Materials Today Nano最新文献

{"title":"From waste to catalyst: Engineering brush-like Co/Zn nanoclusters on biomass-derived carbon for peroxymonosulfate activation","authors":"Bao-Ying Wang,&nbsp;Huan-Yan Xu,&nbsp;Jing-Ming Lan,&nbsp;Bo Li","doi":"10.1016/j.mtnano.2026.100898","DOIUrl":"10.1016/j.mtnano.2026.100898","url":null,"abstract":"<div><div>Peroxymonosulfate (PMS)-based advanced oxidation processes (AOPs) provide an efficient and eco-friendly method for degrading organic pollutants in water, yet monometallic activators are limited by active-site aggregation. One-dimensional carbon nanotubes, with their rich surface functionality, offer an ideal platform to overcome this limitation by stabilizing synergistic bimetallic active centers. In this work, Co/Zn nanoclusters were controllably grown on biomass-derived one-dimensional carbon, yielding the composite catalyst Co/Zn@ABC. In this architecture, carbon nanotubes serve dual roles as a morphological template and a growth substrate for in-situ Co/Zn deposition. The resulting hierarchical structure features zero-dimensional metal nanoparticles anchored on one-dimensional carbon nanotubes, while the interwoven nanotubes and nanocluster form a three-dimensional interconnected network. Through its multi-scale architecture, the material provides high exposure of active sites and enables rapid electron transport, leading to markedly enhanced PMS activation. Degradation experiments demonstrated that Co/Zn@ABC achieves 81% removal of high-concentration tetracycline within 10 min. Quenching tests and electron paramagnetic resonance spectroscopy identified ¹O₂ and O₂^•- as the primary reactive species, with SO₄^•- and •OH playing subsidiary roles. Density functional theory calculations based on Fukui functions and molecular orbital theory further elucidated the radical-attack sites and electronic-level reaction pathways. This study not only presents a viable strategy for valorizing biomass into functional catalysts but also provides a material and theoretical foundation for the design of high-performance bimetallic PMS activators, advancing the practical application of AOPs in water treatment.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100898"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148642088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-enabled performance prediction and design for flexible strain sensors","authors":"Yingnan Wu,&nbsp;Zijing Dong,&nbsp;Zhiyuan Sun,&nbsp;Chao Zhi,&nbsp;Zhe Liu,&nbsp;Xingzhong Gao,&nbsp;Yanli Sun,&nbsp;Qi Wang,&nbsp;Xiaolin Zhang,&nbsp;Siman Li,&nbsp;Chenxi Yang,&nbsp;Jindi Chen,&nbsp;Lingjie Yu","doi":"10.1016/j.mtnano.2026.100887","DOIUrl":"10.1016/j.mtnano.2026.100887","url":null,"abstract":"<div><div>The sensing performance of carbon-based flexible strain sensors is largely governed by processing parameters. Therefore, the exploration of optimal processing parameters is of great significance to the enhancement of material properties. However, the complex coupling among multiple variables renders conventional trial-and-error optimization inefficient. Here, a data-driven prediction–optimization strategy integrating design of experiments (DoE) with machine learning (ML) is established to accelerate the regulation of sensing performance in a thermoplastic polyurethane/carbon nanotube-carbon fiber/thermoplastic polyurethane (TPU/CNTs-CF/TPU) strain sensor. Uniform and information-rich experimental datasets are constructed within a high-dimensional parameter space, and a multilayer perceptron (MLP) model is trained to characterize the relationship between processing parameters and sensing performance. SHAP-based interpretability analysis is further employed to quantitatively elucidate the contribution mechanisms of key factors, including carbon loading and carbon nanotube ratio, thereby guiding targeted experiments in high-sensitivity regions and enabling iterative optimization through dataset expansion. As a result, the sensor sensitivity is markedly improved, with the gauge factor (GF) increasing from 15 to 105 while maintaining high predictive accuracy (R² = 0.96). The trained model is subsequently used to screen 600 randomly sampled parameter combinations, from which two optimal candidates are identified and experimentally validated, yielding relative prediction errors as low as 2.3% and 3.1% at 80% strain. Moreover, the optimized sensors exhibit excellent stability under cyclic loading and human-motion monitoring. This work provides an efficient and interpretable paradigm for regulating material–process–performance relationships in flexible electronics, substantially reducing experimental cost and offering broad methodological guidance for high-performance flexible sensing systems.