Cellular materials are recognized for their high specific mechanical properties, making them desirable in ultra-lightweight applications. Periodic lattices have tunable properties and may be manufactured by metallic additive manufacturing (AM) techniques. However, AM can lead to issues with un-melted powder, macro/micro porosity, dimensional control and heterogeneous microstructures. This study overcomes these problems through a novel technique, combining additive manufacturing and investment casting to produce detailed investment cast lattice structures. Fused filament fabrication is used to fabricate a pattern used as the mold for the investment casting of aluminium A356 alloy into high-conformity thin-ribbed (~ 0.6 mm thickness) scaffolds. X-ray micro-computed tomography (CT) is used to characterize macro- and meso-scale defects. Optical and scanning electron (SEM) microscopies are used to characterize the microstructure of the cast structures. Slight dimensional  variations originate from the 3D printing of the pattern. At the mesoscale, the casting process introduces very fine (~ 3 µm) porosity, along with small numbers of (~ 25 µm) gas entrapment defects in the horizontal struts. At a microstructural level, both the (~ 70 μm) globular/dendritic grains and secondary phases show no significant variations across the lattices. This method is a promising alternative means for producing highly detailed non-stochastic metallic cellular lattices and offers scope for further improvement through refinement of filament fabrication. As a result, this class of materials is being considered for a wide range of potential applications across transportation , medical (e.g. scaffolding/stenting12), among other industries15. In applications that demand significant load-bearing capability, metallic lattice structures are most appropriate.Cellular lattices are characterized by an interconnected solid scaffold configuration, showing high specific strength and very low relative density18, although they may also be produced by powder metallurgy21, wire-weaving24, additive manufacturing28 and casting32.Stochastic cellular lattices are classically produced by the introduction of foaming/blowing agents in alloy melts35, however, they tend to have issues in terms of poor fine detail/dimensional control. Further, at a finer scale metal-based additive manufacturing techniques have been reported to promote meso- and micro-scale defects, such as: porosity, delamination, and un-melted powders, as well as highly anisotropic grain morphologies as a function of build direction44.Regular periodic lattice structures have the advantage that the properties can be more precisely tailored. Additive manufacturing techniques are reported to be able to produce such lattices with thin-walls and struts with thicknesses down to ~ 0.24mm45 allowing good dimensional control50 coupled with good microstructural control53. However, the main difficulties associated with casting techniques are frequently related to mold production54. To address this issue, recent research has focused on developing novel hybrid additive manufacturing assisted investment casting techniques57 which is the focus of the current study.Some of these issues may be addressed by metal casting techniques, where there have been recent advances on the filling of thin-walled molds58. As a hypoeutectic aluminium alloy, the microstructural characterization of A356 is often concerned with the size and shape of the α-Al matrix61, eutectic Si65, Mg2Si and Fe-based intermetallic compounds69, such as Chinese script-shaped α-Al8Fe2Si and needle-shaped β-Al5Fe2Si. In as-cast samples, previous to solution treatment, Mg2Si are precipitated in the grain boundaries71 and, due to the presence of Mg, Chinese script-shaped π-Al8FeMg3Si6 may also be observed49.Here we take a look at the metallurgical aspects of A356 aluminium alloy lattice structures. A356 is the most common Al alloy used to cast components for transportation industries due to its capability to be cast in ceramic block to produce thin-walled and complex geometriesWe characterize hybrid additive manufacturing assisted investment cast lattice structures at the macro-, meso- and microstructural scales using a combination of X-ray micro-computed tomography (μCT) and optical/electron microscopy in order to assess its promise for the manufacture of fine periodic lattice structures. While the manufacturing approach is considered to be applicable to many lattice design, here the selected lattice topology is a classic reentrant honeycomb configuration which has been widely explored for its auxetic (i.e. negative Poisson’s ratio) behavior. While having a bending dominated deformation mechanism, it has also been shown to possess high specific strength, relatively to other more common open cellular lattices.Figure 74.Regarding the deviations introduced during the production of the PLA pattern (Step I), these can be primarily attributed to the precision of the 3D-printer stepper motor (resolution ± 12.5 μm). Additionally, vertical struts may become bent due to interactions with the rigid nozzle, whereby molten filament in the nozzle may adhere to already deposited PLA as well as due to thermal expansion/contraction effects due to temperature mismatch and oscillations between glass/rubbery states75; and (ii) during/after A356 melt casting: due the contraction of the A356 alloy during the solidification and subsequent cooling77. The net result is that the final A356 cast samples tend to display slightly larger dimensions than the PLA samples.Deviations between the PLA pattern and the final A356 lattice structure (Step II) can be attributed to dimensional changes that occur during two distinct processing stages; (i) forming the investment cast: due to the expansion of the investment gypsum mold during its curing which involves the loss of water and the transformation of gypsum from α  to β (quartz)The data in Fig. The analysis of both the deviations from the CAD model and their statistical distribution upon making the PLA pattern (Stage I) and then casting the A356 lattice (Stage II) are shown in Fig. 78 mean that fine artifacts are introduced into the PLA pattern. However, it is evident that these artifacts are not present in the final A356 sample, probably because they are extremely thin such that the melt is not able to fill their cavities.X-ray μCT was also used to characterize the details and defects. Figure 79 originating from Step I. The concave effect in the layer boundaries is due to the surface tension on the filament in the rubbery state.Figures 57. Although the casting process is performed in vacuum (− 1 bar), due to the high filling rates, residual gas in the casting chamber may become entrained in the mold. This residual gas is not dissolved in the melt and cannot escape due to the low permeability of the plaster mold, and so gets entrapped in the horizontal ribs between two fronts of opposite melt flow. The surface tension and the pressure that is generated by the compression of this entrapped gas is attested to by the quasi-spherical shape of these defects. It is suggested that these defects could be minimized by improving the vacuum. This kind of defect is present in ~ 12% of the horizontal ribs.Figure ● ~ 0.0127 mm4 and I○ ~ 0.0116–0.0125 mm4). It is known that the main deformation mechanism in these cellular lattices is due to strut bending81. Due to the rare occurrence of this defect  and the low impact in the moment of area of these ribs, it is not expected that these defects will significantly affect the static mechanical properties. It should be noted however that near-spherical voids may generate stress concentrations in their vicinity and, thus, could influence fatigue properties.The modeling of these defects as spherical inclusions in a cylindrical beam suggests that they generate a 1.6% to 8.6% reduction in the moment of area of the ribs  analysis and energy-dispersive X-ray spectroscopy  on deeply-etched samples  step. Even more accurate lattice structures could be obtained with higher resolution stepper motors and better control of the PLA extrusion process. The second (casting) step is associated with only small volumetric deviations due to phase transitions and shrinkage during solidification;Mesoscale characterization of the intermediate PLA pattern and the final A356 casting shows that staircase defects are introduced by the FFF process. Fine porosity (~ 3 ± 1 µm) is found to homogeneously distributed in the casting in both vertical struts and horizontal ribs due to undissolved gas in the melt. However, larger (~ 26 ± 15 µm) defects may be observed in ~ 12% of horizontal ribs arising from the meeting of two melt fronts. Due to the low permeability of the plaster mold, it is suggested that this defect could be addressed by increasing the vacuum pressure;2Si and the evidence of β-phase, the only observable intermetallic compound that was originated by π- to β-phase transition;The microstructure of the cast samples shows grains with both globular/dendritic morphologies. The grain size (73 ± 39 μm) does not significantly change in the different areas of the periodic cells, suggesting that there is no point variation or anisotropy. The subsequent heat treatment is able to refine, agglomerate and spheroidize the eutectic Si. This is proved by the absence of MgThis study describes the characterization of lattice structures formed by a novel fused filament fabrication assisted investment casting technique at the macro-, meso- and microstructural scales. The process involves a two-step protocol, namely the 3D printing of a sacrificial PLA pattern (Step I) that is then used to fabricate the mold for the subsequent casting step (Step II). The following conclusions can be drawn:The dimensional fidelity could be increased further by improvements to the fused filament process for pattern manufacture. More broadly the macro-, meso- and macrostructural evidence suggest that the hybrid additive manufacturing assisted investment casting approach could be applied to other light alloys to fabricate fine periodic lattice structures.h = 4 mm) and eight oblique struts (l = 2 mm) with a circular cross-section (d = 0.6 mm). Individual periodic cells were assembled by connecting their common ribs/struts in a 9 × 9x8 array configuration with plates on the top and bottom to enclose the lattice core.A cellular lattice Fig.  was desiInitially  which hardens the plaster and burns off the enclosed pattern. Meanwhile, A356 ingot was cut into 24 g loads, cleaned and degreased. The alloy was inserted in a SiC crucible with the addition of master alloys (0.05 g Al5Ti1B and 0.07 g Al10Sr) to promote grain refinement and modification of the eutectic Si. After melting in an Indutherm MC15 + induction furnace , the melt was maintained at a temperature of 700 ± 2 °C for 3 min in vacuum (− 1 bar) and magnetic stirring to homogenize the A356 and master alloys. The melt was then cast into the preheated gypsum cylindrical mold . Upon removing the cast the samples were subjected to a T6-treatment The macrostructural characterization of the PLA pattern and final Al lattices was performed by 3D X-ray μCT using a Zeiss Versa XRM-520 μCT scanner . Imaging was controlled by an XRM scout-and-scan system , using the parameters described in Table Mesoscale characterization was also performed by µCT, however, the parameters were adjusted Table  to focus87.μCT scanning data was reconstructed using the XRM software, while segmentation and 3D visualization was assembled in Avizo Standard . The dimensional measurements of the sample strut/ribs were performed on the original 2D TIFF micrographs using FijiMicrostructural analysis was performed by optical microscopy (Leica DM2500M) to evaluate the microstructural characteristics, morphology of the α-Al grains and secondary phases. Micrographs were taken from 27 cells (in a 9 × 9 matrix configuration) focusing on three distinct regions  for each analyzed sample, while a total of five samples were analyzed. Fiji software was used to quantify the grain diameter. Measurements were carried out according to ASTM E112 Standard on samples that were previously polished with SiC abrasives down to 11 μm granulometry and finished using 1 μm diamond solution. Avizo Standard was also used to threshold and separate objects in these images to highlight the sizes and shapes of α-Al grains and secondary phases, which were highlighted with different colors.Deeply etched samples (Keller’s solution—30 s) were observed by SEM (FEI Nova 200) as well as by energy dispersive x-ray spectroscopy (EDS) to characterize and identify the intermetallic compounds (IMCs).


