Solution‑Processed Thin Film Transparent Photovoltaics:Present Challenges and Future Development

Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar energy.However,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban environment.To overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric energy.Current TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar panels.In this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve transparency.Figures of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV technology.Then we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic PVs.The applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and facades.Finally,current challenges and future opportunities in TPV research are pointed out.

Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing

The common marmoset(Callithrix jacchus)has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies.Epileptic marmosets have been independently reported in two Asian primate research centers.Nevertheless,the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated.Here,we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing.We identified 14558184 single nucleotide polymorphisms(SNPs)from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples.Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers.In addition,SNP and copy number variation(CNV)analyses suggested that the WW domain-containing oxidoreductase(WWOX)and Tyrosine-protein phosphatase nonreceptor type 21(PTPN21)genes may be associated with epilepsy in marmosets.Notably,KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets.This study provides valuable population genomic resources for marmosets in two Asian primate centers.Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers,while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.

Reversible Mn^(2+)/Mn^(4+)double-electron redox in P3-type layer-structured sodium-ion cathode

The balance between cationic redox and oxygen redox in layer-structured cathode materials is an important issue for sodium batteries to obtain high energy density and considerable cycle stability.Oxygen redox can contribute extra capacity to increase energy density,but results in lattice instability and capacity fading caused by lattice oxygen gliding and oxygen release.In this work,reversible Mn^(2+)/Mn^(4+)redox is realized in a P3-Na_(0.65)Li_(0.2)Co_(0.05)Mn_(0.75)O_(2)cathode material with high specific capacity and structure stability via Co substitution.The contribution of oxygen redox is suppressed significantly by reversible Mn^(2+)/Mn^(4+)redox without sacrificing capacity,thus reducing lattice oxygen release and improving the structure stability.Synchrotron X-ray techniques reveal that P3 phase is well maintained in a wide voltage window of 1.5-4.5 V vs.Na^(+)/Na even at 10 C and after long-term cycling.It is disclosed that charge compensation from Co/Mn-ions contributes to the voltage region below 4.2 V and O-ions contribute to the whole voltage range.The synergistic contributions of Mn^(2+)/Mn^(4+),Co^(2+)/Co^(3+),and O^(2-)/(O_n)^(2-)redox in P3-Na_(0.65)Li_(0.2)Co_(0.05)Mn_(0.75)O_(2)lead to a high reversible capacity of 215.0 m A h g^(-1)at 0.1 C with considerable cycle stability.The strategy opens up new opportunities for the design of high capacity cathode materials for rechargeable batteries.

GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

Microwave-accelerated direct regeneration of LiCoO_(2)cathodes for Li-ion batteries

Recycling spent lithium-ion batteries is integral to today's low-carbon environmental protection efforts.The concept of direct regeneration,acknowledged for its environmental sustainability,economic viability,and consistent performance of recycled materials,is gaining prominence.This study presents an efficient and nondestructive approach by utilizing an ultrafast microwave technology to directly regenerate spent lithium cobaltate(LCO)cathode materials.In contrast to conventional furnacebased processes,this method significantly reduces the regeneration timeframe.By subjecting the spent LCO mixed with lithium sources to three microwave heating cycles(at approximately 1,350 K),LCO regeneration is achieved,yielding a specific capacity of 140.8 mAh g^(-1)(0.2 C)with a robust cycle stability.With further environmental and economic benefits,the ultrafast microwave technology holds scientific promise for directly regenerating cathode materials,while establishing competitiveness for industrial applications.

The effect of volume change and stack pressure on solid-state battery cathodes

Solid-state lithium batteries may provide increased energy density and improved safety compared with Li-ion technology.However,in a solid-state composite cathode,mechanical degradation due to repeated cathode volume changes during cycling may occur,whichmay be partially mitigated by applying a significant,but often impractical,uniaxial stack pressure.Herein,we compare the behavior of composite electrodes based on Li4Ti5O12(LTO)(negligible volume change)and Nb2O5(+4%expansion)cycled at different stack pressures.The initial LTO capacity and retention are not affected by pressure but for Nb2O5,they are significantly lower when a stack pressure of<2MPa is applied,due to inter-particle cracking and solid-solid contact loss because of cyclic volume changes.Thiswork confirms the importance of cathode mechanical stability and the stack pressures for long-term cyclability for solid-state batteries.This suggests that low volumechange cathode materials or a proper buffer layer are required for solid-state batteries,especially at low stack pressures.

