chorioretinal atrophy and choroidal neovascularization in the 6th decade, progressing to significant vision loss  that is encoded by another retinal disease‐causing gene  screen to identify CTRP5‐interaction partners and a proteomic approach to identify altered proteins in the Bruch's membrane/choroid (BM‐Ch) tissue involved in disease pathology. Mice with homozygous or heterozygous S163R CTRP5 mutations served as models to study the disease pathology.22.1BD‐CTRP5 construct was used in Y2H screening against a universal, normalized human cDNA library (TaKaRa). A total of 56 positive clones were isolated from 4 × 106 yeast transformants with a mating efficiency of 13%. After distinguishing genuine positive clones and eliminating duplicates, our high‐stringency plating conditions resulted in the identification of high temperature requirement A serine peptidase 1 (HTRA1) as one of the potential binding partners of CTRP5 , and Zonula Occludens‐1 (ZO‐1)] protein domain  using cell lysates of ARPE19 cells overexpressing WT‐CTRP5‐V5 or S163R‐CTRP5‐V5 fusion proteins. We observed that HTRA1 co‐immunoprecipitated with both WT‐CTRP5‐V5 and S163R‐CTRP5‐V5  aa 1–238) . Higher concentrations of WT‐CTRP5  resulted in a linear increase in DQ elastin degradation .To understand the potential impact of the interaction of CTRP5 with HTRA1, the protease activity of HTRA1 was tested in the presence of full‐length CTRP5. We performed an in vitro elastase degradation assay using DQ elastin, quenched by BODIPY‐FL dye, as a substrate to measure the activity of proteolytically active, recombinant HTRA1. While addition of BSA as a control had no effect on DQ elastin degradation, the presence of WT‐CTRP5 significantly increased the degradation of DQ elastin . Preincubation with WT‐CTRP5 activated HTRA1 to almost similar levels as WT‐CTRP5 or S163R‐CTRP5 added to the reaction mixture without preincubation  and was half the protease activity compared with the that measured without preincubation.Previous observations indicated that co‐expression of WT‐CTRP5 with S163R‐CTRP5 enhanced the formation of sub‐RPE deposits in mice . Moreover, the activity of HTRA1 preincubated with the 1:1 mixture of WT‐CTRP5 and S163R‐CTRP5 was similar to the level of HTRA1 activity observed when preincubated with S163R‐CTRP5 alone   . The laTaken together, these results establish that WT‐CTRP5, but not S163R‐CTRP5, is a substrate of HTRA1 and undergoes cleavage by HTRA1. The resistance of S163R‐CTRP5 to cleavage by HTRA1, together with its previously demonstrated tendency to aggregate, could explain the formation of thick deposits at the basal RPE   , respectively. Both models developed basal deposits associated with BM.The formation of basal deposits associated with the BM is one of the key pathological features of both L‐ORD and AMD  intensities for the proteins in each genotype were averaged. Levels of CTRP5 were 10‐fold higher in the BM‐Ch of S163R/wtCtrp5 mice than those in Wt mice as early as 5 months and increased to 12‐fold in 18‐month‐old mice . By comparing LFQ peptide intensities, it was determined that the intensity of this peptide in heterozygous BM‐Ch samples was approximately 40% of that found in wild‐type BM‐Ch samples. However, this peptide was not observed in es Table . The subS163R/wtCtrp5 and S163R/S163RCtrp5 models  showed that the levels of Ctrp5 mRNA in S163R/wtCtrp5 mice were 2‐fold higher when compared to its expression in Wt mice  in the expression of Htra1 when compared to that of Wt mice . However, the levels of CTRP5 detected by immunoblot analysis were similar in the posterior eyecup lysates of both S163R/wtCtrp5 and S163R/S163RCtrp5 mice aged 3–6 months, and higher compared to the levels observed in age‐matched Wt mice .  due to mutations in EGF containing fibulin extracellular matrix protein 1 (EFEMP1) and Sorsby fundus dystrophy (SFD) due to mutations in tissue inhibitor of metalloproteinase‐3 (TIMP3), in addition to the common condition AMD (Fu et al., Formation of high molecular weight protein aggregates has been suggested as the underlying cause of several neurodegenerative diseases including retinal degenerations (Dawson & Dawson, .Our data from the proteolytic cleavage and Y2H assays demonstrate that WT‐CTRP5 is a substrate for HTRA1. However, the resistance of S163R‐CTRP5 to HTRA1 cleavage Figure a likely Wt mice. The accumulation of HTRA1 substrates clusterin, vitronectin, C3, ADAM9, and tubulin detected in L‐ORD mouse models may indicate the lack of normal levels of HTRA1 activity and/or abnormal turnover of ECM proteins (Figure ECM proteins such as Col3a1‐C are known to interact with HTRA1 through their PDZ‐ligands and enhance HTRA1 activity in vitro (Murwantoko et al., s Figure . Aberrans Figure , 2016. SCtrp5 gene is not only correlated with the accumulation of HTRA1, but also additionally with the elevated expression of the Htra1 gene in L‐ORD mouse models (Figure Htra1 expression similar to that observed in the L‐ORD mouse models.The S163R mutation in the HTRA1, which is identified as a major risk allele for AMD, results in elevated HTRA1 expression (DeWan et al., Elevated HTRA1 expression is associated with AMD, arthritis, Alzheimer's disease, and Duchenne muscular dystrophy (Bakay, Zhao, Chen, & Hoffman, In summary, our results suggest a complex interplay between HTRA1 and CTRP5 and point to a dual role of CTRP5 as an allosteric activator and a substrate for HTRA1. The present study shows that HTRA1/CTRP5 interaction has a physiological function and CTRP5, as an HTRA1 activator, may be involved in HTRA1‐dependent ECM remodeling. HTRA1 has been previously reported to cleave a wide variety of proteins which are involved in formation of sub‐retinal deposits and thereby functions in remodeling ECM within the sub‐retinal space. In this context, HTRA1 by its enzymatic activity may have the ability to influence protein turnover in the extracellular milieu of RPE cells. The drusen phenotype and the findings in the L‐ORD mouse models point to the dysfunction of ECM homeostasis as a central feature in the development of disease pathology. RPE plays a predominant role in age‐related changes in BM by formation of basal deposits either directly by altering expression and secretion of ECM proteins or indirectly by regulation of protein turnover in ECM (Bergen et al., 4Detailed description of materials and methods used in the study was included in the Appendix None declared.involved