The material properties of tissues and their mechanical state is an important factor in development, disease, regenerative medicine and tissue engineering. Here we describe a microrheological measurement technique utilizing aggregates of microinjected ferromagnetic nickel particles to probe the viscoelastic properties of embryonic tissues. Quail embryos were cultured in a plastic incubator chamber located at the center of two pairs of crossed electromagnets. We found a pronounced viscoelastic behavior within the ECM-rich region separating the mesoderm and endoderm in Hamburger Hamilton stage 10 quail embryos, consistent with a Zener  model. The viscoelastic response is about 45% of the total response, with a characteristic relaxation time of 1.3 s. Tissues are physical bodies, thus their formation necessarily involves controlled generation and relaxation of mechanical stresses  became recently possible to obtain during development  wrapped around with multiple layers of magnet wire .For magnetic microrheology we have custom built electromagnets  using 5 Tmagnetic of the magnetic field B0 acting on a particle with magnetization m isTelastic resisting the rotation of the particle in the x-y plane isE/[2(1 + ν)] is the shear modulus, f = πℓ3/[3ln(ℓ/4r)] is a geometric factor and ϕ0 denotes the particle's direction in the absence of external forces or fields |≫|cos(θ−ϕ0)Δϕ|, thus Tmagnetic remains a constant during small deformations. Under such conditions, the solutions of Equation (4) are:A = Tmagnetic/(μ2f) and the characteristic relaxation time isTmagnetic in the Kelvin-Voigt unit, henceIn the Kelvin-representation of the standard linear solid (SLS), an elastic and a Kelvin-Voigt material are in series: the short term response is hence elastic, followed by a slower viscoelastic relaxation to a new elastic equilibrium. In this approximation the rotation of the material Δϕ = ϕ−ϕFertile wild type quail (Coturnix coturnix japonica) eggs  were incubated for varying periods of time (from 20 to 36 h) at 37°C to reach Hamburger and Hamilton (HH) stage 4  were directly conjugated to AlexaFluor 488, 555, or 647 (Molecular Probes) according to the manufacturer's instructions  equipped with epifluorescence illumination and a Planapo 2.0x objective. The imaging system recorded 1,392 × 1,040 pixel images at a rate of 15.44 frames/s and at a resolution of 0.4 μm /pixel.h is the resolution of the optical flow-derived grid.To characterize tissue deformation, we first apply our non-invasive, optical flow-based method described in Czirok et al.  for eachTo facilitate microrheology measurements in live embryos, we built a plastic incubator chamber surrounded by two, orthogonal pairs of electromagnets . The plaThe magnetic field within the incubator chamber could be gradually adjusted up to a value of 30 mT by setting the voltage across the electromagnets . The appTo measure the material properties of embryonic tissues, we microinjected ferromagnetic nanorods into HH stage 4 quail embryos. In the confined space of the injector capillary, the particles formed aggregates, which incorporated into the tissue, and were detectable by transmitted light microscopy for the entire length of ex ovo development . The aggMicrorheological recordings were performed in HH10 embryos—by which time the injury associated with microinjection completely healed. As high framerate transmitted light live imaging reveals, alternating magnetic fields readily induce rotation of the embedded aggregates, accompanied by a profound deformation of the surrounding tissue microenvironment . The defu). The time-dependent spatial average of u indicates a gradually increasing baseline, upon which the magnetic field-induced changes are superimposed  − ϕ∞| indeed validates the presence of a slow, exponential relaxation with a characteristic time of 1.3 ± 0.2 s (n = 4) we calculated μ2/μ1 = 0.45 ± 0.1 and found that the ratio of the viscoelastic and pure elastic response is 45:55%.While we do not know the net magnetic moment of the aggregates, the temporal behavior of tissue rotation allows the characterization of the local viscoelastic response of the tissue using Equations (7) and (8). As  ± 0.2 s . The pre ± 0.2 s , represe ± 0.2 s  inset. BCompression of cell aggregates yielded the first insight into the viscoelastic properties of cell assemblies  inside the embryo. This could be potentially achieved with the same method presented here, but using magnetic beads where magnetization can be determined and small enough to inject. Further studies can take this direction to explore additional local internal tissue properties.Since cantilever beam probing encompasses a larger area, a more local measurement would be useful to determine local material parameters (The importance of tissue material properties on stem cell differentiation (Charrier et al., The datasets generated for this study are available on request to the corresponding author.ZA, SG, PD, and AC designed experiments and the microrheological instrument. PD provided nanorods and designed the calibration experiment. ZA, SG, and EK performed the calibration. EK and SR injected quail embryos and performed measurements. ZA, DI, and AC analyzed data and wrote 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.


Geomagnetic fields interfere with the accumulation of iron in the human brain. Magnetic sensing of the human brain provides compelling evidence of new electric mechanisms in human brains and may interfere with the evolution of neurodegenerative diseases. We revealed that the human brain may have a unique susceptibility to conduct electric currents as feedback of magnetic dipole fluctuation in superparamagnetic grains. These grains accumulate and grow with brain aging. The electric feedback creates an electronic noise background that depends on geomagnetic field intensity and may compromise functional stability of the human brain, while induced currents are spontaneously generated near superparamagnetic grains. Grain growth due to an increase of iron mobility resulted in magnetic remanence enhancement during the final years of the studied brains. Another study alerted that some of the magnetite/maghemite particles can be of external origin, coming from the polluted environment2. Here we focus on single domain magnetic state effect in the human brain tissue. We present room temperature, induced and remanent magnetization measurements on samples from two brains affected by neurodegenerative diseases, Alzheimer with Parkinson (B01) and Alzheimer (B02) and compared them with the brain (B03) with not known neurodegenerative disease and with the brain of the child before it was born (17 weeks—morbus Patau). We discovered that while B01 had significantly larger remanent magnetization than B02, the induced magnetization of B01 was significantly lower than B02. Both brains had significantly larger magnetic remanence compared with normal brain and the brain of the unborn child.While the human brain contains magnetite mineralization, it has not been established if magnetism of these grains has any potential influence on the development of neurodegenerative diseases. In this work we project a new magnetic mechanism of the brain activity. The success of treatment in the above studies may relate to the presence of magnetic nanoparticles (MNPs) in the brain. The presence of the magnetic minerals in human brain has been reported decades agoThe human postmortem brains were obtained at Institute of Forensic Medicine and Toxicology and Institute of Pathology 1st Faculty of Medicine, Charles University and General Teaching Hospital between 2019 and 2020 in Prague. They were donated for examination and scientific research without time limit, in accordance with relevant guidelines and regulations in the Czech Republic. Under the laws in the Czech Republic, informed consent is not required for the collection of biological material collected during an autopsy that is anonymized and used for scientific or educational purposes. The use of these brains for scientific research was approved by the Ethical Board of the Charles University, Faculty of Science (24.4. 2020).Brain B01 was from 79 years old male  with Alzheimer and Parkinson disease. Brain B02 was from 80 years old female with Alzheimer disease . Brain B03 is from 60 to 70 years old female without neurodegenerative disease . Brain B04 was from unborn (17 weeks of pregnancy) female fetus. The removal of the brain specimens from the skull followed standard procedures. Opening of the cranial cavity was done with a saw and then was used stainless steel autopsy knife to cut off the cranial nerves and tentorium cerebelli. Spinal cord was interrupted under the brain stem to remove the brain from skull. For removing brain of the female fetus were used stainless steel scalpel and scissors. The brains were fixed in 10% formaldehyde for more than 30 days.3 cubes,  and left (L) hemisphere. Then each hemisphere was sliced into horizontal, 4–6 cuts. The top cut was marked as F0, and the following cuts, from the top down, as F1, F2,….Each slice was divided into two halves, front (F) and back (B). F and B slices were cut into 4–8 cm, Figure . WheneveWe used superconducting magnetometer made by 2G company with horizontal sample translation, located in Pruhonice laboratory, Geological Institute, Czech Academy of Sciences. Brains samples were placed into the plastic cups and measured. Once measured we removed the sample on the porcelain plate from the plastic cup and measured the empty holder with empty plastic cup. The values of the plastic cups with holder were subtracted from the magnetic measurements. The remanent magnetization of each specimen was first measured in its initial  state . After the NRM value was established, the specimen was placed inside the pulse magnetizer  with the coil exposing the sample with the magnetic pulse of 1.3 T for a few seconds. Specimen was returned to the plastic holder and its magnetic remanence was measured again in their magnetically saturated state ; 1–2 min elapsed between SIRM acquisition and remanence measurement. Few samples had their NRM and SIRM demagnetized in steps with alternating demagnetizing field up to 20 mT (this procedure is standard part of the 2G superconducting instrument).All collected brain samples were measured for magnetic susceptibility using magnetic susceptibility meter SM30 (Z. Hulka Inc.). It applies the AC frequency of 8000 Hz and generates field of amplitude of 40 A/m.Ten samples were freeze dried inside the vacuum chamber. Freeze drying was performed in order to reduce the volume of the brain tissue so we can get measurement of frequency dependent magnetic susceptibility. Samples were measured at frequencies 4000 Hz and 8000 Hz and field of 320 A/m inside 30 ml plastic holder by instrument of SM100 (Z. Hulka Inc.).While X-ray fluorescent analysis may be far from quantitative, we used X-ray Fluorescence (XRF) analyses (Vanta VMR by Olympus) and measured from each of the adult brain 12 randomly picked samples for measurement of major element concentration using a Geochem mode. For the unborn brain B04 we obtained for each hemisphere two chemical analyses. The instrument was used to detect the following elements along with the detection limits (ppm) in parentheses: Mg (~ 900), Al (~ 100), Si (~ 30), P (~ 20), S ~ 15), K (~ 13), Ca (~ 