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High-selectivity electroreduction of low-concentration CO2 with large concentration fluctuation

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Science China Chemistry 2025年

作者： Mengyu Qi Yanbin Ma Chao Zhang Bingwei Li Xueqing Yang Zhaolin Shi Simeng Liu Changhua An Jiqing Jiao Tongbu Lu MOE International Joint Laboratory of Materials Microstructure Analysis and Testing CenterInstitute for New Energy Materials and Low Carbon TechnologiesSchool of Materials Science and EngineeringSchool of Chemistry and Chemical EngineeringTianjin University of Technology Key Laboratory of advanced Energy Materials Chemistry (Ministry of Education) Nankai University

Electrochemical CO2reduction reaction（CO2RR） has been regarded as one of the most promising solutions to achieving “zero carbon emission”. In most of the CO2RR-related studies, high-purity CO2has been employed as the feed gas; however, in practice, CO2is generally emitted in low concentrations, so it is of great significance to realize high-selectivity electroreduction of low-concentration CO2with large concentration fluctuation. In this work, we constructed a dual-active-site catalyst and successfully achieved CO2local enrichment and conversion for low-concentration CO2. Operando experiments reveal that the catalyst has one type of site for activating CO2and one type of site for binding the reaction intermediates. The dual-active-site catalyst displays a selectivity for formic acid consistently above 97% over a broad potential window（from-0.9 to-1.6 V ***）. Even when fed with a low-concentration CO2stream（volume ratio from 50% down to 10%）, the dual-active-site catalyst could display high activity and selectivity（>91%）. In particular, the selectivity is still above 85% when the CO2volume ratio is as low as 5%. This work offers a feasible route for converting low-concentration CO2via a synergistic effect for dual-active-site catalysts.

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Advances in the Development of Gradient Scaffolds Made of Nano‑Micromaterials for Musculoskeletal Tissue Regeneration

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Nano-Micro Letters 2025年第3期17卷 455-500页

作者： Lei Fang Xiaoqi Lin Ruian Xu Lu Liu Yu Zhang Feng Tian Jiao Jiao Li Jiajia Xue Beijing Laboratory of Biomedical Materials Beijing University of Chemical TechnologyBeijing 100029People’s Republic of China State Key Laboratory of Organic‑Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029People’s Republic of China School of Biomedical Engineering Faculty of Engineering and ITUniversity of Technology SydneySydneyNSW 2007Australia

The intricate hierarchical structure of musculoskeletal tissues,including bone and interface tissues,necessitates the use of complex scaffold designs and material structures to serve as tissue-engineered *** has led to growing interest in the development of gradient bone scaffolds with hierarchical structures mimicking the extracellular matrix of native tissues to achieve improved therapeutic *** on the anatomical characteristics of bone and interfacial tissues,this review provides a summary of current strategies used to design and fabricate biomimetic gradient scaffolds for repairing musculoskeletal tissues,specifically focusing on methods used to construct compositional and structural gradients within the *** latest applications of gradient scaffolds for the regeneration of bone,osteochondral,and tendon-to-bone interfaces are ***,the current progress of testing gradient scaffolds in physiologically relevant animal models of skeletal repair is discussed,as well as the challenges and prospects of moving these scaffolds into clinical application for treating musculoskeletal injuries.

关键词： Gradient scaffolds Musculoskeletal tissues advanced manufacturing Biomaterials Tissue regeneration

Sex differences in aging and injured brain

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Neural Regeneration Research 2025年第10期20卷 2901-2902页

作者： Jordan N.Williamson Yuan Yang University of Illinois Urbana-Champaign Grainger College of EngineeringDepartment of BioengineeringUrbanaILUSA Carle Foundation Hospital Stephenson Family Clinical Research InstituteClinical Imaging Research CenterUrbanaILUSA University of Illinois Urbana-Champaign Beckman Institute for Advanced Science and TechnologyUrbanaILUSA Northwestern University Department of Physical Therapy and Human Movement SciencesChicagoILUSA

Background:The prevalence,age of onset,and symptomatology of traumatic brain injury,stroke,and neurodegenerative diseases(such as Alzheimer’s disease(AD),Parkinson’s disease,amyotrophic lateral sclerosis,and Huntington’s disease)differ substantially between males and *** higher prevalence of these brain disorders has been attributed to females having a greater longevity compared with *** one of the greatest risk factors of acquired brain injury(such as stroke,traumatic brain injury caused by fall)and neurodegenerative disease is age.