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100887"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148642142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of grain size distribution in regulating the phase transformation behavior of polycrystalline NiTiCu shape memory alloys","authors":"Shuai Wang,&nbsp;Xiang Zhu,&nbsp;Liangliang Chu,&nbsp;Guansuo Dui","doi":"10.1016/j.mtnano.2026.100893","DOIUrl":"10.1016/j.mtnano.2026.100893","url":null,"abstract":"<div><div>NiTiCu shape memory alloys have attracted considerable attention in precision sensing owing to their exceptionally narrow transformation hysteresis. However, how the spatial distribution of grain sizes influences their superelastic behavior remains poorly understood. In this study, molecular dynamics simulations were employed to elucidate the microscopic mechanisms governing martensitic transformation in polycrystalline NiTiCu alloys with uniform, bimodal, and gradient grain size distributions. Uniform nanograined structures exhibit high strength, but dense grain boundaries inhibit transformation and promote localized martensite bands, increasing energy dissipation and irrecoverable deformation, leading to pronounced hysteresis that can be alleviated by larger grains. Bimodal distributions maintain fine grains while reducing overall grain boundary density, concentrating transformation within coarse-grained regions, thereby lowering energy dissipation and suppressing irrecoverable deformation. Gradient structures suppress strain localization by promoting spatially diffuse, progressive transformation, preventing local strain concentration. A surface-to-interior grain refinement generates dense martensitic variant interfaces, synergistically enhancing strength and energy dissipation. Conversely, a surface-to-interior grain coarsening simplifies the transformation pathway, further reducing hysteresis. These atomic-scale insights provide a theoretical foundation for designing low-hysteresis, high-performance shape memory alloys.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100893"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148642143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the role of pyrolysis duration to nitrogen speciation in Co-N-C catalysts for bifunctional energy conversion applications","authors":"V. Saranya,&nbsp;Sivalingam Muthu Mariappan,&nbsp;M. Navaneethan,&nbsp;J. Archana","doi":"10.1016/j.mtnano.2026.100908","DOIUrl":"10.1016/j.mtnano.2026.100908","url":null,"abstract":"<div><div>Designing efficient multifunctional electrocatalysts with improved interfacial charge-transfer kinetics remains crucial for the development of advanced energy conversion systems. In this study, nitrogen-rich MOF-derived cobalt-carbon (CN@Co) nanostructures were prepared through the controlled annealing of ZIF-67 under a nitrogen atmosphere. By experimentally varying the annealing duration from 2 to 6 h, it is observed that prolonged thermal treatment significantly increases the proportion of pyridinic nitrogen (∼90.4%), enhances Co-N coordination and facilitates the formation of a porous carbon framework with uniformly distributed cobalt nanoparticles. These results provide clear evidence of a time-dependent structural evolution, where extended annealing promotes the stabilization of pyridinic-N and Co-N_x active sites, as confirmed by XPS analysis, which ultimately contributes to improved electrochemical performance. Electrochemical studies further support this observation, the optimized sample shows the lowest overpotential,Tafel slopes and reduced charge-transfer resistance in EIS measurements, indicating faster interfacial kinetics. Among the prepared catalysts, CN@Co-6h exhibits the best performance, delivering low overpotentials of 330 mV @ 25 mA cm⁻² for OER and 249 mV @ −50 mA cm⁻² for HER, along with excellent operational stability over 70 h. Furthermore, the samples were tested in dye-sensitized solar cells, the catalyst achieves a power conversion efficiency of 5.10%, which can be attributed to its enhanced triiodide reduction kinetics.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100908"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148770372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-inspired anisotropic phase-change composites via in-situ alkaline activation for thermally adaptive, anti-dripping, and electrically insulating battery thermal management","authors":"Dehao Li,&nbsp;Liyuan Zhang,&nbsp;Renjie Chen,&nbsp;Jun Li","doi":"10.1016/j.mtnano.2026.100936","DOIUrl":"10.1016/j.mtnano.2026.100936","url":null,"abstract":"<div><div>The aggressive implementation of fast charging protocols in high-energy-density lithium-ion batteries severely intensifies internal Joule heating, triggering a hazardous electro-thermal-fire trilemma. Traditional organic phase-change materials (PCMs) offer an attractive energy-free cooling route but suffer from low thermal conductivity, liquid leakage, flammability, and poor electrical insulation. Herein, a leaf-vein-inspired anisotropic phase-change composite material (CPCM) is fabricated via an elegant, pre-modification-free in-situ alkaline activation and directional ice-templating strategy. By leveraging the residual nucleophilic hydroxyl ions natively dwelling within the strongly alkaline aramid nanofiber (ANF) slurry, the unpassivated edge defects of pristine boron nitride nanofibers (BNNFs) undergo a spontaneous interfacial chemical reconstruction. This in-situ reaction matures an extensive hydrogen-bonding network and mechanical interlocking