8), Ti (~ 4000), V (~ 12), Cr (~ 7), Mn (~ 4),Fe (~ 4), Co (~ 3), Ni (~ 2), Cu (~ 7), Zn (~ 2), Ga (~ 200), As (~ 2), Se (~ 3), Rb (~ 0.5), Sr (~ 0.5), Y (~ 2), Zr (~ 0.5), Nb (~ 2), Mo (~ 2), Ag (~ 21), Cd (~ 5), Sn (~ 5), Sb (~ 7), I (~ 40), Ba (~ 280), La (~ 450), Ce (~ 450), Pr (~ 650), Nd (~ 850), Ta (~ 250), W (~ 5), Pt (~ 65), Au (~ 2), Hg (~ 3), Pb (~ 2), Bi (~ 7), Th (~ 2), U (~ 2), and LE (~ 900). LE is the sum of the elements that are lighter than Mg. For this research we discuss only relative amounts of Fe.Significance: Electromagnetic control of the electric noise in the human brain. Localized magnetic heating by resonance. Remote control of human brain activity. Prospects of neurodegenerative disease treatment.3. However, a significant advancement in magnetic resonance imaging (MRI) was established due to realization that iron concentration can be imaged by utilizing two different MRI fields on the same human subject and this gave a way to an establishment of a quantitative susceptibility mapping (QSM)9. In other words, this advancement means a realization that human brain contains nanosized magnetic compounds, including magnetic oxides with magnetization susceptible to the applied magnetic fields1. Dimensions of these grains are on the orders of nanometers and at the human body temperature are in so called superparamagnetic single domain state that is characterized with an enhanced magnetic susceptibility to the external field that, for magnetic iron oxides, ranges between few nanotesla to 10 s of militesla10. Above the militesla magnetic field range the magnetic susceptibility of magnetic oxides decreases by orders of magnitude10, however magnetic compounds like ferritin have paramagnetic susceptibility exceeding several Tesla range and this allowed detection of paramagnetic concentration changes when applied magnetic fields > 1 T commonly used in MRI instruments. Therefore, QSM allows detection of primarily paramagnetic (e.g. ferritin-like compounds) concentrations when applying magnetic fields exceeding 0.1 T. This is because magnetic oxides  are all saturated at fields > 0.1 T and contribute very little to the overall difference in magnetization11.Despite a tremendous research effort in universities and pharmacy, effective treatment of neurodegenerative diseases (ND) is lacking12. Specifically, transcranial magnetic stimulation (TMS) on motor cortex13 delivers an alternating electric current through a coiled wire loop above the scalp. The coil, due to Ampere’s law, creates a magnetic field changes across the skull, and induces an electric currents in the brain regions due to Faraday’s law14.Additionally to QSM, the experiments with application of external alternating magnetic fields on human brains showed better performance on psychiatric tests15. These formations are associated with increased iron deposits, together with changes in the regulation of iron storage in the association in neurodegenerative diseases, including AD17. So far, the antibodies aiming to modify these compounds have failed to improve cognition in clinical trials3. Iron is essential for normal neural function. This is because iron activates biological processes responsible for specific architecture and maintenance of neural network. Iron participates during DNA synthesis and enzymatic processes. Iron is required for fundamental brain processes that include myelination and neurotransmission. Specifically, iron is a cofactor of the iron-containing tyrosine hydroxylase that catalyzes the hydroxylation of tyrosine to form dihydroxyphenylalanine (DOPA), the precursor of dopamine, adrenaline, and noradrenaline (catecholamine neurotransmitters). Brain iron levels generally increase with the aging brain18 and show a dramatic localized increase in their brain iron content in patients with AD or Parkinson’s disease (PD)17. While the reason for iron accumulation in the brain in these disorders is unknown, it correlates with the production of reactive oxygen species (ROS) and oxidative damage that hallmark these disorders19.Alzheimer disease (AD) is characterized by both deposition of senile plaques made of ß-amyloid proteins (A beta) and by hyperphosphorylation of tau proteins2+) and ferric (Fe3+) iron seems to disrupt iron-related functions via the ROS production that often relates to the Fenton and/or Fenton-like reaction22. Divalent Fe2+ promotes the catalytic decomposition of hydrogen peroxide to highly cytotoxic hydroxyl radical (·OH) and trivalent form of iron Fe3+. Then, Fe2+ plays a role in the transformation reaction of H2O2 and superoxide to ·OH23. The ratio of Fe2+:Fe3+ in the brain of Parkinson's patients appears to be 1:3 in comparison to 1:1 in control brains25. Furthermore, in severely damaged brains of PD patients, substantia nigra contained significantly increased total Fe and Fe3+27. Oxidative stress acts via the biomolecule oxidation in the areas of the brain expressing neurodegenerative disorders of both AD and PD29.Ionic imbalance between the ferrous  residing in a superparamagnetic state2.Increased localized concentration of iron goes well with post-mortem analyses of amyloid plaques2/kg, and the SR values from 8.36e−9 to 1.01e−6 Am2/kg. The level of the natural remanent magnetization (NRM) of the brain tissues in Fig. 2/kg) to more that order of magnitude above this noise level. In Fig. 2/kg, B02 from 2.88e−9 to 8.15e−8 Am2/kg, B03 from 6.75e−9 to 2.21e−7 Am2/kg, and B04 , SR values distribute slightly over two orders of magnitude  from 2.39e−8 to 2.87e−8 Am2/kg). Histograms of SR values  and an induced magnetization (expressed by magnetic susceptibility X). We discarded any brain samples that weighted less than 4 g. Measurements revealed an existence of MNPs in the brain capable of holding stable magnetic remanence. This is illustrated in Fig. 3/kg. The susceptibility frequency distribution had the maximum near − 1.3e−8 m3/kg for B01, followed by maximum near − 1.05e−8 m3/kg for B04, then maximum near − 9.5e−8 m3/kg for B02 and then maximum near − 8.0e−9 for B03. Specifically, the magnetic susceptibility ranged between − 1.50e−8 and − 8.12e−9 m3/kg for B01, between − 1.13e−8 and − 6.18e−9 for B02, between − 9.33e−9 and − 6.48e−9 for B03 and between − 1.23e−8 and − 9.02e−9 for B04.Figure Since magnetic susceptibility is often driven by concentration of iron, we compared X values and its error distribution with the XRF detected concentration of iron Figure B and shoDemagnetization of brain samples’ NRM with alternating field up to 40 mT showed no significant decrease in magnetic remanence Fig. . This suMagnetic nanoparticles in the brain can have either homogeneous distribution, or they may be in clusters of particles. Detection of magnetic nanoparticles interaction relates to how easily samples are magnetized and demagnetized. This analysis is shown in Fig. 2. This is evidenced not only by 5–6-min rapid magnetization decay by 0.5% , main iron transport glycoprotein in the central nervous system (CNS)33. Tf has ferric iron binding sites where these ions get engulfed into cells via Tf receptor-1 (TfR-1) using endocytosis34. Ferric ions inside the neurons get to be reduced to ferrous and get into the cytosol via divalent metal transporter-1 (DMT-1). The concentration of iron ions in neurons is kept in balance by iron regulatory proteins (IRP) as a feedback from activity of TfR-1 and DMT-1  that forms a 26–30 nucleotides loop structure that commonly occurs in 3′ or 5′ untranslated regions (3′-UTR or 5′-UTR) of eukaryotic mRNA that is responsible for balancing translational iron dependency21. There is another iron transporter in neural cells, transferrin receptor-2 (TfR-2) that has missing IRE and is more prevalent in the mitochondria of neural cells36. While mitochondrial dysfunction was observed hand in hand with elevated Tf and TfR-2 levels, it suggests an oxidative stress promoted by iron redox chemistry36. Intracellular iron is also balanced by translation of ferritin, the most significant iron storage protein in the 5′-UTR of Tf mRNA37, and neuromelanin38. Both ferritin and neuromelanin has been observed to contain dense iron cores39, which may allow for mineralization of magnetic iron oxides observed here  of uncertain function generates Ab41. A functional IRE stem loop has sequence homology to the IREs for ferritin and TFR mRNA in the 5′ UTR of APP41. Such APP translation would be sensitive to free iron levels in cytoplasma. In addition, APP translation also controls the way how iron regulatory proteins bind to TFR mRNA and ferritin itself42. With high cellular iron levels, translation of AD ß-amyloid protein precursor and the iron-storage protein ferritin would increase41, while RNA for the iron importer TFR would degrade. Our data in Fig. 44.Note that in AD, Zn2+ accumulates with ß-amyloid (Ab) in extracellular plaques, hallmark for AD11.Data in Figure B when a magnetic mineral grows in an applied field H0. The ratio of CRM Mcr of a single domain (SD) grain of volume V that is characterized by a saturation magnetization Ms at blocking temperature TB and coercive force HC is the same as theory for thermoremanent magnetization (Néel 1949) only by using Mcr instead of thermoremanent magnetization (Mtr).k is the Boltzmann’s constant. From the Néel’s (1949) theory, we have the relationship that describes the timescale τ by which magnetic remanence is acquired at the blocking temperature for specific volume V .0 is a characteristic timescale of thermal oscillations, which is approximately 10−9 s. For laboratory experiments where we record magnetic remanence τ is generally on the order of 100 s or more, which gives ln(τ/τ0)≃25. Due to the logarithmic dependence on time, ln(τ/τ0) is relatively insensitive to the time scale of magnetization acquisition. Solving for Ms in the above equation and inserting into Eq.  is recorded at the blocking volume Vion Néel 949 only cr of individual grains is equal that of Mrs, and we can simplify this equation toFor superparamagnetic cases the natural remanent magnetization MThis approximately satisfies  for all Then for the time scales of electric currents c(VB) in (Result in  suggestsc(VB) in ) of magn45. Taking 20 mT magnetic field from this range changing its direction with the frequency determined by the size of the magnetic grain allows estimation of the electric currents generated within the brain tissue by these magnetic grains. Because the frequency of the synapses’ electrical signatures is between 0.1 and 500 Hz46 we take frequency of 10 Hz from this range of frequencies, like we did in . Presence of magnetic particles in the brain represents a hotspot for generation of an alternating currents near the MNPs that may be near synapses. For Faraday’s law we haveMagnetization of magnetite particles creates space around them where magnetic field decays exponentially from 200 to 2 mTe did in . Human b49.Note that because the MNPs are within a conducting medium, the generation of current would resist the magnetic moment fluctuation. In reality this would decrease the frequencies of small superparamagnetic grains and create potential for magnetic tunneling32. The exact MNPs location in terms of the cellular neural function is not known. When MNPs are small, induced currents from fluctuating magnetic dipoles distribute in only small volumes and the frequency of these currents (> 500 