in in silico structure modeling. SB: involved in data interpretation and manuscript writing. CS, CH: provided CTRP5 plasmids, interpreted the data, and wrote the manuscript. PS: provided HTRA1 plasmid and interpreted the data. RA, SS: designed, supervised the study, interpreted the data, prepared the manuscript, and acquired funding. RA: developed the concept of the study.AC and KZR: designed and performed the majority of experiments and prepared the manuscript. AC: coordinated the study with collaborators, maintained mouse models, provided tissue samples for analysis, and prepared purified proteins. DG: performed proteome analysis and analyzed data. ASH, VK, MV, PB; performed experiments. AC, SB, DG:  Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Owing to the slow Cu2+ diffusion through the base pairing sites in the S‐DNA electrolyte, the synaptic operation of the S‐DNA device features special long‐term plasticity with negative and positive nonlinearity values for potentiation and depression (αp and αd), respectively, which consequently improves the learning/recognition efficiency of S‐DNA‐based neural networks. Furthermore, the representative neuronal operation, “integrate‐and‐fire,” is successfully emulated in this device by adjusting the duration time of the input voltage stimulus. In particular, by applying a Cu2+ doping technique to the S‐DNA neuromorphic device, the characteristics for synaptic weight updating are enhanced  and also the threshold conditions for neuronal firing (amplitude and number of stimulus pulses) are modulated. The improved synaptic characteristics consequently increase the Modified National Institute of Standards and Technology (MNIST) pattern recognition rate from 38% to 44% (single‐layer perceptron model) and from 89.42% to 91.61% (multilayer perceptron model). This neuromorphic device technology based on S‐DNA is expected to contribute to the successful implementation of a future neuromorphic system that simultaneously satisfies high integration density and remarkable recognition accuracy.A bioinspired neuromorphic device operating as synapse and neuron simultaneously, which is fabricated on an electrolyte based on Cu In the emerging “Big Data” era, it is challenging to handle large amounts of informal data, such as characters, images, sounds, and other unstructured data formats using current computing technology based on von Neumann architecture (series and linear processing).x‐,x‐,x‐2Sb2Te5‐2O3/TiO2x memristor crossbar point array and demonstrated successful pattern classification of 3 × 3 binary images. In addition, PCRAM devices could emulate firing and relaxation functionalities of biological neurons owing to easy transition between insulator and metal. Tuma et al.2:Ag/Ag) neurons and drift memristor (Ta/HfOx/Pd) synapses, where they then demonstrated an unsupervised synaptic weight updating and a pattern classification by their fully memristive neural network.Since Jo et al.2+‐doped salmon deoxyribonucleic acid (S‐DNA) electrolyte. Owing to the slow Cu2+ diffusion through the base pairing sites in the S‐DNA, the S‐DNA device presents the special synaptic characteristic (LTP characteristic with negative nonlinearity), which consequently improves the accuracy of numerical digit pattern recognition of S‐DNA‐based neural network. In addition, this S‐DNA device successfully emulates the integrate‐and‐fire behavior of a neuron. As the S‐DNA synaptic and neural operations are based on Cu redox reactions (Cu ↔ Cu2+ + 2 e−), we discuss how the Cu2+ doping applied to the S‐DNA electrolyte influences the synaptic and neural operating characteristics, respectively, in terms of: i) the nonlinearity and weight update margin of LTP/LTD characteristics and ii) the threshold condition of firing phenomenon. We then predict the accuracy of MNIST pattern recognition with respect to the number of learning steps, where a single‐layer ANN structure (or a multilayer ANN structure for +NeuroSim simulator) and a back‐propagation weight update algorithm are applied.Herein, we report a bio‐inspired neuromorphic device operating as synapse and neuron simultaneously that is fabricated on a CuFigureVpre) is applied to the Cu/Ti electrode, an electric‐field‐assisted diffusion of Cu2+ occurs between Cu/Ti and Pt electrodes. The diffused Cu2+ adjust the conductivity of the S‐DNA device (synapse weight) by contributing to the formation of a Cu filament. Here, a Ti buffer layer was inserted at the Cu/S‐DNA interface to improve the operating stability of the S‐DNA device.2+ diffusion rate into the S‐DNA and ii) activation energy for the formation of the Cu filament. To understand the diffusion mechanism of Cu2+ in the S‐DNA electrolyte in detail, we performed Raman spectroscopy analysis and Fourier‐transform infrared spectroscopy (FT‐IR) analyses. Figure 2+‐doped S‐DNA films with various concentrations . In the spectral range from 600 to 1400 cm−1, we observed eight Raman peaks. Here, the four Raman peaks between 786 and 1095 cm−1 indicate the vibration mode of the backbone of S‐DNA,−1) are related to the S‐DNA base pairs of cytosine (C), adenine (A), thymine (T), and guanine (G).2+ concentrations. In particular, the intensity decrease in the Raman peaks for the base pairs was more severe than that for backbone peaks. As the Cu2+ concentration increased from 0 to 1 × 10−3m, the Raman peak intensities related to the S‐DNA backbone and base pairs decreased by ≈18% and 40%, respectively, as shown in Figure In a biological synapse, neurotransmitters are released from a presynaptic neuron. They then diffuse toward a postsynaptic neuron when an active signal reaches the presynaptic neuron. Subsequently, the neurotransmitters are combined with receptors at the postsynaptic neuron, generating a postsynaptic signal.2+ doping. This is because Cu2+ ions are preferably bound at the base pairing sites, thereby influencing the S‐DNA molecular structure.2+ to the S‐DNA molecule is graphically illustrated in Figure 2+ ions are, thus, expected to move through the base pairs in the S‐DNA molecule, enabling conductive filament‐based switching. We then investigated the postsynaptic current characteristics of the S‐DNA device to confirm its feasibility as a synaptic device. Figure Vpre = 4, 4.5, and 5 V) and inhibitory  pulses with a duration time (td) of 100 ms, respectively. The amplitude of the excitatory and inhibitory pulses was determined by the following procedure: i) we experimentally confirmed the set and reset voltages (VSET and VRESET) of the S‐DNA devices ; ii) we then selected three different pulse amplitudes near the VSET and VRESET values. Here, the chosen amplitudes for the excitatory pulses were 4, 4.5, and 5 V, and the ones for the inhibitory pulses were −4, −4.5, and −5 V because the VSET and VRESET were 4.5 and −4.5 V, respectively. The excitatory postsynaptic current (EPSC) value increased to 7.2 nA after applying the +4 V pulse, whereas the inhibitory postsynaptic current (IPSC) induced by the −4 V pulse decreased to −2.7 nA. Moreover, the EPSC and IPSC values could be controlled by adjusting the pulse amplitude. When increasing the amplitude of the excitatory pulse from 4 to 5 V, the EPSC value varied from 7.2 to 37.1 nA. Similarly, the ΔIPSC value decreased from −2.7 to −46.6 nA when the amplitude of the inhibitory pulse reduced to −5 V. The EPSC and IPSC characteristics of the S‐DNA device can be explained by the growth and decomposition of Cu filament by the presynaptic spike signal (Vpre), respectively, as illustrated in Figure Vpre is applied to the Cu/Ti electrode, Cu2+ ions diffuse into the S‐DNA electrolyte and then a Cu filament starts growing from the Cu surface through the reduction process (Cu2+ + 2e− → Cu). In contrast, an inhibitory Vpre will lead to the oxidation of the Cu filament (Cu → Cu2+ + 2e−), resulting in the decomposition of the filament in the S‐DNA film.Similarly, in the FT‐IR analysis shown in Figure S3 in the Supporting Information, we confirmed that the FT‐IR peak intensities related to the S‐DNA base pairs were reduced by CuFigureVpre = 4.5 V/−4.5 V and td = 100 ms). Here, the amplitudes of the excitatory and inhibitory pulses were chosen on the basis of the set and reset voltages of the S‐DNA device. As the excitatory pulses were applied, the current level was potentiated gradually from 1.7 to 52.1 nA. After that, the current level was depressed by the inhibitory pulses, eventually recovering to its initial level. From the LTP/LTD characteristic curves shown in Figure G = Gmax − Gmin). Here, the blue dotted lines indicate ideal LTP/LTD curves (α = 1) and the circle symbol shows the experimental conductance data. The conductance values were fitted by using the equations G = B(1−eP/A) + Gmin and G = −B(1−e(P−Pmax)/A) + Gmin, where B is a fitting factor, P is the pulse number, and A is the nonlinearity of potentiation (αp) and depression (αd). After fitting the data, we confirmed a special potentiation characteristic with a negative nonlinearity value in the S‐DNA device. Typical synaptic devices have an LTP curve with a positive nonlinearity value .p and positive αd) can be explained by the harsh Cu2+ diffusion condition in the S‐DNA electrolyte owing to the relatively lower number of defective sites. For easier understanding, we illustrated two operating mechanisms for the S‐DNA device, as shown in Figure 2+ ions from the Cu electrode diffuse through the base pairing sites of the S‐DNA to the Pt electrode and subsequently increase the conductance of the S‐DNA device.2+ in the S‐DNA electrolyte, the conductance value is predicted to slowly increase until the Cu2+ reacted with the electrons coming from the Pt‐side and a Cu filament is subsequently formed on the Cu‐side.2+ ions contribute not only to an increase in the conductance of the S‐DNA electrolyte but also to further growth of the Cu filament,p < 0). When a series of inhibitory pulses (from 1st to 7th) is applied, a Joule heating–assisted oxidation process (Cu → Cu2+ + 2e−) causes the dissolution of the Cu filament, resulting in an exponential decrease in conductance (Case II in LTD).2+ toward the Cu‐side (Case I in LTD) and the diffused Cu2+ ions are trapped at the Cu/S‐DNA interface.2+ in the S‐DNA electrolyte gradually as an inhibitory pulse is supplied, finally leading to a linear decrease in conductance. In particular, the magnitude of the nonlinearity factors for the LTP and LTD curves varied oppositely when the S‐DNA electrolyte was doped with a higher Cu2+ concentration. As shown in Figure p| reduced as the Cu2+ concentration increased from 0 to 1 × 10−3m (|αp|: 31 → 20), whereas |αd| increased from 12 to 18. This can be explained by the increase of the Cu2+ concentration in the S‐DNA electrolyte. Before the formation of the Cu filament . However, after the Cu filament partially forms, additionally supplied Cu2+ ions are predicted to help the growth of the Cu filaments (LTP‐side red region).2+ ions thicken the Cu filament, unlike in the control S‐DNA device, resulting in a large conductance change . Similar conductance change is expected in the LTD‐side two regions with (red) or without (blue) a Cu filament. Consequently, the 1 × 10−3m Cu2+‐doped S‐DNA device showed favorably symmetric LTP/LTD characteristics (αp: −20/αd: 18). The weight update margin (ΔG) was also dependent on the Cu2+ doping concentration. By increasing the Cu2+ concentration from 0 to 1 × 10−3m, ΔG was improved by factors of 8.2 (ΔG: 33 → 287 nS), as seen in Figure The S‐DNA device was investigated in more detail in terms of its long‐term synaptic plasticity, such as its LTP/LTD characteristics. td) of voltage stimulus pulse. FigureVpre = 4.5 V, f = 1 Hz). Like in the previous case in which a short voltage pulse with td = 50 ms was applied, the current of the S‐DNA device gradually increased as pulses with td = 100 ms were supplied continuously (I = 157 nA after applying the tenth pulse), representing long term plasticity. The increment in the current became larger when the duration time increased to 500 ms (I = 1.19 µA after applying the seventh pulse), and most of the increased current disappeared after the eighth pulse. This phenomenon indicates that the S‐DNA device can operate as a neuron on the basis of two mechanisms: i) “integrating” electrical input signals and ii) “firing” electrical output signals when the integrated value exceeds a threshold point. This device‐mode conversion from synapse to neuron was possible by virtue of the difference in growth rate of the Cu filament, which was dependent on the td of an input pulse. During the operation of the S‐DNA device, the amount of diffused Cu2+ ions is proportional to the energy (Vpre × td), which is related to the applied voltage pulse.td = 100 ms), the Cu filament grew slowly owing to the decreased supply of Cu2+, resulting in a small increase in the current , a higher supply of