with neighboring ANF backbones, structurally locking them into highly aligned, vertical lamellar cell walls. Benefiting from continuous vertical phonon highways, the engineered CPCM delivers an outstanding out-of-plane thermal conductivity of 1.12 W/(m·K) while preserving a premium latent heat density of 216.9 J/g with an elite cycling enthalpy retention of 96.58% across 400 continuous thermal iterations. Furthermore, the robust aerogel framework confers exceptional shape-stabilization, reliable electrical isolation (12.47 MΩ), and advanced anti-dripping structural integrity that effectively prevents hazardous flaming liquid runoff and pool fires during aggressive thermal matrix decomposition. When evaluated under a continuous 2C constant-current rapid-charging protocol for 1800 s, the dynamic synergy between accelerated directional heat conduction and large-capacity latent heat buffering successfully shunts intense internal heat flux outward, pinning the battery contact interface temperature at 34.3 °C with a peak regulation efficiency of 69.2%.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100936"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148853979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metal organic framework-derived hollow structures for environmental remediation and wastewater treatment: The nexus of experimental, artificial intelligence, and machine learning approaches","authors":"Iftikhar Hussain,&nbsp;Karanpal Singh,&nbsp;Riffat Amna,&nbsp;Abdullah Al Mahmud,&nbsp;Shabhe Haider,&nbsp;Khalid Aljohani,&nbsp;P. Rosaiah,&nbsp;Uzair Sajjad,&nbsp;Wail Al Zoubi,&nbsp;Sajjad Hussain","doi":"10.1016/j.mtnano.2026.100909","DOIUrl":"10.1016/j.mtnano.2026.100909","url":null,"abstract":"<div><div>Metal-organic frameworks (MOFs)-porous hybrid materials formed by the self-assembly of metal ions/clusters with organic ligands offer exceptional versatility and precise composition control without losing their structural integrity. Through various controlled routes, MOFs readily convert into nanostructured hollow porous materials (NHPMs), such as metal oxides, sulfides, and beyond. Featuring high surface areas and interconnected pore networks, these derivative NHPMs play a critical role in environmental remediation and wastewater treatment. This review highlights the MOF-derived NHPMs for environmental remediation and wastewater treatment. Further, Artificial intelligence and Machine learning approaches have been discussed. Finally, current challenges in the field and potential future directions are discussed.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100909"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148730378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of machine learning for accurate prediction of graphene-based terahertz metamaterial sensor performance","authors":"Youssef Amraoui,&nbsp;Imane Halkhams,&nbsp;Rachid El Alami,&nbsp;Mohammed Ouazzani Jamil,&nbsp;Hassan Qjidaa","doi":"10.1016/j.mtnano.2026.100911","DOIUrl":"10.1016/j.mtnano.2026.100911","url":null,"abstract":"<div><div>This paper presents a high-performance sensor based on a tunable dual-band metamaterial absorber for terahertz (THz) applications. The suggested design has a compact size of 20.5 × 20.5 × 14 μm³ and exhibits near-unity absorption peaks of 99.82% and 99.88% at 2.9215 THz and 9.0199 THz, respectively. Owing to the tunable surface conductivity of graphene, the sensor enables dynamic control of its electromagnetic response. The proposed absorber is employed to evaluate the sensing performance in terms of analyte thickness and refractive index (RI). The sensor achieves a sensitivity of approximately 495 GHz/RIU for a 1 μm-thick analyte with a refractive index ranging from 1.32 to 1.40, along with quality factors of up to 2.6 at the first resonant frequency and 51.9 at the second resonant frequency. To address the high computational cost associated with full-wave electromagnetic simulations, several supervised machine learning models are implemented to predict the absorptivity response based on key physical parameters. A comparative study involving Random Forest, Decision Tree, K-Nearest Neighbors, and Gradient Boosting Regression is conducted. Among these models, Random Forest demonstrates the best performance, achieving an RMSE of 0.0056, MAE of 0.0026, MSE of 0.000032, and an R² value of 0.9375. These findings demonstrate the effectiveness of combining graphene-based metamaterials with machine learning method to develop high-performance, tunable THz sensors while enabling efficient prediction and optimization of sensing performance, with potential extension to other spectral regimes.