Hz) is outside the frequency of neural tissue50. However, as the MNPs grow, their increased fluctuating magnetic moments and decreased frequency, generate microcurrents that start matching the frequency of neural connection between 1 and 500 Hz50. Such interference may result in neural connection malfunction and may contribute to the disruption of the iron pathways32. This is because the accumulation of the MNPs often collocates with places of the neurotransmitters17.Iron regulatory proteins, ferritin, and neuromelanin, all serve for an iron storage. Evidence of biomineralization of MNPs in the brain is likely due to disruption of the iron pathways, perhaps due to free zinc presence52. Magnetic properties detected by SQUID magnetometer attributed the magnetic signature to the presence of magnetic iron oxides52. Hysteresis properties allow an estimation of a concentration of single domain magnetic grains per mass. Figure 2/kg. Given that single domain size for magnetite/maghemite is 100 nm53 and that magnetite/maghemite have saturation magnetization constants 93.2 and 77.6 Am2/kg, respectively we use average value 85 Am2/kg. Saturation remanence of SD grains is about 1/2 of saturation magnetization, leaving 47.5 Am2/kg compared with measured 1.8 to 3.7 e−7 Am2/kg ~ 2.7 e−7 Am2/kg gives concentration 5.8 ng/g. Comparison with concentration of 1000 s of nanograms per gram reported in AD tissues from hysteresis measurements54 indicates that only 0.5% of the magnetic iron was capable of carrying magnetic remanence in B01. This leaves the rest of the iron being in superparamagnetic state with their magnetic vectors fluctuating with high frequencies that decrease with increasing size49.Hysteresis loop on brain samples showed that ND contains single domain grains apart from superparamagnetic grains46. There are variations in electric activity spectra where some peak location (e.g. around 10 Hz) seems to be relevant for dementia and AD50.The electric activity of the brain ranges between 0.1 and 500 Hz2, for which the grain sizes are such that they do not interfere with the brain frequencies of < 500 Hz, and their concentration increase result in increase of magnetic susceptibility. Such magnetic grains have sizes of less than 40 nm11. Magnetic moments fluctuate in broad spectrum of frequencies, ranging from over nine orders of magnitude, from high (109 Hz) down to units of Hz. Our measurements showed that the brain with ND is associated with not only an increased iron concentration, but also biomineralization of nano-sized magnetic iron oxides and growth into their single domain magnetic state. These iron oxides likely nucleated from the solid iron cores that have been observed inside ferritin and neuromelanin39. Magnetic iron oxides serve as a new source of high frequency electric currents inside the neuron structures. Our analyses showed that the ND brains have increased volume of these magnetic oxides that not only slows down the frequency down to frequencies of neural transmissions (10 Hz) but also increase the volume of the neural tissue that would be affected by magnetic nano-oxides’ eddy currents. Evidence of this new electric source stems from detection of magnetic grain remanence indicating the presence of magnetic grains that already exceeded 100 nm grain size. Once the grains grow into the single domain magnetic state, their mass normalized magnetic susceptibility decreases and this is what we have detected 56. Magnetic susceptibility has become relevant to the study of aging57 and ND due to high contrast in QSM using magnetic resonance imaging (MRI)59. While QSM focused on monitoring the spatial distribution and the temporal dynamics of iron deposition to gain insight of our understanding of ND pathogenesis15, it could not resolve if the iron accumulation is the cause or the effect61, despite, for example, superior AD identification compared to MRI analyses with gray matter volume changes61.This newly identified potential mechanism of iron interference with the neural functions does not uniquely single out that iron accumulation is the cause of ND but it strongly supports it. Such novel mechanism suggests that iron accumulation in human brain is the cause of magnetically stimulated neurodegenerative disease rather than a consequence of it, answering the question that was focus of multiple studies that used quantitative iron levels22 or potential iron disappearance15. Such iron concentration changes, in terms of their grain sizes, could constrain novel reasoning, why there is a general disagreement between the brain iron concentration and gray vs white matter, that is currently attributed to an increase in myelin content rather than concentration of iron6. While iron accumulation might constitute ideal proliferation and perpetuation environments for ß-amyloid aggregation and neurotoxicity63, our data support that both iron accumulation and reduction may lead to a significant increase in magnetic particle size, generating the electric currents that may interfere with the normal neural functions.If iron homeostasis is significantly disrupted, it may lead either to iron accumulationWe show that a nano-mineralization of magnetic grains in human brains corelates with the progression of neurodegenerative diseases. Magnetic nanoparticles contain oscillating magnetization that in conducting brain tissue generates electric currents that may interfere with the synapses function in the brain. The progress of mineralization appears to be significantly enhanced in brains with neurodegenerative disease (ND). This observation proposes a new phenomenon that may interfere with the normal brain processes. Due to nanosized volume, magnetic moment oscillates within the MNPs with frequency up to 1e9 Hz. Microcurrents generated this way interfere with the brain cellular functions. As the iron in the brain migrates, perhaps due to Zinc interrupting the iron pathways, the MNPs volume increases from the nuclei made from ferritin and neuromelanin precursors. This increase in iron oxides’ volume broadens the frequency of induced electric currents (IECs) from gigahertz down to sub-hertz frequencies. When frequency of IECs matches the frequency of electric currents of synapses, the two currents may interfere via resonance and this may contribute to neural malfunction that contributes to the form of neurodegenerative disease (ND).Our data revealed a new phenomenon that explains why there can be both lower and higher magnetic susceptibility in brains with ND. While most of the magnetic grains that grow in the brain would be superparamagnetic in early onset of ND and the susceptibility increases with this progression, when the grains grow into the single domain magnetic states the susceptibility gets lower.We postulated a new mechanism for electric interference of MNPs with the neural synapsis function. Theoretical consideration of blocking the remanence direction fluctuating in the brain during the MNPs growth identified that magnetic coercivity of MNPs are sensitive to geomagnetic field magnitude.Supplementary Information


Metal-ion batteries are key enablers in today’s transition from fossil fuels to renewable energy for a better planet with ingeniously designed materials being the technology driver. A central question remains how to wisely manipulate atoms to build attractive structural frameworks of better electrodes and electrolytes for the next generation of batteries. This review explains the underlying chemical principles and discusses progresses made in the rational design of electrodes/solid electrolytes by thoroughly exploiting the interplay between composition, crystal structure and electrochemical properties. We highlight the crucial role of advanced diffraction, imaging and spectroscopic characterization techniques coupled with solid state chemistry approaches for improving functionality of battery materials opening emergent directions for further studies. The development of high performing metal-ion batteries require guidelines to build improved electrodes and electrolytes. Here, the authors review the current state-of-the-art in the rational design of battery materials by exploiting the interplay between composition, crystal structure and electrochemical properties. Yet, the vast number of compositions potentially available from the Periodic Table poses an overwhelming challenge for the materials science community to find new battery electrodes. Obviously, researchers desperately need solid guidelines while searching through this huge parameter space for the best chemical combinations and structures. Solid state chemistry is the art of building the desired atomic arrangements based on information hidden in the Periodic Table. Over the decades, this research field has evolved from the trial and error Edison’s approach to become a fully-fledged science delivering an unprecedented control over material’s structure and properties. This allowed building predictive models and conferring specific functional properties to a material, with an extra degree of freedom offered by defects in solids, structure dimensionality, and nanosizing. Nowadays, the context of research is displaced towards accelerated materials discovery and novel eco-compatible processes together with engineering advances for device fabrication and prototyping. Thus, solid state chemistry is still expanding pursuing our demands of understanding matter and transforming it to useful solids for emerging technologies.Invention of new functional materials is vital for the advancement in technologies that will move society towards high global standards of living. Electrode materials have played a crucial role in the development of highly performing Li-ion batteries, as was recognized by the 2019 Nobel Prize recompensing solid-state chemists for their decisive impact+ into the host electrode material with a concomitant addition/removal of electrons. In light of this ion-electron duality, it pertains to design an inorganic framework with the proper crystal and electronic structure to reversibly accept and release ions and electrons. This is the favored playground for solid-state chemists willing to better predict and improve battery functionality, as picturized in Fig. −1 or Wh l−1) is defined as the product of the operating potential (V) and the capacity (Ah kg−1 or Ah l−1), both related to the crystal and electronic structure. Extraction of one A+ alkali cation is accompanied by loss of one electron which produces both a negatively-charged cationic vacancy and a positively-charged electronic hole in the M–L framework . Generating holes upon battery charge should be considered in the band structure context, but for a chemist it is tempting to link these holes to specific redox centers. Although strongly simplified, this concept enables solid-state chemists to rationalize the electrochemical behavior of electroactive materials on the basis of crystal chemistry, molecular orbitals, ionocovalency, bond valence approach, thermodynamics, and defect chemistry considerations, which provide insights into the electrochemical and thermal stability, charge/discharge mechanisms, structural phase transitions, oxygen evolution, cationic migration and origins of kinetic hindrances.Within the metal-ion battery technology the electrode reactions are based on reversible insertion/deinsertion of the