Thermal transport mechanism of electrons and phonons in pristine and defective HfB_(2)

Hafnium diboride(HfB_(2))is an important metallic ceramic that works in harsh environments,due to its high strength and thermal conductivity.Although the thermal conductivity of HfB_(2) has been measured,the experimental results are scattered.Also,the thermal transport mechanism of HfB_(2) is not well understood.In this work,we study the thermal transport in both pristine and defective HfB_(2) from first-principles calculations.For the pristine HfB_(2),the room-temperature thermal conductivities are 175.0 and 157.7 W·m^(-1)·K^(-1)on a-and c-axes,respectively,where the contributions from electron and phonon are comparable.The Lorenz number is significantly smaller than the Sommerfeld value and shows a temperature dependence,which demonstrates that the Wiedemann-Franz law cannot be used to estimate electronic thermal conductivity.The phonon-isotope and the phonon-electron scattering are non-negligible compared to the phonon-phonon scattering.For the defective HfB_(2),the grain size effects are negligible with length scales larger than 1μm.The pore can limit thermal conductivity when its occupancy is larger than 10%.The vacancy is found to induce scattered results in experiments.The phonon thermal conductivity significantly reduces even with only 1%vacancy,while the electronic thermal conductivity is not sensitive to the vacancy.Our study provides an in-depth understanding of the thermal transport in HfB_(2),and the revealed mechanisms provide important guidance on the design of HfB_(2)-based materials.

Simple-structured hydrophilic sensors for sweat uric acid detection with laser-engraved polyimide electrodes and cellulose paper substrates

Accurate detection of uric acid(UA)is crucial for diagnosing gout,yet traditional sweat-based UA sensors continue to face challenges posed by complex and costly electrode fabrication methods,as well as weakly hydrophilic substrates.Here,we designed and developed simple,low-cost,and hydrophilic sweat UA detection sensors constructed by carbon electrodes and cellulose paper substrates.The carbon electrodes were made by carbonized polyimide films through a simple,one-step laser engraving method.Our electrodes are porous,possess a large specific surface area,and are flexible and conductive.The substrates were composed of highly hydrophilic cellulose paper that can effectively collect,store,and transport sweat.The constructed electrodes demonstrate high sensitivity of 0.4μA Lμmol^(-1)cm^(-2),wide linear range of 2–100μmol/L.In addition,our electrodes demonstrate high selectivity,excellent reproducibility,high flexibility,and outstanding stability against mechanical bending,temperature variations,and extended storage periods.Furthermore,our sensors have been proven to provide reliable results when detecting UA levels in real sweat and on real human skin.We envision that these sensors hold enormous potential for use in the prognosis,diagnosis,and treatment of gout.

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development.Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions.However,the internal mechanisms of batteries are sensitive to many factors,such as charging/discharging protocols,manufacturing/storage conditions,and usage patterns.These factors will induce state transitions,thereby decreasing the prediction accuracy of data-driven approaches.Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources.Hence,we develop two transfer learning methods,Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit,to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance.From our results,our transfer learning methods reduce root-mean-squared error by 41%through adapting to the target domain.Furthermore,the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining.These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

Positioning solid-state sodium batteries in future transportation and energy storage

In accordance with the Paris Agreement,China has committed to reach the peak of carbon dioxide emissions and achieve carbon neutrality by 2030 and 2060,respectively.This places rechargeable batteries to the central stage because they are at the core of renewable energy technologies such as electric vehicles and large-scale energy storage systems.On one hand,some emerging applications(such as power electric aircrafts and trucks)demand very high energy density.For this,we must solve both energy density and safety problems.Solid-state lithium batteries are the way to go[1].

Correlate phonon modes with ion transport via isotope substitution

Understanding the correlations between lattice dynamics(phonons) and ion transport is important for improving the ionic conductivity of solid-state electrolytes. This understanding largely hinges on selective tuning or excitation of specific phonon modes without changing the chemical environments of atoms, which is, however, challenging to be achieved. In this work, we used ~6Li isotope substitution to selectively change the phonon properties associated with lithium, without introducing additional defects or disorders which would affect the ion transport properties. The changes in the phonon modes were then related to ion transport properties through impedance measurements and deep potential molecular dynamics simulations. Our results demonstrated that lower lithium vibration frequency leads to higher ionic conductivity and lower activation energy in the garnet solid-state electrolyte of Li_(6.4)La_(3)Zr_(1.4)Ta_(0.6)O_(12). We furthermore quantified the effect of lithium-related phonons on the migration entropy and attempt frequency, which would be difficult to be achieved otherwise. Our work suggests an effective isotope substitution method to decouple the effect of phonon modes to ion transport from that of other complex structural factors. The obtained insights can contribute to innovative understanding of ion transport in solids and strategies to optimize the ionic conductivity of solid-state electrolytes.