Cu2+ accelerated the growth of the Cu filament. This rapidly grown Cu filament reached the Cu electrode, suddenly generating a spiking current . Here, the positive voltage pulses with amplitudes of 4.5, 1.5, and 1 V, which were the same as the EPSC pulses used in the Figure −3m Cu2+‐doped S‐DNA devices, respectively. The threshold current level for firing was set as 0.5 µA. In the control device (Cu2+ 0 × 10−3m), an output current signal was fired after a +4.5 V voltage pulse was supplied eight times (N = 8), where the peak current at the firing state was ≈1 µA. After doping the S‐DNA device with 0.1 × 10−3m Cu2+, the output current signal was fired early after the sixth input pulse (N = 6), showing a higher peak current of 1.5 µA. The peak current in firing increased up to 1.8 µA and the number of voltage pulses required for firing reduced to N = 3 by doping the device with 1 × 10−3m of Cu2+. This is attributed to the reduction in activation energy required for neuron firing owing to an increase in Cu2+ concentration. Figure −3m (control) and 1 × 10−3m Cu2+ doping conditions. When presynaptic voltage pulses are supplied continuously, Cu ions steadily stick to the Cu filament (pulse integration), eventually generating a spiking current pulse instantly (firing of neuron). From the neuron operating point of view, Cu2+ doping allowed for a relatively low amplitude of presynaptic voltage pulse (V0mM > V1mM) and a low number of pulses for neuron firing (N0mM > N1mM). Here, after the initial firing occurred, the S‐DNA neuronal device did not show the firing phenomenon again. This is likely due to the nonvolatile characteristic of Cu conduction filament formed in S‐DNA electrolyte. To remedy this shortcoming, it is necessary to initialize the Cu conductive filament with the assistance of external electrical element or circuit. For instance, Wang et al.2:Ag/Ag) and an external electrical component  to achieve a leaky integrate‐and‐fire behavior and a persistent firing of neuron device.We also found that the operating mode of the S‐DNA device can convert from synapse to neuron by adjusting the duration time td of voltFigure+ and G−) were connected between the presynaptic and postsynaptic neurons; we calculated synaptic weight as W = G+ − G−. After the MNIST image data  were transmitted to the input layer, they generated the postsynaptic current vector (I = ∑V × W), which is a product of the image data vector and the synaptic weight vector . This postsynaptic current vector was then converted into an output vector (f(net)) through the sigmoid activation function. Finally, to update the synaptic weight, we calculated the difference (δ) between the output value of each output neuron (Vout) and the label data of the MNIST dataset (Vlabel). If the sign of the product of the δ value and the input value (sgn(δ × Vi)) was positive, the relevant synapses' weights were updated in an increasing direction and vice versa. In the case of δ = 0, the synaptic weight did not change (sgn(δ × Vi) = 0). The MNIST learning phase is described in more detail in Figure S6 in the Supporting Information. The mapping images of 784 synaptic weights for the number “5” are plotted in Figure 2+ doping concentration, the shape of the number “5” appeared more clearly in the mapping image, in which the color of the filled pixels became darker. This means that the Cu2+ doping process successfully improved the learning performance of ANNs consisting of S‐DNA devices. This improvement was possible owing to the negative LTP nonlinearity  and the high weight update margin, which were achieved by the Cu2+ doping. To analyze the performance of ANNs quantitatively with respect to various Cu2+ doping concentrations, we performed a supervised learning with the MNIST learning dataset and then predicted the recognition rate. The MNIST test phase is detailed in Figure S7 in the Supporting Information. The average recognition rate for every 5000 learning phases was plotted in Figure −3m Cu2+ doping. As predicted, the recognition rate after 60 000 learning phases increased from 38% to 44% as the concentration of Cu2+ increased from 0 to 1 × 10−3m. This improvement in recognition rate achieved by increasing Cu2+ concentration was also identified by the multilayer perceptron (MLP) model‐based MNIST simulation. Here, the MLP‐based MNIST simulation was conducted on the “+NeuroSim” platform,2+ concentration increased from 0 to 1 × 10−3m. The maximum recognition rate in this study (91.61%) was higher than the values obtained by conventional ReRAM‐based ANNs (10–73%), which was also comparable to the value predicted by the FeFET synaptic device (≈90%).With the S‐DNA synaptic devices, we virtually constructed an online learning platform based on single‐ and multilayer artificial neural networks (ANNs), as shown in  V1−V78, V were  V1−V78, V were p) and the weight update margin (ΔG) affect the recognition rate. The mathematical LTP/LTD model was built with the equations G = B(1−Pe/A) + Gmin and G = −B(1−e(P−Pmax)/A) + Gmin. Figure d = −16 (Pmax = 64 and ΔG = 10). The negative and positive LTP nonlinearity values respectively indicate the synaptic operations of the S‐DNA device and typical ReRAMp values  and then plotted the resulting recognition rates as a function of the learning phase in Figure p was varied from 16 to −64, the recognition rate after learning with 60 000 MNIST image data did not change much and just varied between 32% and 36%. However, for αp = −16, the recognition rate immediately improved up to ≈42%. This is because the synaptic weights continue to increase as pulse signals for potentiation are supplied, unlike in the case of the conventional LTP characteristic with a positive αp in which synaptic weights are saturated as the number of input pulses increases. In addition, the weight update margin (ΔG) also influenced the recognition rate. We prepared LTP/LTD curves with different magnitudes of ΔG, with ΔG = 1, 10 for the undoped S‐DNA device and ΔG = 100 for the Cu2+‐doped S‐DNA device , where the operating mode of the device could be converted by adjusting the duration time (td) of the voltage pulse. When a voltage pulse with a short duration time (td = 100 ms) was applied, the device successfully emulated the synaptic function, such as LTP/LTD characteristic. In addition, as applying a voltage pulse with a long duration time (td), the device worked as a neuron based on its “integrate‐and‐fire” behavior. In