关键词： Huntington prevalence traumatic

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Asymmetric interfacial engineering regulated charge distribution on Ru/Ni-N-C sites for efficient hydrogen evolution reaction in alkaline and seawater electrolytes

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Science China Chemistry 2025年

作者： Rui Yu Xi Cao Chengyang Zhu Qingqing Chen Ziyi Yan Binbin Jiang Junjie Mao Xianwen Wei Key Laboratory of Electrochemical Clean Energy of Anhui Higher Education Institutes College of Chemistry and Materials ScienceAnhui Normal University Anhui Provincial Key Laboratory of advanced Catalysis and Energy Materials School of Chemistry and Chemical Engineering Anqing Normal University School of Chemistry and Chemical Engineering Anhui University of Technology

Developing highly efficient and cost-effective electrocatalysts for hydrogen evolution reaction（HER） is grandly challenging in alkaline and alkaline seawater electrolytes. Herein, the asymmetric interfacial active sites with Ru nanoparticles and Ni single atoms in Ru/Ni-N-C were designed through a solvothermal-pyrolysis process. Constructing highly asymmetric interfacial active sites with a strong electron delocalization effect significantly improves HER kinetics. As expected, Ru/Ni-N-C requires low overpotentials with around 20 mV at 10 mA cm-2and robust durability over 48 h in alkaline and alkaline seawater *** at 200 mA cm-2, the overpotentials are close to 100 mV in both above electrolytes for Ru/Ni-N-C. Density function theory calculation results suggest that the asymmetric interface between Ru nanoparticle and Ni-N-C could accelerate the dissociation of water molecules and modulate the hydrogen species, consequently improving the HER performances. This work opens a unique approach for constructing advanced materials for energy conversion.

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A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen School of Electronic and Information Engineering University of Science and Technology LiaoningAnshan114051China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

Post-tunable salt gel electrolytes toward flexible supercapacitor switches

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Journal of Energy Chemistry 2025年第1期 114-124页

作者： Hui Wang Shuang Chen Xuming Liu Qin Zhang Xin Liu Polymeric and Soft Materials Laboratory School of Chemistry and Life Science and Advanced Institute of Materials Science Changchun University of Technology Polymeric and Soft Materials Laboratory School of Chemical Engineering and Advanced Institute of Materials Science Changchun University of Technology

Convertible hydrogel supercapacitors have emerged as promising energy storage devices in switches,diodes, and transistors. However, inherent weaknesses in ionic conductivity, mechanical properties,and water retention of hydrogel electrolytes seriously hinder their development. Inspired by the hardness conversion of sea cucumber skin, a conductivity and mechanics dual-tunable salt gel electrolyte is successfully designed. The salt gel presents a reversible switching of conductors-insulators and a mechanical regulation between softness and hardness via the dissolution-crystallization transition of sodium acetate trihydrate（SAT）. Meanwhile, the salt gels spontaneously grow a layer of “armor” through saturated phase-change salt crystals effectively reducing water evaporation of hydrogel ***, this phase-change soft-rigid conversion strategy will expand the capabilities of gel-based flexible supercapacitors(area capacitance: 258.6 mF cm-2), and the capacitance retention rate could still reach 86.9% after 3000 cycles at high temperatures. Moreover, the salt gel supercapacitor is potentially used in over-heat alarm systems. It is anticipated that the strategy of conductivity and mechanics of dual-tunable salt gel would provide a new perspective on the development of energy storage devices,wearable electronics, and flexible robots.

