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Oxidation Resistance of Form-stable Hightemperature Phase Change Thermal Energy Storage Materials Doped by Impregnated Graphite

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 1-12页

作者： LI Baorang DAI Jianhuan zhang Wei LIU Xiangchen YANG Liu School of Energy Power and Mechanical Engineering North China Electric Power UniversityBeijing 102206China School of Ener-gy and Environment Southeast UniversityNanjing 210096China

We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite *** mass ratio of graphite to Al(H_(2)PO_(4))_(3) changed from 0.5:1 to 4:1,and the impregnation time changed from 1 to 7 *** typical composite phase change thermal storage materials doped with the as-treated graphite were fabricated using form-stable *** investigate the oxidation and anti-oxidation behavior of the impregnated graphite at high temperatures,the samples were put into a muffle furnace for a cyclic heat *** on SEM,EDS,DSC techniques,analyses on the impregnated technique suggested an optimized processing conditions of a 3 h impregnation time with the ratio of graphite:Al(H_(2)PO_(4))_(3) as 1:3 for graphite impregnation *** investigations on high-temperature phase change heat storage materials doped by the treated graphite suggested excellent oxidation resistance and thermal cycling performance.

关键词： phase change materials graphite impregnation method oxidation,sintering thermal analysis

Targeting Epac2 and GluA3-containing AMPARs:a novel therapeutic strategy for Alzheimer's disease

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Neural Regeneration Research 2025年第11期20卷 3223-3224页

作者： Tong zhang Martina Schmidt Department of Molecular Pharmacology Groningen Research Institute of PharmacyUniversity of GroningenGroningenThe Netherlands School of Pharmacy Tianjin Medical UniversityTianjinChina

Alzheimer's disease(AD)is a neurodegenerative disease that manifests progressive decline in memory and *** the early stage of AD,memory retrieval is impaired preceding memory acquisition and consolidation(Roy et al.,2016).Prior to the onset of symptoms,pathological amyloid-β(Aβ)plagues and tau protein tangles accumulate in extracellular and intracellular spaces,respectively,leading to *** these hallmark pathologies,Aβ is proposed to be the primary etiology by triggering a cascade of pathogenic events,including neuroinflammation,oxidative stress,tau hyperphosphorylation,synaptic/neuronal dysfunction,and neuronal death(zhang et al.,2023b).

关键词： Alzheimer impaired Aβ

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Polybenzimidazolium-reinforced polyimide separators to inhibit dendrites for high-security lithium-ion batteries

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Science China Chemistry 2025年

作者： Guohua Sun Jiaqi Cui Qingsong zhang Yisong Zhou Xinluo Li Yingying zhang Zhanao zhang Xin zhang Jiantao Fan Pengpeng Li Lianlong Hou Nanjun Chen Hebei Key Laboratory of Flexible Functional Materials School of Materials Science and Engineering Hebei University of Science and Technology State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical Engineering Xiamen University

Lithium dendrite formation poses a significant safety hazard in lithium-ion batteries（LIBs）, severely impeding their widespread adoption and further technological advancements. Here, we present a novel quaternized polybenzimidazolium（q-PBI） to armor polyimide（PI） nanofiber separator（q-PBI@PI）, in which the q-PBI containing lithiophilicity and anionphilicity sites serves as the multifunctional nano-layers to suppress the Li dendrite and reinforce the mechanical properties of PI nanofiber ***, the q-PBI@PI separator displays an unprecedented mechanical strength of 82.8 MPa, significantly outperforming previously reported PI nanofiber membranes（typically below 50.0 MPa）. Besides, we demonstrate that the q-PBI@PI separator simultaneously possesses low nucleation overpotential（59 mV） and exceptional average coulombic efficiency due to the suppression of Li dendrite. Importantly, q-PBI@PI-based Li||Li battery enables a stable Li plating-stripping at 1.0 m A cm-2for600 h. Attributing to these exceptional merits, the armored PI separator-based LIBs display remarkable specific capability and capacity retention. The density function theory calculations reveal that q-PBI is conducive to the desolvation of Li+and can immobilize Li+and PF6-ions near affinity sites of PI nanofibers for inhibiting the formation of Li dendrites. Our work paves a new avenue for the design of next-generation high-performing separators in LIBs.

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Highly conductive and stable iodine doped argyrodite electrolyte for all-solid-state lithium batteries

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Journal of Energy Chemistry 2025年第1期100卷 50-58页

作者： Gaozhan Liu Jing zhang Jing Yang Jinghui Chen Xingyue Xiao Xiayin Yao Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences

Lithium argyrodites with high ionic conductivity and low cost are considered as one of the most prospective solid electrolytes for all-solid-state lithium ***,the poor chemical stability and compatibility with lithium metal limit their ***,Li5.4PS4.4Cl1.4I0.2solid electrolyte with high ionic conductivity of 11.49 m S cm-1and improved chemical stability is synthesized by iodine *** ultra-thin Li5.4PS4.4Cl1.4I0.2membrane with thickness of 10μm can be obtained by wet coating process,exhibiting a high ionic conductivity of 2.09 mS cm-1and low areal resistance of 1.17Ω***,iodine doping could in-situ form LiI at the lithium/electrolyte interface and improve the critical current density of Li5.4PS4.4Cl1.6from 0.8 to 1.35 mA *** resultant LiCoO2/Li5.4PS4.4Cl1.4I0.2/Li battery shows excellent cycling stability at 1 C,with a reversible specific capacity of 110.1 mA h g-1and a retention of 80.5% after 1000 *** addition,the assembled LiCoO2/Li5.4PS4.4Cl1.4I0.2membrane/Li pouch cell delivers an initial discharge capacity of 110.4 mA h g-1and 80.5% capacity retention after 100 cycles.