alkali  cations A3. Great hopes have been placed in the predictive capabilities of the high-throughput materials genome initiative, being nowadays empowered with artificial intelligence (AI)4. The materials genome approach relies on computational electronic structure methods5 while AI is based on mining, manipulating and reasoning from what is now called Big Data and building artificial neural networks to deduce regularities6. So, should our write-up stop here in case of looking old-fashioned? Certainly not. The material-oriented research is still largely driven by simple ideas, hence importance of conceptual models and generalizations. This is what this paper tries to illustrate and discuss as personally perceived.A legitimate question, however, regards the best way to combine such a chemist’s approach with the spectacular advances in characterization techniques and computational methods so as to be more prolific in identifying practical electrode materials. The design of battery materials has benefited from tremendous progress in computational techniques  and molecular dynamics (MD)) which greatly contributed to interlinking the “Atoms & Ions” and “Crystal Structure” sectors in Fig. nd orbitals and L n′p orbitals, as presented in Box U/2) term, where Δ and U are the charge transfer and d-d Coulomb interaction energies, respectively +/Mk+ redox couple, in which the relative energy of the (M–O)* band with respect to the 1s band in metallic Li governs the electrode redox potential (Box p-like states (Box p)NB orbitals delivering extra electrons on top of those given by the cationic M(k+1)+/Mk+ redox center and, hence, extra capacity. The layered oxides Li4/3−xNi2+xMn4+2/3−xCo3+xO2 termed “Li-rich NMCs” demonstrate a high reversible capacity exceeding 250 mA h g–1 that cumulates a cationic redox activity  amounting to ~130 mA h g–1 and an anionic redox activity of ~120 mA h g–1 at potentials above 4.5 V vs. Li+/Li. Pushing the Li removal to its maximum provokes a structural instability of the oxidized oxygen accompanied by the release of O2, concomitantly with other practical difficulties, such as sluggish kinetics, voltage fade and hysteresis7. Curing this problem calls for a fundamental understanding of the Li-driven anionic redox reactions.The redox properties of the insertion materials are best considered in terms of their band structure, which is inherited from the overlapping atomic M vely Box , panel dionic Mk++/Mk+ red2IrO3 the anionic redox leads to π-bonding between Ir 5d and O 2p orbitals at the cost of shortening the Ir-O interatomic distance to <1.8 Å n− dimers with short interatomic distance of ~1.44 Å (similar to that in the true (O–O)2− peroxogroup) bridging two neighboring metal-oxygen octahedra either within the same M–O layer or between the adjacent M–O layers11. These peroxogroups are associated with the cationic migration from the M positions to the vacant Li positions leaving “undercoordinated” oxygens which use their 2p orbitals to bind with each other.In order to stabilize the highly oxidized oxygen species we need to increase their tightness to the lattice, hence calling for exploration of possible bonding mechanisms. Hong et al. suggested that in Sn-doped Li.8 Å Fig., left8. als Fig. , middle.2− with respect to O2−, the sulfur catenation into disulfide (S2)2− groups is more pronounced as realized in TiS3 = Ti4+S2−(S2)2− and FeS2 = Fe2+(S2)2−13. Li insertion is assumed to break the S-S bond resulting in the Li2Ti4+(S2−)3 and Li2Fe2+(S2−)2 intercalated structures. However, the long-believed anionic redox intercalation chemistry related to forming/breaking polysulfide S-S bonds still needs a solid crystallographic confirmation. In a broader context, such redox chemistry is recently demonstrated for the low-temperature insertion of Cu into La2O2S2, Ba2S2F2, LaSe2, BaS2 containing (L2)2−  dimers to obtain the Cu2La2O2S2, Ba2Cu2S2F2, LaCuSe2 and BaCu2S2 phases14. Through this insertion, metallic Cu donates electrons from 3d orbitals to low-lying σ* orbitals of the (L2)2− dimers causing their cleavage. These findings open up a new synthetic strategy worth being explored for designing novel transition metal compounds from precursors containing polyanionic redox centers.In case of the transition metal sulfides, owing to the lower chemical hardness of S2IrO316. This deformation, as deduced by transmission electron microscopy and Rietveld refinements, consists in a trigonal prismatic distortion of the MO6 octahedra that splits the O–O distances into three long and three short (~2.4–2.5 Å) ones  and high temperature (1800 K)20. This suggests that the feasibility of reductive coupling increases with either a spatial extension of the M nd orbitals, or, otherwise, a shortening of the M–O distances by applying external pressure. The effect of pressure can be mimicked with epitaxial strain compression in thin films that is known as a tool to modify physical properties. Thus, finding the right epitaxial relations and lattice mismatch could enable stable and reversible oxygen redox due to the reductive coupling in thin film or even 3D electrodes based on 3d transition metal oxides.Although the anionic redox scenarios enlisting the M–O π-bonding or the O–O covalent bonding look plausible, they still call for an unequivocal proof of the drastic shortening of the M–O bonds or O–O bonds. Instead, the crystallographic data point to a cooperative deformation of the octahedral framework that was theoretically and experimentally confirmed in both α and β-polymorphs of Lines Fig. , right. ely Fig. , right11p)NB orbitals  aligned along the linear Li-O-Li bridges21, but other types of anionic “lone pairs” as electron donors have also been considered in Li-rich layered oxides. This was successfully done in Na-based layered oxides with Mg2+ and Zn2+, which form ionic bonds with oxygen and by the same token can form peroxide compounds 22. In LiFePO4, the “stellar member” of the polyanionic positive electrode materials, oxygens sit in the oxo-centered tetrahedra , within which the tetrahedral oxygens are not even bound to the transition metal; the reasons why they are termed “dangling” or “semilabile” . Although the redox potential is beyond the stability window of the standard carbonate-based electrolytes, recent report on highly fluorinated electrolytes stable up to 5.6 V vs. Li/Li+ might curb this difficulty28. In short, it is not therefore impossible to envisage that the polyanionic redox process could be triggered upon removal of Li, hence justifying further exploration.Although these electrons are believed to be too low in energy, hope must prevail as evidenced by deintercalation of two Liens Fig. , could fp non-bonding states, we are still far from a complete understanding. The main reason is rooted in difficulties of getting precise knowledge on the structure at the end of charge and its evolution during charge-discharge, although the fundamental understanding received from such data is worth the efforts29. The structural complexity of layered oxides  poses serious obstacles for decent crystallographic studies. Moreover, it is intriguing why there is a relatively small number of extended solids having transition metals coordinated by (O–O)2− peroxogroup alike WO2(O2)H2O30 while the panel of materials showing anionic redox activity is rapidly growing? An explanation from a crystal structure and chemical bonding standpoint could really benefit the anionic redox field. Additional insights are also necessary for designing chemical strategies that could help in taking high capacity anionic redox cathodes from the labs into market.One conclusion to be drawn from this brief overview is that, although the general picture of the anionic redox is well established at least with respect to the importance of the O 2Box 1 Molecular orbitals and band theory in application to electrode materialsk+ is octahedrally coordinated with ligands L that results in a schematic band structure deduced from the overlapping atomic M orbitals with L n’p orbitals (panel a), whereas part of the L n′p orbitals are not capable of bonding overlap by symmetry and remain non-bonding (NB). The “orbitals of interest”, i.e. those determining the redox properties, comprise the bonding orbitals with a major L contribution  and anti-bonding eg and t2g orbitals with a major M nd impact . Being placed into a periodic crystal potential, these groups of molecular orbitals give rise to the electronic “bands of interest”, which are the (M–L)* antibonding and (M–L) bonding bands, and the non-bonding (L n’p)NB band (panel b). However, in case of strong electron-electron correlations one needs to consider the band structure in terms of the Zaanen-Sawatzky-Allen theory75. The d-d Coulomb repulsion splits the partially occupied (M–O)* band into empty upper and filled lower Hubbard bands  with an energy separation U that is the energy penalty for dndn → dn+1dn−1 electron transfer between adjacent M sites giving rise to a Mott-Hubbard insulator with the bandgap inside the (M–L)* states (panel c). In case of the large U, the highest-energy filled band is L n′p, and virtual electron transfer occurs between ligand and metal, defined by a charge-transfer (CT) energy Δ, which is the energy cost of moving an electron from ligand and placing it at the M nd orbitals dn→dn+1L (L is the ligand hole). In the Mott-Hubbard regime U < Δ, but if Δ < U, a CT insulator is realized with the bandgap between the UHB and L n’p bands. Δ and U can roughly be traced with the ionic model (panel d)96. Solid-state chemists manipulate these terms by tuning the electron affinity of the M cations that increases with either their electronegativity or with formal oxidation state. Neglecting electron-electron correlations for the sake of simplification, upon Li+ removal and in absence of drastic structural transitions, decreasing the Madelung term results in a decrease and increase in energy of the cationic (M–L)* and anionic L n′p bands, respectively, hence lowering Δ, but the holes still reside in the cationic (M–L)* band . Thus, the redox reaction is mostly cationic with the Mk+ cation acting as the major redox center. For the Mk+ cations with higher electronegativity at the end of the M(k+1)+/Mk+ cationic capacity, the L n’p orbitals are pushed towards the Fermi level equalizing the contributions of the M nd and L n′p states . The holes equally belong to the cationic and anionic sublattices. The increased hybridization of the M nd and L n’p states implies high covalency of the M–L bonding rendering the L ligand a participant of the charge transfer process where holes partially reside at the L n’p states that, however, does not increase the overall number of electrons donated by the cathode, as the overall number of holes remains the same. Partial oxygen oxidation in contrast can lead to capacity advantages, as realized for the rock-salt based complex transition metal compounds, which by specific structural an stoichiometry reasons (L/M ratio >1) involve redox-active non-bonding (L n′p)NB orbitals21. Accordingly, upon Li+ removal, extra capacity is gained from the localized (L n′p)NB anionic states in addition to that coming from the (M–L)* band . In the majority of the insertion compounds for metal-ion batteries a transition metal cation MBox 2 Crystal chemistry rationale behind the operating voltage of