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100911"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148730379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermochromic fluorescent hydrogels tuned by self-crystallinity phase change toward intelligent sensing and self-powered applications","authors":"Liuyan Zhuo,&nbsp;Miao Tian,&nbsp;Shuo Lin,&nbsp;Qingrong Jiang,&nbsp;Yanya Mao,&nbsp;Xiaohua Chang,&nbsp;Jie Shang,&nbsp;Albert G. Nasibulin,&nbsp;Yutian Zhu","doi":"10.1016/j.mtnano.2026.100920","DOIUrl":"10.1016/j.mtnano.2026.100920","url":null,"abstract":"<div><div>Thermo-switchable fluorescent materials have aroused considerable interest owing to their distinctive temperature-dependent fluorescent colorimetric responses. Here, we propose a facile and general approach to develop thermochromic fluorescent hydrogels governed by a self-crystallinity phase transition. The reversible crystallization/melting process of long-chain saturated fatty acids (FAs) dominates the fluorescence switching of the hydrogels. Below the melting point, FA molecules self-assemble into crystalline domains, confining coumarin dyes in an aggregated (non-dispersed) state with orange fluorescence. When the temperature exceeds the phase transition point, the melting of FAs disperses the coumarin dyes, thereby triggering a distinct orange-to-blue fluorescence color conversion. Furtherly, by using FAs with different melting points, a fluorescent thermometer covering 30–65 °C is demonstrated. Importantly, the temperature-induced fluorescence change correlates well with the resistance signal, achieving synergistic optical–electrical dual-mode temperature feedback. Beyond temperature sensing, the hydrogel shows excellent strain and pressure sensing performance, as well as triboelectric energy harvesting capability. This work provides an effective strategy to construct thermochromic fluorescent hydrogels and offers a promising platform for next-generation wearable electronics.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100920"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148730529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conductive zeolite-confined nickel oxide for efficient and durable water electrolysis","authors":"Tenglong Zhang,&nbsp;Huijie Zhang,&nbsp;Shuaichong Wei,&nbsp;Lanlan Wu,&nbsp;Jingde Li","doi":"10.1016/j.mtnano.2026.100913","DOIUrl":"10.1016/j.mtnano.2026.100913","url":null,"abstract":"<div><div>The oxygen evolution reaction (OER) is the critical step for the water electrolysis due to the sluggish four-electron transfer processes as well as the durability issue under the harsh anodic potentials. Here, we develop a conductive zeolite confinement strategy by embedding nickel oxide nanoparticles within Co-modified zeolite Y to form a NiO@CoY heterostructure. The zeolite with supercages confines the active phases in the cavities, preventing them detachment or aggregation and thus improving the long-term durability. Moreover, strong Ni−O−Co interfacial electronic interactions induce positively shift of Ni d-band center, enhancing *OOH adsorption and accelerating OER activity. Consequently, NiO@CoY achieves a low overpotential of 247 mV at 10 mA cm⁻² in 1.0 M KOH, and operates stably for over 700 h at 500 mA cm⁻² in an anion-exchange-membrane electrolyzer. This work offers a strong foundation for tailoring conductive zeolite as sensible support for efficient and durable OER electrocatalysts.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100913"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148730684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graphene-driven synergistic strengthening-toughening of layered Cu/Fe nanocomposite","authors":"Pengfei Wu,&nbsp;Gaojing Sun,&nbsp;Wei Zhang,&nbsp;Yang Sun,&nbsp;Kai Liu,&nbsp;Yunlai Zhou,&nbsp;Arash Kardani","doi":"10.1016/j.mtnano.2026.100902","DOIUrl":"10.1016/j.mtnano.2026.100902","url":null,"abstract":"<div><div>Layered Cu/Fe nanocomposite and their graphene-reinforced counterparts were systematically investigated to clarify their tensile response, as well as the regulatory effects of temperature (293 K/77 K) and graphene incorporation. Both materials undergo three distinct deformation stages, namely elastic deformation, plastic deformation and fracture failure, which are fundamentally dominated by the inherent property differences between Cu and Fe phases as well as interfacial interaction behaviors. Graphene displays selective interfacial adhesion—detaching from Cu while strongly bonding to Fe—enabling Fe-graphene synergistic deformation. This unique effect significantly breaks the traditional strength-ductility trade-off, reverses Fe's failure sequence (from prior to posterior fracture), effectively promotes dislocation accumulation in both phases, and enhances the HCP phase (stacking faults) in Cu. It is found that pristine Cu/Fe nanocomposites merely achieve strength enhancement at 77 K with no obvious improvement in ductility. In contrast, graphene-reinforced Cu/Fe composites realize synchronous optimization of strength and ductility under cryogenic conditions through graphene-induced interfacial regulation, achieving a 9.66% increase in tensile strength and a 5.31% improvement in ductility. This work enriches multi-phase nanocomposite deformation theory and guides the design of high-performance materials for extreme low-temperature applications.</div></div>","PeriodicalId":48517,"journal":{"name":"Materials Today Nano","volume":"35 ","pages":"Article 100902"},"PeriodicalIF":7.6,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148642092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}