关键词： Solid-State Batteries

Wafer‑Scale Ag_(2)S‑Based Memristive Crossbar Arrays with Ultra‑Low Switching‑Energies Reaching Biological Synapses

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Nano-Micro Letters 2025年第3期17卷 328-339页

作者： Yuan Zhu Tomas Nyberg Leif Nyholm Daniel Primetzhofer Xun Shi Zhen zhang Division of Solid‑State Electronics Department of Electrical EngineeringUppsala University75121 UppsalaSweden Department of Chemistry Uppsala UniversityUppsalaSweden Department of Physics and Astronomy Uppsala UniversityUppsalaSweden State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050People’s Republic of China

Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic ***,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMOS)technology still suffer from substantially larger energy consumption than biological synapses,due to the slow kinetics of forming conductive paths inside the memristive *** we report wafer-scale Ag_(2)S-based MCAs realized using CMOS-compatible processes at temperatures below 160℃.Ag_(2)S electrolytes supply highly mobile Ag+ions,and provide the Ag/Ag_(2)S interface with low silver nucleation barrier to form silver filaments at low energy *** further enhancing Ag+migration in Ag_(2)S electrolytes via microstructure modulation,the integrated memristors exhibit a record low threshold of approximately−0.1 V,and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological *** low-temperature process also enables MCA integration on polyimide substrates for applications in flexible ***,the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training *** impressive accuracy of 92.6%in image recognition simulations is demonstrated with the MCAs after the *** demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.

关键词： Wafer-scale Ag_(2)S films Reactive sputter Silver nucleation Ag^(+)migration Energy-efficient neuromorphic computing

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

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Structural Durability & Health Monitoring 2025年第1期19卷 25-54页

作者： Chao zhang Shang-Xi Lai Hua-Ping Wang School of Civil Engineering and Mechanics Lanzhou UniversityLanzhou730000China Key Laboratory of Special Functional Materials and Structural Design Ministry of EducationLanzhou UniversityLanzhou730000China

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the ***,it is particularly signiﬁcant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientiﬁc basis for structural damage identiﬁcation and dynamic model modiﬁ*** view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and brieﬂy describes how to identify structural damages based on the derived modal *** paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),brieﬂy describes damage identiﬁcation methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artiﬁcial intelligence(AI)methods in the direction of modal parameter recognition and damage identiﬁcation is further *** on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identiﬁcation methods are given to provide scientiﬁc references for the optimized design and functional upgrading of SHM systems.

关键词： Structural health monitoring data information modal parameters damage identiﬁcation AI method

DecMamba:Mamba Utilizing Series Decomposition for Multivariate Time Series Forecasting

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Computers, Materials & Continua 2025年第1期82卷 1049-1068页

作者： Jianxin Feng Jianhao zhang Ge Cao Zhiguo Liu Yuanming Ding Communication and Network Key Laboratory Dalian UniversityDalian116622China

Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy *** decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time ***,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between *** problems make it difficult to analyze the intricate temporal variations of real-world time *** this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between *** backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend *** with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.

关键词： Data prediction time series Mamba series decomposition

Unraveling brain aging through the lens of oral microbiota

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Neural Regeneration Research 2025年第7期20卷 1930-1943页

作者： Qinchao Hu Si Wang Weiqi zhang Jing Qu Guang-Hui Liu State Key Laboratory of Membrane Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Hospital of Stomatology Guanghua School of StomatologyGuangdong Provincial Key Laboratory of StomatologySun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders Xuanwu HospitalCapital Medical UniversityBeijingChina Aging Translational Medicine Center International Center for Aging and CancerBeijing Municipal Geriatric Medical Research CenterXuanwu HospitalCapital Medical UniversityBeijingChina CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijingChina University of Chinese Academy of Sciences BeijingChina Institute for Stem Cell and Regeneration Chinese Academy of SciencesBeijingChina Aging Biomarker Consortium BeijingChina State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Beijing Institute for Stem Cell and Regenerative Medicine BeijingChina

The oral cavity is a complex physiological community encompassing a wide range of *** of oral microbiota can lead to various oral infectious diseases,such as periodontitis and tooth decay,and even affect systemic health,including brain aging and neurodegenerative *** studies have highlighted how oral microbes might be involved in brain aging and neurodegeneration,indicating potential avenues for intervention *** this review,we summarize clinical evidence demonstrating a link between oral microbes/oral infectious diseases and brain aging/neurodegenerative diseases,and dissect potential mechanisms by which oral microbes contribute to brain aging and *** also highlight advances in therapeutic development grounded in the realm of oral microbes,with the goal of advancing brain health and promoting healthy aging.

关键词： Alzheimer's disease brain aging multiple sclerosis neurodegeneration neurodegenerative diseases oral microbiota Parkinson's disease periodontitis bacteria Porphyromonas gingivalis

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Early identification of stroke through deep learning with multi-modal human speech and movement data

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Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao Wang Bin zhang Haobang Liang Bei Hu Longlong Ren Yanjuan Liu Yuhu zhang Chengbo Dai Hejun Wu Weifeng Li Xin Li School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke

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