metal-ion battery electrodess band. The energy difference between (M–L)* and (M–L) can be expressed as a function of the overlap integral, S2, and electronegativity difference, Δχ, between M and L (panel a). The higher Δχ, the more ionic the M–L bond. This lowers the S2/Δχ and consequently the (M–L)* band such that the redox potential increases.In the general case of M–L (L = ligand) bonding, the electrochemical redox potential is determined by the position of the (M–L)* band that hosts the Fermi level relative to the Li 1nm−  offers another degree of freedom in tuning the electrode potential of electrode material by varying ionocovalency of the M–L bonds by means of “inductive effect” . In terms of the band structure, placing a highly electronegative X cation lowers the energy of (M–L)* antibonding states and Fermi level thus enlarging the energy gap between Fermi level in the cathode and the Li+/Li redox couple (panel b). Further on, the inductive effect is not simply governed by the chemical nature of X: a more accurate prediction of the electrode potential can be made based on the understanding of how the entire coordination environment of the transition metal–ion affects the covalency/ionicity of the M–L bonds including the distances with the nearest neighbors and the contribution of cation–cation electrostatic repulsion97. The increased electrostatic repulsion through shorter cation–cation interactions typically results in enlarging of the M–L bond distances and consequently increases their ionicity leading to a higher potential of the M(k+1)+/Mk+ redox couple.Introducing a complex polyanion group XL4 tetrahedron through ML5 trigonal bipyramid to ML6 octahedron) can render the M–L bond more ionic thus raising the M(k+1)+/Mk+ redox potential. The number of A+ alkali cations nesting in a close proximity to the redox center also affects the M(k+1)+/Mk+ redox potential that is considered as a “secondary” inductive effect (panel c). The A–L bonding increases the ionic character of the M–L bonds through a similar mechanism as to the XLnm− polyanions. In practice, shifting the ionocovalency of the M–L bond through the inductive effect appears a useful tool to tune the redox potentials in quite a broad range. For instance, a cumulative inductive effect of fluoride and phosphate anion species in KTiPO4F allowed for a substantial boost of the Ti4+/Ti3+ redox potential up to 3.6 V vs. K+/K turning it into a prospective cathode despite the well-establish perception of Ti-containing compounds as “only-anode” materials98. At the same time changing the coordination number of the M cation , the number (n) of mobile carriers  and the activation hopping energy (Ea) for the conducting ion. The latter is the sum of the energies to create the defect and to overcome the energy barrier for the ion migration that depends on the local bonding environment and interconnectivity between available sites in the anionic sublattice. Within a simple ionic model, the electrostatic interactions of neighboring ions together with the free structural volume for ion migration can be estimated fairly well beyond time-consuming DFT-based methods. These approaches, briefly summarized in Box 32. The latter provides the network of diffusion channels and large local spaces promoting fast diffusion. The former delivers a tentative estimate of the energy barriers for ion diffusion, ranking materials by the energetics of this space. The polarizability of the anion sublattice can also be accounted for by appropriate modification of the bond valence parameters33. These approaches are typically applied for pre-screening of solid electrolytes and electrode materials being supplemented with simulations of higher accuracy for precise evaluation of the most promising selected examples. As a result, many previously untested compounds with anticipated ion-diffusion properties have been identified as prospective candidates for further investigation not only for the Li-ion conductors, but also for Na-, K-based ones36.Both battery electrodes and Li(Na)-based inorganic electrolytes can be described as an anionic framework in which mobile cations hop between sites through interconnected diffusion channels. Their ionic conductivity (σ), which is a thermally activated process following the Arrhenius law, is governed by the charge  have highly polarizable anionic frameworks adopting a body-centered cubic packing  or multivalent (Mg2+) ions. However, since b.c.c. anion frameworks are less common than the h.c.p. or f.c.c. ones, high ionic conductivity should be limited to a small number of compounds. Gladly, there are a few exceptions to the rules with namely the argyrodite-type Li7PS6 and its halide-substituted derivatives, which show high ionic conductivity while not having a b.c.c. anionic framework but still containing tetrahedral sites for the mobile ions. Such insights open perspective for further exploration among both sulfides and oxides.Trying to identify rules to relate the structure to the ionic conductivity, it has long been recognized that the best ionic conductors  (σRT ~ 10−6 S cm−1) while the HT cubic phase is a good ionic conductor with an extrapolated σRT of ~10−4 S cm−1 due to the high Li disorder43. Quenching together with chemical substitution are the common strategies to stabilize the HT disordered polymorphs at RT. The highest Li ionic conductivity of σRT ~ 1.4 × 10−3 S cm−1 among oxides was achieved for the inherently disordered Ga-substituted cubic Li6.25Ga0.25La3Zr2O12 garnet44 providing the absence of grain boundaries which most frequently negatively affect ionic conductivity. Such boundaries usually originate from crystallites of different orientation in polycrystalline samples and more frequently from minute amounts of surficial phase having either structure, composition or both, different from the grain material.Whatever the underlying structure is, it must be recognized that ionic conductivity can also be enhanced with a configurational or occupational disorder resulting from either vacancies or interstitials. Temperature is another elegant way to introduce the configurational disorder, hence explaining why in numerous solid electrolytes the high-temperature (HT) and highly disordered polymorphs always show best ionic conductivity. An illustrative example is the garnet-type LiEa. Along that line, the replacement of O2− with larger and more polarizable S2− widens the diffusion pathways and improves the conductivity by several orders of magnitude. The research on sulfide-based ionic conductors has recently been accelerated owing to the pioneering work of Kanno et al suggesting highly conducting (1-x)Li4GeS4–xLi3PS4 phases guided by a tendency of increasing ionic conductivity with the number of mobile charge carriers, namely Li vacancies in the Li4−xGe1−xPxS4 solid solutions due to the heterovalent P5+ for Ge4+ substitution45. The actual crystal structure of the Li10GeP2S12 (or Li3.33Ge0.33P0.67S4) phase with the highest ionic conductivity σRT ~ 10−2 S cm−1 is, however, different from the parent Li4GeS4 and Li3PS4 structures46. Further optimization via dual cationic (Si for P) and anionic (Cl for S) substitutions resulted in Li9.54Si1.74P1.44S11.7Cl0.3 with σRT ~ 2 × 10−2 S cm−1 comparable to that in the Li-based liquid electrolytes47. This combination of ligands also provides high ionic conductivities in the argyrodite-type phases Li6PS5X  with the maximum σRT ~ 0.94 × 10−2 S cm−1 for Li5.5PS4.5Cl1.548. Equally, the high temperature β-Li3PS4 polymorph with σRT ~ 10−3 S cm−1 can be synthesized at low temperature (<150 °C) by nano-structuring via wet-chemical synthesis49. However, inherent drawbacks of sulfide-based electrolytes are nested in their limited electrochemical stability which necessitates the use of coatings when placed in contact with oxide positive electrodes, but also in their moisture reactivity which complicates their handling. To alleviate this issue great efforts are placed towards the design of oxysulfides that is a real challenge for solid-state chemists. A viable alternative is provided through revisiting ion transport uncovered back to the 1930’s in LiX  that has led to Li-based ternary halides Li3YX6  with ionic conductivities of 0.07–1.7 × 10−3 S cm−1 after ball milling. Moreover, in terms of practical benefit these ternary halides are stable at high potential as demonstrated with an electrochemically workable (Li3YCl6/LiCoO2) cell without pre-coating of the cathode50.More spacious and polarizable framework is preferable for ionic conduction, as it weakens the Li-anion bonds reducing 51. This migration increases the Li diffusion barriers causing a contraction of the Li layer thickness52. Being only partially reversible, the migration gradually transforms the layered structure to spinel-like or disordered rock-salt like structures raising the cell impedance53. However, even with a high degree of the Li–M disorder, Li-rich rock-salt oxides can still demonstrate measurable Li diffusion if the Li concentration enables the percolated diffusion paths54. The dynamic antisite disorder can equally be induced electrochemically in polyanionic cathode materials possessing the polyanionic groups with “semilabile” oxygen atoms. By extraction of the A+ cations these oxygens experience severe underbonding due to the depleted coordination environment , and also acknowledged in the electrode materials. The LiBox 3. Topology and bond valence approaches to cation diffusion32.Solid-state chemistry methods based on crystal structure analysis can be applied for both electrode and solid electrolyte materials to probe potential ion migration pathways, find intercalation sites, and roughly estimate the activation energy of ion migration within reasonably short time. Among them are purely geometry-topological approaches such as Voronoi–Dirichlet polyhedra (VDP) partition, which deals with crystallographical space, and electrostatics-based methods known as “bond-valence” (BV)a, top) indicate elementary voids and channels sorted by their radii . Only significant voids and channels with sufficiently large Rsd and Rad are suitable for mobile ions. Such downselection results in a continuous system represented by curved 1D pathways for LiFePO4.According to VDP, the crystal space can be split into atoms and voids subspaces. VDPs are built only around so-called “framework” atoms, which remain immobile during ion migration. The vertices and edges of VDP  resulting in a BVS map . The key parameter—BVS mismatch (BVSM)—limits the deviation of all BVS values from the reference . The higher BVSM in a particular area, the lower possibility for a mobile ion to pass through it99. Once the sites with low BVSM percolate, ionic conduction is likely to be possible. An important advantage of BVSM is not only low time cost (panel b), but also easier treatment of non-stoichiometric compounds  by adding corresponding normalizing coefficients to the formula (1). The BVSM values can be translated into energy-related values using a Morse-type interaction potential. Such an approach is called bond valence energy landscape (BVEL)100, which is sometimes referred to as bond-valence site energy. With the BVSM input, the site energy, E(A), can be estimated according to the formula (2), panel a100, where Easym—the energy penalty due to the coordination asymmetry, and Erep—the electrostatic (Coulomb) repulsion, Vid—expected valence of the A atom, D0 and g—empirical coefficients. The BVEL approach might reveal energetically favorable sites for ions or define migration pathways characterized by an activation energy Eact, which can be treated as a migration barrier of a mobile ion. Since BVSM and BVEL deal with a static crystal structure and the relaxation of the surrounding atoms during migration is disregarded, the BVEL migration barrier is generally higher than the experimental one. Nevertheless, substantial literature data for monovalent ions validate a steady correlation between experimental, computational (DFT and MD), and BVEL activation energies. Noteworthy, the solid-state methods also provide a significant gain in time and cost (panel b). In predominantly ionic and covalent compounds, the sum of bond valences (BVS) of a specific ion should be equal to its valence , and can be calculated according the formula (1), panel 58, thus we keep focus at the intercalation materials below.In spite of a tremendous progress in understanding the metal-ion electrochemical systems conveyed in the previous sections, the extreme complexity of electrodes and solid electrolytes still does not allow retrieving full details on the bulk and defect structures and their evolution upon battery life cycle which too often leads to hypotheses on the exact nature of their electrochemical behavior based on incomplete data. Chemists have at hand powerful diffraction and spectroscopic techniques to interrogate the materials locally and in the bulk Fig. , but we 1+xM1−xO2 compile such a complexity by reuniting within the same structure faulted stacking associated with random lateral displacements of the “honeycomb” Li/M ordering  limiting our ability to judge on evolution of the chemical bonding. Being sensitive to average long-range order, XRPD and NPD do not probe short-range correlations, and this gap can be closed with total scattering with a pair distribution function (PDF) analysis, which delivers local information on interatomic distances, coordination numbers and disorder, without presuming periodicity62. Neutron PDF provides a unique capability to reveal 2D ordering of transition metal cations in the layered oxides and 3D clustering in disordered rock-salt oxides that would be difficult to resolve with other methods because of the closeness of atomic numbers of the 3d transition metals63. The local structure can be completed with 6,7Li or 23Na nuclear magnetic resonance (NMR) spectroscopy which demonstrates high sensitivity towards surrounding of alkali cations by transition metals because of the strong dependence of the hyperfine shift on the number and types of the A-O-M interactions with the paramagnetic centers64.X-ray and neutron powder diffraction (XRPD and NPD) that can be done in either ex situ or in situ modes using dedicated electrochemical cells, enables to determine precisely the crystal structures of electrode materials. An important obstacle pertaining to such techniques is severe distortion of the diffraction intensities and profile shapes by planar defects, such as stacking faults and twins. Li-rich layered oxides Liing Fig. , faulted65. Electron diffraction intensities can be collected ex situ from submicron-sized single crystals of the electrode at different SoCs free of conductive additives and binder interference, and used for the crystal structure solution. The relative sensitivity of EDT to lithium compared to that of X-rays scales as ~[Zheavy/3]1/2, where Zheavy is the atomic number of the heaviest element in the structure, hence enabling a ~3 times better Li detection in the structures like LiCoO2 and its derivatives. Thus, Li positions, occupancy factors and antisite disorder can be determined rather precisely26. Moreover, EDT is so far the only single-crystal diffraction method to retrieve the crystal structure quantitatively from in situ experiments inside the electron microscope using an electrochemical cell with liquid electrolyte  demonstrates a number of advantages being applied to the Li-ion battery electrode materialsyte Fig. 66. The a69, surface layer reconstruction in layered oxides51, antisite defects in LiFePO470, O–O dimers formed at anionic redox16, staged Li-vacancy ordering71, and many other local details. However, these techniques require relatively high electron dose to provide images with a reasonable signal-to-noise ratio because the annular detectors used in these methods collect only a small fraction of the electrons interacting with the specimen. Hence, there are risks of creating misleading artefacts for charged cathodes, which are frequently highly instable. Nowadays, a broader availability of fast pixelated or segmented STEM detectors introduced emerging alternative low-dose STEM imaging techniques, such as ptychography and differential phase contrast (DPC). In ptychography, a convergent beam electron diffraction (CBED) pattern is recorded for every scanned point of the specimen with a pixelated electron detector and used for reconstructing an atomic-resolution phase image, which is capable of showing reliably the positions of Li, O and heavier elements even at subpicoampere electron currents72. In contrast, during the integrated differential phase contrast (iDPC-STEM) imaging, the “center of mass” shift of intensity in the CBED pattern at every scanned point is recorded with a 4-quadrant STEM detector. iDPC-STEM retrieves direct phase image of the transmitted electron wave providing a linear dependence of the contrast on the atomic number Z that is more advantageous for visualizing light elements than the strong ~Z2 dependence in the HAADF-STEM imaging73. The DPC images can be recorded at the electron dose at least few orders of magnitude lower than a conventional ABF-STEM image still maintaining a good signal-to-noise ratio. As a proof of concept, Fig. 2 electrode (5% and 60% delithiated). Spectacularly, Li vacancies are clearly visible already at their low concentration, whereas at large delithiation the Li-vacancy ordering is unambiguously detected, and a partial migration of Co to the tetrahedral interstices becomes apparent.A deeper insight into the local structure requires advanced transmission electron microscopy (TEM) imaging. Aberration-corrected high angle annular dark field scanning TEM (HAADF-STEM) and annular bright field STEM (ABF-STEM) have extensively been used to visualize the M cation migration upon the battery cathode cycling74, and availability of the low-dose STEM imaging techniques makes it a perfect tool to study quantitatively the atomic structures of oxidized oxygen species formed due to the anionic redox, clusters of point defects, grain boundaries and interfaces.The low-noise imaging at the low electron dose stands as a serious asset for extracting atomic positions with sub-Å precision through a quantitative image processing with the statistical parameter estimation theory since the highest attainable precision depends on both spatial resolution of the microscope and signal-to-noise ratio of the image. Based on fitting intensity at the atomic columns with Gaussian peaks and retrieving the atomic column positions, this approach has already been applied to a number of materials2)n− species. Hence, a resurge of interest for spectroscopy techniques, from the time of the high-Tc superconductors, to probe ligand’s electronic state as described by the Zaanen-Sawatzky-Allen diagram75. Among them, lab X-ray photoelectron spectroscopy (XPS) has been the most popular with its main drawback of probing solely the material surface (<8 nm). However, XPS provided the first hint of anionic activity by the presence of an extra O signal located at 530.5 eV in the O 1s spectrum of Li-rich layered oxides. Its hastily assignment to the (O2)n−  species became rapidly controversial because its energy position was structure- and charge-independent76. A similar issue occurs with the sulfide compounds showing an anionic redox activity. The same uncertainty remains in hard X-ray photoelectron spectroscopy (HAXPES) which by virtue of a higher energy X-ray beam of ~6.9 keV can increase the inelastic mean free path and therefore the bulk sensitivity up to ~30 nm77. To tackle this issue soft X-ray absorption spectroscopy (soft-XAS) which probes the unoccupied states at the atomic level was brought into the scene for looking at the O K-edge. While such a technique demonstrated great merits for cations, a serious pitfall with the O K-edge XAS interpretation is encountered when correlating the intensity changes in the pre-edge of the spectra with the holes on oxygen sites, because of hybridization between the O 2p and M levels, hence leading to highly controversial results78. Beyond the conventional XAS, resonant inelastic X-ray scattering (RIXS), which probes the excited states promoted by the electric dipole transition, is described as the “Holy Grail” to track the evolution of the M and O redox in Li-rich electrodes upon delithiation. Such a confidence is rooted in the appearance of a specific feature at 523.7 eV emission energy which resonates at 531 eV incident energy79. As for HAXPES results, this feature was almost material-neutral and assigned to the anionic redox. However, no theoretical evidences have allowed to undoubtedly assigning such a feature to the occurrence of exotic O states. Obviously more rigorous implementations of RIXS are being awaited along with an in-depth theoretical support to further elaborate on the nature of the oxidized oxygen species formed during charge and hopefully to bring a corrected trend/picture to this topic.Aside from representing a transformational change in design of high capacity electrode materials, the anionic redox has also modified the characterization landscape calling for new approaches to visualize, besides cations, oxygen atoms and more so to underpin the charge compensation mechanism involving superoxo/peroxo-like  carbonophosphates80, LiMoP2O7 pyrophosphates82, Li9V3(P2O7)3(PO4)2 phosphate-pyrophosphate83 and Li3Cr2(PO4)385. However, considering the complexity of the battery materials, a combination of the solid state chemistry approaches with the computational tools still remains serious assets. Among many other examples, this can be illustrated by recent discoveries of metal-ion battery cathodes triggered by the relatively simple concept of the anionic redox and its crystal chemistry expansions: the Li2O3 69 and Li3IrO486 oxides with the layered and framework structures, the Li-rich disordered xLi3NbO4 – (1-x)LiMO2 (or Li2MO3) 87 and short-range ordered Li1.2Mn0.4M0.4O2 63 rock-salt oxides and Li1.9Mn0.95O2.05F0.95 oxyfluoride88, the Na-based Mg/Zn-doped layered oxides22 and Na-based Li-rich layered oxides89, Li1.68Mn0.6O4−xFx partially ordered spinels90, and, finally, the Li-rich layered Li1.33–2y/3Ti0.67–y/3FeyS2 sulfides91. However, the next step towards the materials with practical importance is clearly of high demand.Modern solid state chemistry, relying on scientific rules, advanced characterization techniques and being empowered with computational tools, is capable of uniting composition, structure and material’s properties and delivering predictions by following a deductive reasoning. DFT- and MD-based computational methods provide a valuable insight into different aspects of the electrochemical behavior of