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Decreased levels of phosphorylated synuclein in plasma are correlated with poststroke cognitive impairment

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Neural Regeneration Research 2025年第9期20卷 2598-2610页

作者： Yi Wang Yuning Li Yakun Gu Wei Ma Yuying Guan Mengyuan Guo Qianqian Shao Xunming Ji Jia Liu Department of Clinical Laboratory Beijing Bo’ai HospitalChina Rehabilitation Research CenterCapital Medical UniversityBeijingChina Beijing Institute of Brain Disorders Laboratory of Brain DisordersMinistry of Science and TechnologyCollaborative Innovation Center for Brain DisordersBeijing Advanced Innovation Center for Big Data-based Precision MedicineCapital Medical UniversityBeijingChina Department of Neurosurgery Xuanwu HospitalCapital Medical UniversityBeijingChina

Poststro ke cognitive impairment is a major secondary effect of ischemic stroke in many patients;however,few options are available for the early diagnosis and treatment of this *** aims of this study were to(1)determine the specific relationship between hypoxic andα-synuclein during the occur of poststroke cognitive impairment and(2)assess whether the serum phosphorylatedα-synuclein level can be used as a biomarker for poststro ke cognitive *** found that the phosphorylatedα-synuclein level was significantly increased and showed pathological aggregation around the cerebral infa rct area in a mouse model of ischemic *** addition,neuronalα-synuclein phosphorylation and aggregation were observed in the brain tissue of mice subjected to chronic hypoxia,suggesting that hypoxia is the underlying cause ofα-synuclein-mediated pathology in the brains of mice with ischemic *** phosphorylatedα-synuclein levels in patients with ischemic stroke were significantly lower than those in healt hy subjects,and were positively correlated with cognition levels in patients with ischemic ***,a decrease in serum high-density lipoprotein levels in stroke patie nts was significantly correlated with a decrease in phosphorylatedα-synuclein *** ischemic stroke mice did not show significant cognitive impairment or disrupted lipid metabolism 14 days after injury,some of them exhibited decreased cognitive function and reduced phosphorylatedα-synuclein *** together,our results suggest that serum phosphorylatedα-synuclein is a potential biomarker for poststroke cognitive impairment.

关键词： biomarker high-density lipoprotein ischemic stroke phosphorylatedα-synuclein poststroke cognitive impairment

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Learning to see speckle in the weak laser field through multimode fiber

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Optoelectronics Letters 2025年

作者： JI Yunqi SONG Binbin LI Xueqing LI Yonghui The Engineering Research Center of Learning-Based Intelligent System (Ministry of Education)， the Key Laboratory of Computer Vision and systems (Ministry of Education)， and the School of Computer Science and Engineering， Tianjin University of technology

Multimode fibers (MMFs) have great potential for endoscopic imaging due to the high number of modes and a small core diameter. Deep learning based on neural networks has received increasing attention in the field of scattering image reconstruction. However， most studies focus on designing complex network architectures to improve reconstruction， but these network models struggle to reconstruct images in a weak laser field. In the paper， a lightweight generative adversarial network model combined with a histogram specification algorithm is designed to reconstruct speckles in the weak laser field through MMF. Experimental results show that the reconstruction results of our algorithm have better metrics. Moreover， the model demonstrates excellent cross-domain generalization ability with regards to the Fashion-MNIST dataset. It is worth mentioning that we found that the speckles after inactivation still retain the ability to be reconstructed， which enhances the robustness of the model

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Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

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Energy Engineering 2025年第1期122卷 203-220页

作者： Yu Zhang Daoyu Zhang TiezhouWu School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan430068China

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery ***,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity ***,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model *** address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural ***,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity ***,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network *** validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging *** experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

关键词： Lithium-ion battery state of health differential thermal voltammetry Sparrow Search Algorithm