particular, the following remarkable enhancements in the synaptic characteristics were achieved by using the Cu2+ doping technique: i) improvement in the nonlinearity of the LTP characteristic (|αp|: 31 → 20) and ii) increase in the weight update margin (ΔG: 35 → 287 nS). The Cu2+ doping also modulated the threshold conditions for the firing of the neuronal device: i) the amplitude of the presynaptic voltage pulse (Vpulse: between 4.5 and 1 V) and ii) the required number of pulses for neuron firing (N: between 8 and 3). This is because Cu2+ doping of the S‐DNA electrolyte reduced the activation energy for the formation of the conduction filament. In addition, owing to the negative LTP nonlinearity (the symmetric LTP/LTD characteristic) and the high weight update margin, which were achieved by the Cu2+ doping, the MNIST pattern recognition rates improved from 38% to 44% (single‐layer perceptron model) and from 89.42% to 91.61% (multilayer perceptron model) with an increase in the concentration of Cu2+ from 0 to 1 × 10−3m.In conclusion, we studied a salmon deoxyribonucleic acid (S‐DNA)‐based neuromorphic device operating as both a synapse and a neuron. The S‐DNA synaptic and neural operations were based on Cu redox reactions  was dissolved in 10 mL of deionized (DI) water to make an S‐DNA solution. Then, 0, 0.1, and 1 × 10−3m of Cu2+ 2 purchased from Sigma Aldrich, St. Louis, USA) were added to the S‐DNA solution, followed by magnetic stirring (1000 rpm for 24 h at room temperature). For the formation of an S‐DNA film, 20 µL of the Cu2+‐doped S‐DNA solution was spin‐coated on an SiO2/Si substrate at 3000 rpm for 90 s, and then the samples were annealed at 100 °C in a vacuum oven for 2 min. The illustration that describes this process is in Figure S1 in the Supporting Information. The thickness of S‐DNA electrolyte was ≈30 nm , which was investigated by performing atomic force microscopy .2+‐Doped S‐DNA Thin FilmCharacterization of the Cu: The S‐DNA thin films with different concentrations of Cu2+  were subjected to Raman spectroscopy  and FT‐IR (MIR_ATR (ZnSe), Bruker Inc.) analysis. A Raman spectroscope with an excitation wavelength of 532 nm was used. The beam size of the laser was ≈0.7–0.9 µm, and the instrumental spectral resolution was less than 0.9 cm−1. The FT‐IR spectral range was from 600 to 3700 cm−1, the scan rate was 32 scans per s, and the resolution was ≈4 cm s−1. To analyze the FT‐IR data, we subtracted the background spectrum produced by bare glass.Fabrication of the S‐DNA Neuromorphic Device: The surface of the SiO2 substrate was cleaned through a sonication process for 10 min in acetone, 2‐propanol, and deionized water. A bottom electrode with Pt (10 nm) and Ti (5 nm) was formed on the SiO2 substrate using an e‐beam evaporator and a shadow mask . After coating a 20 nm thick S‐DNA film on the Pt/Ti/SiO2 sample, a top electrode with Cu (30 nm) and Ti (2.5 nm) was deposited using the same shadow mask with the 5‐line pattern.Characterization of the S‐DNA Neuromorphic Device: The fabricated S‐DNA devices were electrically analyzed by using a semiconductor parameter analyzer (HP‐4155A) connected with a voltage pulse generator . The measurement set up is described in Figure S2 in the Supporting Information. To read the current flowing between pre‐ and postsynaptic terminals, a constant voltage of 0.1 V was applied to a presynaptic terminal. To analyze synaptic characteristics, a series of 15 excitatory/inhibitory pulses (td = 100 ms) was applied to a presynaptic terminal; Vpre were ± 4.5, ± 1.5, and ± 1 V for the 0, 0.1, and 1 × 10−3m Cu2+‐doped S‐DNA devices, respectively. To investigate the neural characteristics of S‐DNA devices, a series of potentiation pulses (td = 500 ms) was used. Here, the values of Vpre were the same as the values used for synapse characterization.The authors declare no conflict of interest.SupplementaryClick here for additional data file.


Harmful materials in the blood are prevented from entering the healthy brain by a highly selective blood–brain barrier (BBB), and impairment of barrier function has been associated with a variety of neurological diseases. In Alzheimer's disease (AD), BBB breakdown has been shown to occur even before cognitive decline and brain pathology. To investigate the role of the cerebral vasculature in AD, a physiologically relevant 3D human neural cell culture microfluidic model is developed having a brain endothelial cell monolayer with a BBB‐like phenotype. This model is shown to recapitulate several key aspects of BBB dysfunction observed in AD patients: increased BBB permeability, decreased expression of claudin‐1, claudin‐5, and VE‐cadherin, increased expression of matrix‐metalloproteinase‐2 and reactive oxygen species, and deposition of β‐amyloid (Aβ) peptides at the vascular endothelium. Thus, it provides a well‐controlled platform for investigating BBB function as well as for screening of new drugs that need to pass the BBB to gain access to neural tissues. An increase in permeability of the blood–brain barrier (BBB) has long been considered a key factor in the cause and consequences of Alzheimer's disease (AD). In this study, a physiologically relevant 3D model is developed and used to investigate several key aspects of BBB dysfunction in AD and to provide a standardized platform for screening of new drugs. However, these models lack AD neurons and also fail to reproduce the gradual accumulation of soluble Aβ peptides in the extracellular matrix (ECM) and their transport through the local microenvironment.Microfluidic technology has emerged as a powerful tool for studying new multicellular phenomena with precise control of 3D cellular and noncellular microenvironments, integration of multiple functional steps in one experimental platform, and improved imaging capabilities. We previously developed a 3D human neural cell culture model of AD in which human‐origin neural progenitor cells (NPCs) expressing amyloid precursor protein (APP) or APP/presenilin 1 (PSEN1) with familial AD (FAD) mutations grow to maturity in a 3D culture system (referred as “3D AD” culture).In the present study, we successfully reproduced the 3D AD culture system with an intact vascular wall in a 3D microfluidic platform to study direct effects of the AD pathological microenvironment on bECs, a major component of the BBB. Our microfluidic AD platform mimics the cerebral–vascular interface by reconstituting a tube‐shaped