battery-related materials. However, they are very demanding for computer power and often offer too simplified treatment of the real chemical systems, such as disordered or partially ordered materials, materials with intersite mixing, high concentrations of defects, strong electron correlations etc. Nevertheless, the predictive power of these methods in battery research have resulted in several experimentally confirmed polyanion electrode materials, such as the A92. The most significant problem foreseen on this way is the limited size of available well-labeled datasets required for building good models and training the neural networks . One could argue that there is a massive amount of data already stored in scientific publications, which are exponentially growing within the field of batteries, but the reported metrics are full of incoherency with respect to composition characterization, preparation techniques, specimen preparation, measurement methods causing the data variance and making a large part of reports obsolete. More importantly, the whole battery research community must be structured to provide standardized and reliable data calling for more “quantitative” experimental characterization techniques, particularly with respect to retrieving information on disorder and defects. Whatever, the predicted materials will have to be synthesized after all, which brings us back to the skills and competences in solid state chemistry along with some serendipity contribution.Most likely, methods based on Big Data would come into play in the near future, where the semiquantitative links between the chemical composition, crystal structure and electrochemical properties might form a playground for computer-driven analysis of such relationships. Nowadays we evidence an explosive growth of applications of the machine-learning methods in solid-state materials science aimed at predictions of material’s structure and properties95. Thus the solid-state chemists have received a powerful instrument for precise control of the chemical composition, electron/hole doping and stabilizing metastable compositions and oxidation states.Finally, we have to return back to Fig. operando. To fulfill our prediction and hopes, such a multifaceted platform of knowledge should accelerate the development of better materials for rechargeable batteries.In summary, with the battery research becoming a society-driven demand, this field attracts a colossal number of researchers having wide ranges of expertise, hence enabling a multifaceted approach. Solid state chemistry should largely help to unite a vision on the many-sided problems of the discovery of novel materials and novel reactivity concepts based on combined experimental and computational methods together with the help of novel advanced characterization techniques with an improved energy and spatial resolution, preferably applied


Rhesus antigens have been documented to cause haemolytic disease of the newborn as well as acute and delayed transfusion reactions. This study was performed to evaluate the frequency of rhesus antigens  in the studied population.  This study was a cross-sectional study involving 130 prospective blood donors attending University of Calabar Teaching Hospital (UCTH) donor clinic. Donors were grouped for Rh antisera  using the standard serologic technique. 0R0).  The most prevalent Rh antigen was “c” (98.5%), followed by “D” (97.7%), while the least was “C” (30.7%). The most prevalent phenotype was cDe/cDe (R This work therefore concludes that the most prevalent rhesus antigen and rhesus phenotype was c and cDe/cDe among blood donors in University of Calabar Teaching Hospital. The term “blood group” refers to the entire blood group system comprising red blood cell antigens whose specialty is controlled by a series of genes which can be allelic or linked very closely on the same chromosome . PresentThe rhesus blood group, formerly known as the rhesus system, is the second most important blood group system after ABO . At a moThis study took a cross-sectional design with a systematic random sampling technique. A total of 130 prospective blood donors attending University of Calabar Teaching Hospital (UCTH) donor clinic were recruited into the study. Two millimeters (2 ml) of venous blood was collected from each of the 130 blood donors through veinpuncture using the antecubital vein into a plain container. The rhesus phenotypes were determined according to manufacturer's instructions using five specific monoclonal antisera  supplied by Lorne Laboratories (United Kingdom). The principle is based on the ability of Lorne reagents to cause a direct agglutination of the test red blood cells that carry the corresponding rhesus antigen. The presence of the group-specific rhesus antigen was indicated by agglutination.n = 128), followed by the “D” antigen  and “e” antigen . The least observed antigen was “C” , whereas antigen “E” had a prevalence of 39.2% (n = 51)  .n = 60), followed by cDE/cde . The least observed phenotypes were Cde/cde, cde/cde, and CDE/CDe with a prevalence of 0.8% (n = 1)  .Data on various blood group antigens and phenotype frequencies in a population are essential in work-up plan for blood transfusion services .We observed rhesus antigen “c” to be the most prevalent antigen with a prevalence of 98.5%. This finding is similar to the report of Jeremiah and Buseri and Jeremiah and Odumody , 17 who 0R0) followed by cDE/cde . This finding is similar to previous studies in Port Harcourt and Calabar [1R1), CDe/cDe (R1R0), and cDe/cDe (R0R1) as the most prevalent phenotypes in Asians [2R2), CdE/cDe (ryR0) cdE/cde (r11r), cdE/cdE (r11r11), Cde/Cde (r1r1), CdE/Cde (ryr1), CdE/cdE (ryr11), CdE/cde (ryr), and CdE/CdE (ryry) were not detected in the studied population. Due to the low sample size, we could not declare these phenotypes as rare blood. Rare blood is defined on the basis of blood group characteristics, as being found at a frequency of <1 : 1000 random samples in a given population [In our study, the most common phenotype was cDe/cDe . This finding is similar to 97.1% and 93.9% reported in Kano [The prevalence of RhD positive cases was 97.7% and  in Kano  and Beni in Kano .The prevalence of rhesus antigens and phenotypes showed similar pattern in this study and other previous studies with antigen c and cDe/cDe phenotypes occurring as most prevalent antigen and phenotype in Nigerians and other African population. The antigens were found in the order c > D > e > E > C. The data of these antigens put the call to incorporate their testing in synergy with the D antigen in routine blood screening prior to transfusion. We observed low frequency of rhesus D negative blood group in this study (2.3%). The low prevalence of RhD negative blood groups in our study environment also illuminates the need to make proactive plan in event of RhD negative patient requiring blood transfusion. Our frequency data on Rh antigens can help to implement different transfusions and obstetric strategies, which can ultimately improve our patient care. Mass scale typing, however, might be required to complete the database for Rh antigens in Nigeria.


Helianthus tuberosus L. . Usually, purple tubers with high anthocyanin content are more nutritious than white tuber. But, the molecular mechanism underlying it is unknown.Tuber color is an important trait for HtMYB2 (Unigene44371_All) was the only MYB transcription factor, homologous to the MYB transcription factor regulating anthocyanin biosynthesis, expressed in the red tuber epidermis of ‘QY1’. The anthocyanin concentration in the root, stem, leaf, flower, and tuber epidermis of ‘QY1’ was higher than in ‘QY3’, especially tuber epidermis. Correspondingly, HtMYB2 had greater expression in these tissues of ‘QY1’ than in ‘QY3’. The expression of HtMYB2 was associated with anthocyanin accumulation in the different tissues. Overexpression of HtMYB2 activated the anthocyanin biosynthesis pathway, accumulating the pigment in leaves of transgenic tobacco, supporting the model that HtMYB2 regulated anthocyanin biosynthesis. Further experiments found that HtMYB2 had the same coding sequence and genomic sequence in ‘QY1’ and ‘QY3’, but that there were several single nucleotide polymorphisms and one insertion–deletion (indel) mutation of 21 nucleotides in the promoter region between the two alleles. The deletion of three nucleotides “AAA” made the promoter of ‘QY1’ predicted to contain one more possible promoter region. A specific primer, based on the indel, could differentiate between cultivars with red or white tuber epidermis. The genetic variation in HtMYB2 was associated with the tuber skin color in a natural population.In the current study, high-throughput RNA-sequencing was used to compare the transcriptomes between plants with tubers with red or white epidermis. Compared with the white-skinned tubers of cultivar QY3, anthocyanin biosynthesis structural genes had greater expression in the red-skinned tubers of cultivar QY1, indicating that the anthocyanin biosynthesis pathway was activated in ‘QY1’; quantitative PCR confirmed this difference in expression. HTMYB2) controlling anthocyanin biosynthesis in purple epidermis of Jerusalem artichoke tuber. HTMYB2 can regulate anthocyanin biosynthesis in plants and is closely related to the formation of purple phenotype in tubers. This study should be useful in understanding the genetic mechanism underlying different tuber skin colors and in breeding new H. tuberosus cultivars with different tuber skin colors.RNA-seq can successfully isolate the candidate gene ( Helianthus tuberosus L., Jerusalem artichoke or topinambour, belongs to the Asteraceae family and is native to North America , and the effects of chlorophyll and its degradation products on the absorbance results were corrected [Anthocyanins were extracted by the method for “total monomeric anthocyanin pigment content of fruit juice, beverages, natural colors, and wines” . The absorbances (A) at 530 nm and 657 nm -PCR [HtMYB2 of ‘QY1’ and ‘QY3’, a polymorphic PCR marker HtproS was designed to distinguish between ‘QY1’ and ‘QY3’ -PCR . Accordi’ Table S. The allp Table S.Additional file 1: FigureS1. Development of the diagnostic primer HTproS for amplifying the two different alleles of HTMYB2 (QY1 and QY3). The fragments yielded by the marker were either 124 bp or 103 bp, which were indicative of promoter in QY1 and QY3, respectively.Additional file 2: Table S1. The statistic of sequencing, filtering and assembling in transcriptome analysis.Additional file 3: Table S2. The expression level of structural and regulation genes in the anthocyanin biosynthesis pathway.Additional file 4: Table S3. The promoter prediction of HtMYB2.Additional file 5: Table S4. The origin of the Helianthus tuberosus and their MYB genotype examined using HtproS marker.Additional file 6: Table S5. Oligo nucleotide primers used in this work.


The authors of the paper “Evaluation and reconditioning of donor organs for transplantation through ex vivo lung perfusion”, DOI number: 10.31744/einstein_journal/2019AO4288, published in einstein (São Paulo). 2019;17(4):eAO4288 report that the study received funding from the Brazilian Ministry of Health through the PROADIS-SUS Program . During the submission process to einstein (São Paulo) the authors failed to disclose the information about funding.