bEC barrier that has BBB‐like phenotype and integrates into a 3D AD culture system (referred as our “AD model”). Our AD model successfully mimics several vascular alterations observed in AD patients. These include increased BBB permeability with decreased expression of tight junction proteins, claudin‐1 and claudin‐5, and adherens junction (AJ) protein, VE‐cadherin, increased levels of matrix‐metalloproteinase‐2 (MMP‐2) and reactive oxygen species (ROS), and aggregation of Aβ on the abluminal side of the BBB endothelium. To explore the consequences of the impaired BBB in AD pathogenesis, we introduced thrombin, a bloodborne toxic enzyme, within the endothelialized channel. Thrombin was able to pass the leaky BBB and exacerbated neuronal loss in AD, which was prevented by decreasing BBB permeability using pharmacological interventions. We demonstrate that our AD model serves as a well‐controlled platform to understand physiological and pathological mechanisms of BBB dysfunction in AD and can usefully be employed as a standardized therapeutic drug screening platform.22.1We previously reported a unique strategy for recapitulating AD pathology, namely Aβ‐driven neurofibrillary tangles, in a human NPC‐derived 3D Matrigel culture system.FigureWe developed the AD and WT models by incorporating and coculturing a tube‐shaped bEC barrier with 3D‐differentiated ReN‐AD or ReN‐WT cultures in a 3D microfluidic platform. The microfluidic platform consists of five parallel channels fabricated from polydimethylsiloxane (PDMS) elastomer Figure1a. TheTo compensate for the different maturation periods and culture conditions required by the ReN cells and the bEC monolayer, and also to prevent the potential influence of ReN‐AD cells on the bEC barrier during monolayer formation, we developed a simple sequential culture method in which the ReN cell and BBB chambers were separated by the barrier MC, an intervening channel initially filled with air, to allow each cell type to mature independently Figure b.7 cells mL−1 and injected into the 3D ReN cell culture MC. After incubation in 5% CO2 at 37 °C for 30 min, ReN cell differentiation media was added into the ReN cell media MC. ReN cells were differentiated for 5–7 d before initiating bEC barrier formation.ReN‐AD and ReN‐WT cells were individually mixed with Matrigel (1:1 dilution in Dulbecco's Modified Eagle Medium: Nutrient Mixture F‐12 (DMEM/F12) medium supplemented with B27 and heparin) at a density of 10−1 collagen type 1 solution was loaded into the collagen scaffold MC and allowed to gel. On the next day, hCEMC/D3, a well characterized and established brain endothelial cell line,−1 of pH 7.4 collagen type 1 to allow communication between the ReN cells and the bEC monolayer through the ECM via diffusion of soluble factors  and glial fibrillary acidic protein (GFAP) showed that most ReN cells differentiated into MAP2‐positive neurons with some GFAP‐positive astrocytes in both the 3D ReN‐AD and ReN‐WT cultures Figure e.Expression and localization of AJs and tight junctions (TJs) of the bEC monolayer were verified with immunofluorescent staining for VE‐cadherin , and ZO‐1 and claudin‐5 (both TJ proteins). Our staining analysis confirmed that VE‐cad, ZO‐1, and claudin‐5 were expressed and localized along the cell junction of the bEC monolayer  . Daily medium replacement in the bEC barrier MC was also included. All simulation details are presented in the Experimental Section.To further explore the mechanism of Aβ accumulation in the AD model,2.2−6m fluorescent (FITC)‐labeled or Texas Red‐labeled dextran (Mw: 3 and 40 kDa) in culture media to the bEC barrier MC on days 3 and 6 of coculture, and then imaging the fluorescence every 5 min for more than 30 min. The permeability was calculated by measuring the mean fluorescence intensity in a control volume (CV) defined in the collagen gel immediately after introducing the dextran to the MC and again 10 min later, then applying a permeability equation , as compared to the WT model   analysis, ReN‐AD or ReN‐WT cells were cultured and differentiated on a 24‐well plate for 5–7 d, and then combined with a bEC monolayer formed on collagen and matrigel‐coated inserts. At coculture day 3, the bECs were collected, and gene expression levels of TJs , and the AJ [CDH5 (VE‐cadherin)] were analyzed by qRT‐PCR. Among them, the levels of CLDN1 (claudin‐1), CLDN5 (claudin‐5), CDH5 (VE‐cad) expressions in bECs were significantly decreased when cocultured with ReN‐AD cells compared to those cocultured with ReN‐WT cells ) , which prevents the production of Aβ by blocking the β‐secretase enzyme. We added 1 × 10) Figure e. We per) Figure f and inc) Figure g. These 2.6FigureAβ deposition is observed in the cerebrovasculature and is usually described as cerebral amyloid angiopathy (CAA). Aβ deposition in the vasculature leads to proinflammatory and cytotoxic events that contribute to the greater BBB permeability in the AD brain. To check whether Aβ species secreted from ReN AD cells are directly deposited onto the bEC barrier in our AD model, we performed immunofluorescent staining with Aβ40 and Aβ42 antibodies at coculture day 6. Aβ deposition was evident in the 3D AD model, but not in 3D WT model Figure4a. TheIn order to explore whether Aβ can pass the BBB once its permeability is increased, we measured the levels of Aβ40 and Aβ42 in the bEC barrier MC. Although the levels of both were higher in the 3D ReN cell MC of the AD model compared to the WT model Figure e, they w2.7FigureIn AD patients, it is possible that circulating neurotoxins enter the brain through the disrupted BBB and exacerbate AD progression. Therefore, enhancing BBB integrity by pharmaceutical drugs might yield beneficial therapeutic effects by blocking the neurotoxins from entering the brain. We tested these hypotheses using our AD models. We first demonstrated that the leakage of neurotoxins through the disrupted BBB can damage neural cells. For this, we introduced thrombin, a serine protease which is directly neurotoxic, that causes proinflammatory effects and whose level is elevated in the brain and cerebral microvasculature in AD,−6m, respectively, on coculture day 2. After 24 h, we performed a permeability analysis by introducing 3 and 40 kDa dextran into the bEC barrier MC. Etodolac significantly decreased the permeability of the bEC in the AD model compared to vehicle (0.01% DMSO), while beclomethasone did not show such effects  Figure e, leadin3Numerous studies have suggested that BBB breakdown initiates and/or contributes to a vicious cycle of AD progression, resulting in neuronal loss and dysfunction.Our AD model has the following capabilities, which were otherwise difficult to perform with the traditional in vitro BBB transwell models: 1) it provides a 3D microenvironment for cells to quantitatively evaluate bEC barrier permeability; 2) it allows for integration of multiple functional steps in a single experimental platform; 3) it enables enhanced imaging capabilities and economy in reagent and tissue sample size; 4) the developed sequential, compartmentalized culture method allows for the different culture conditions and maturation periods of ReN cells and the bECs; and 5) it realizes a gradual accumulation of Aβ appearing in brains of AD patients by allowing AD cells to continually release Aβ, which gradually accumulates within and diffuse into the ECM. These capabilities enable more physiologically relevant in vitro modeling in our AD model compared with other previous in vitro models.The paracellular permeability of the bEC barrier was increased in our AD models and it was accompanied by decreased expression of tight junction proteins, claudin‐1 and claudin‐5, and an adherens junction protein, VE‐cadherin. The mechanism(s) of BBB impairment in AD are likely diverse and complex. Aβ might directly increase permeability of the bEC barrier. We found that the levels of oxidative stress, MMP‐2, and IFNγ were increased in our AD model compared to the WT model, all of which have shown to impair BBB function in AD. Interestingly, Aβ did not pass the impaired BBB, but rather deposited on the wall of bECs, mimicking CAA pathology. Future studies will require investigation of whether expression of Aβ transporters is altered on the bECs of our AD model. Reducing Aβ production by the treatment of BACE1 inhibitor, LY‐2 886 721, significantly reduced the permeability of bEC barrier in our model, while it increased the expression level of claudin‐5. These results suggest that Aβ itself and/or Aβ‐driven molecular changes effect BBB dysfunction in AD and that reducing parenchymal Aβ pharmacologically could also reduce BBB leakage in AD.Using our AD model, we were also able to suggest that increasing BBB integrity pharmacologically might prove to be a useful therapeutic approach for AD treatment by preventing blood‐originated neurotoxins from entering the brain. Accumulation of neurotoxins, such as fibrinogen and thrombin, that enter though impaired BBB from the circulation was observed in AD patients.We recognize that we do not reconstitute the BBB vasculature entirely. Our model does not contain astrocytes and pericytes both of which play roles in BBB maintenance and function. Rather, in the present study, we have chosen to first study a simpler disease model in order to focus on interactions between the AD cells and bECs, both key components of the BBB. In addition, it has recently been reported that the cerebral vasculature of AD patients has 50% less coverage of pericytes than healthy brains,Recently, attempts have been made to develop more human‐relevant BBB cultures in vitro by employing induced pluripotent stem cells (iPSCs).We believe that our AD model will be a useful standardized tool in the study of BBB biology in AD and also provide a platform for moderate‐throughput drug screening of drugs to inhibit BBB dysfunction or enhance BBB integrity as an adjunct to other AD therapies.4Fabrication of Microfluidic Platform: The micropatterned master with features 150 µm in height was fabricated by using standard photolithography. SU‐8 100 was coated and patterned on a 4 in. silicon wafer by exposing UV light to the top of a transparent photomask on which the desired patterns are printed. A mixture of PDMS  and its curing agent were mixed to a 10:1 weight ratio, poured onto the patterned master to a 5 mm thickness, degassed to remove air bubbles, and cured in an oven at 80 °C for 1.5 h. The cured PDMS was removed from the wafer and holes were punched through the reservoir patterns to make inlets and outlets for media and hydrogel filling. After sterilization, the devices and glass coverslips were assembled by using oxygen plasma treatment and filled with 60 µL of 1 mg mL−1 poly (D‐lysine) solution  to strengthen the attachment of hydrogel to the surface. After incubation for 2 h at 37 °C, the PDL solution was removed, and then the devices were rinsed with water and dried at 80 °C overnight.Cell Culture: Human cerebral microvascular endothelial cells , a cell line derived from human temporal lobe microvessels, were cultured to 90% confluence on a 150 µg mL−1 collagen type 1 coated flask in EndoGRO‐MV Complete Culture Media Kit  supplemented with 1 ng mL−1 bFGF  and 1% penicillin‐streptomycin. ReN‐WT and ReN‐AD cells were cultured on a Matrigel coated flask in proliferation media; DMEM/F12  supplemented with B27 , heparin , 20 ng mL−1 epidermal growth factor (EGF), and 20 ng mL−1 fibroblast growth factor 2 (FGF‐2).3D Cell Culture in the Microfluidic Platform: ReN‐WT and ReN‐AD cells in a 25T confluent flask were washed with D‐PBS and treated with Accutase  in a 37 °C CO2 incubator for 3–5 min for dissociation of cells. The prewarmed differentiation medium was added to the flask, and the cell suspensions were transferred into 15 mL tubes and centrifuged at 2000 g for 3 min. The cells were resuspended at a density of 2 × 107 cells mL−1 in the differentiation medium and placed on ice. ReN cell suspensions were mixed with cold Matrigel at the volume ratio of 1:1 , introduced into the 3D AD culture MC, and placed in a 37 °C CO2 incubator for 30 min. After 30 min, the prewarmed differentiation medium was injected into the ReN cell media MC. After 5–7 d, 4 mg mL−1 collagen type 1 solution, which was prepared by diluting high concentration collagen type 1  in 10× PBS and sterilized deionized water and titrated to pH 7 with 0.5 N NaOH, was injected into the collagen scaffold MC and incubated at 37 °C and 5% CO2 for 30 min. After 1 d, bEC barrier MC was coated with growth factor reduced Matrigel  for 40 min and hCMEC/D3 cells were seeded at a density of 2 × 106 cells mL−1 on the sidewall of the collagen scaffold and top and bottom surfaces of the bEC barrier MC. hCMEC/D3 cells were allowed to form a tight monolayer along the MC for 2–3 d in hCMEC/D3 growth medium. After bEC barrier formation, ReN cell chamber and BBB chamber were connected and allowed to communicate by filling 2 mg mL−1 of pH 7 collagen gel  into the barrier MC. After connection, hCMEC/D3 cells were cultured in EndoGRO‐MV Complete Culture Media Kit  supplemented with 0.5% fetal bovine serum (FBS), 1 ng mL−1 bFGF , and 1% penicillin–streptomycin.Permeability Measurement: The permeability was determined by adding hCMEC/D3 culture medium with 10 × 10−6m FITC‐labeled dextran (Mw: 40 kDa) into the bEC barrier MC 3 and 6 d after connecting the ReN cell chamber and the BBB chamber. Fluorescent images were recorded every 5 min for 2 h with a confocal microscope. The permeability was estimated by measuring the mean fluorescence intensity in a CV defined in the collagen gel at time 0 and time 600 s and then applying the equationVg is gel volume in the CV, Av is vessel surface area in CV, Ig¯ is fluorescence intensity in gel, Im is fluorescence intensity at the monolayer (Im = Ilumen − Igel) at time 0, and ddtIg¯ is the rate of increase in intensity as the dextran diffuses out of the bEC barrier MC into the gel .Reconstitution and Treatment of Aβ40 and Aβ42: Vacuum‐dried synthetic monomeric Aβ40 and Aβ42, which were obtained from Dr. Robert Moir , were reconstituted by adding 200 µL of 20 × 10−3m NaOH, mixing gently multiple times then allowing 30 s for settling. After several mixing steps, the reconstituted Aβ40 and Aβ42 solutions were centrifuged at 10 000 rpm for 1 min and diluted to the desired concentration with sterilized water. Matrigel (diluted in ReN cell differentiation medium at the volume ratio 1:1) was injected into the 3D AD culture MC, collagen scaffold was then introduced to the collagen scaffold MC, and after Matrigel coating hCMEC/D3 was seeded and the monolayer formed. After monolayer formation, the Aβ40 and Aβ42 solutions were introduced into the ReN cell media MC with ReN cell differentiation medium, after which the ReN cell and BBB chambers were connected.Fluorescent‐Tagged Aβ40 and Aβ42 Treatment for CAA Model: Synthetic human HiLyte Fluor 555‐labeled Aβ40 and FAM‐labeled Aβ42  were reconstituted in 1% NH4OH and diluted to the desired concentration of 500 ng mL−1 with ReN cell differentiation media. The reconstituted synthetic human HiLyte Fluor 555‐labeled Aβ40 and FAM‐labeled Aβ42 were added into the ReN cell media MC and refreshed daily for 6 d.Immunofluorescent Staining and Image Acquisition: Cells cultured in the microfluidic system were fixed by incubating with 4% (w/v) paraformaldehyde in PBS for MAP2; GFAP; VE‐cad; ZO‐1; RAGE; pgp; LRP1; Aβ40/42 antibodies or methanol for claudin‐5 antibody for 15 min, and permeabilized with 1% Trion‐x100 (Sigma‐Aldrich) in PBS for 5 min. After blocking overnight at 4 °C, primary antibodies including anti‐MAP2 , anti‐GFAP ; anti‐VE‐cadherin ; anti‐ZO‐1 ; anti‐claudin‐5 ; anti‐RAGE ; anti‐pgp, ; anti‐LRP1; and anti‐Aβ40/42  were added and incubated overnight at 4 °C. After washing the MCs with PBS at least two times, secondary antibodies including Alex Fluor‐488‐conjugated goat‐rabbit and goat‐mouse IgG ; Alex‐647‐conjugated goat‐rabbit and goat‐mouse IgG were introduced to the channels and incubated at RT for 2 h, followed by 6‐diamidino‐2‐phenylindole  for cell nuclei staining.Intracellular ROS Measurement: Intracellular ROX production was measured by CellROX Orange Reagent  according to manufacturer's protocol. At coculture day 3, HCMEC/D3 cells in the bEC barrier MC were incubated with 5 × 10−6m of CellROX Orange Reagent  for 30 min at 37 °C in the dark, followed by triple washing with prewarmed PBS. Then, cells were examined with a confocal laser scanning microscope  at an excitation/emission wave‐length of 545/565 nm.Cell Apoptosis Assay: On coculture day 3, HCMEC/D3 cells in the bEC barrier MC were incubated with 5 × 10−6m of CellEvent Caspase‐3/7 Green Detection Reagent  with Hoechst for 30 min at 37 °C in the dark and washed twice with prewarmed PBS. Cells were imaged with a confocal laser scanning microscope  at excitation/emission wave‐length of 502/530 nm for CellEvent Caspase‐3/7 Green Detection Reagent and 361⁄497 nm for Hoechst.Real‐Time Quantitative Reverse Transcription PCR: Total RNA was isolated and purified using the RNeasy Mini kit  according to manufacturer's instructions. The concentration of total RNA was measured using a Nanodrop 1000 Spectrophotometer. cDNA was synthesized using High‐Capacity RNA‐to‐cDNA Kit  according to manufacturer's protocol. Quantitative Real‐time RT‐PCR was performed on a 7900HT Fast Real‐Time PCR System  using TaqMan Fast Advanced Master Mix . GAPDH was used as a housekeeping gene. Expressions of the following genes in hCMEC/D3 cells were quantified using TaqMan Gene Expression Assays : GAPDH (Hs03929097_g1), CLDN1 (Hs00221623_m1), CLDN5(Hs00533949_s1), OCLN(Hs00170162_m1), ZO‐1(Hs01551861_m1), CDH5 (Hs00901463_m1).Computational Simulation of Concentration Profile of Aβ in the AD‐BBB Model: Concentration profiles of Aβ within the microfluidic system were simulated using COMSOL Multiphysics 5.2. The changes of the concentration profiles over time were estimated by Fick's second law C is concentration and D is the diffusion coefficient. Aβ size was taken as 4 kDa, and the diffusion coefficient of Aβ in media, Matrigel, 2 mg mL−1 collagen, and 5 mg mL−1 collagen were taken from the literature to be 1.8 × 10−10, 1.24 × 10−10, 0.7 × 10−10, and 0.62 × 10−10 m2 s−1, respectively.−7 mol m−3 considering Aβ production before connecting two chambers. The rate of Aβ production by AD cells was assumed to be 5 × 10−12m per hour and diffusion through cells was assumed to be 2 × 10−15 m2 s−1 based on the detected Aβ amount from media in ReN cell media and bEC barrier MC.where BACE1 Inhibitor Treatment: After seeding and differentiating ReN‐AD cells for 2 d, 1 × 10−6m of BACE1 inhibitor  was added with differentiation medium in the ReN media MC. Media was refreshed every day with 1 × 10−6m of BACE1 inhibitor.ELISA Analysis: The measurement of Aβ40 and Aβ42 was performed using the Meso Scale Discovery  96‐well plate V‐PLEX Aβ peptide kits, as outlined in the manufacturer's protocol. The levels of IFNγ, IL‐1β, IL‐6, IL‐8, and TNFα were measured by MSD 96‐well plate Human Pro‐Inflammatory V‐PLEX Human Pro‐Inflammatory Assay kits. MMP‐2, MMP‐3, and MMP‐9 were measured by MSD 96‐well plate Human MMP ultrasensitive kits.The authors declare no conflict of interest.SupplementaryClick here for additional data file.