Science and Technology of Advanced Materials最新文献

{"title":"Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering.","authors":"Aya Fujiwara, Sunao Nakanowatari, Yohei Cho, Toshiaki Taniike","doi":"10.1080/14686996.2025.2454219","DOIUrl":"10.1080/14686996.2025.2454219","url":null,"abstract":"<p><p>Solid catalyst development has traditionally relied on trial-and-error approaches, limiting the broader application of valuable insights across different catalyst families. To overcome this fragmentation, we introduce a framework that integrates high-throughput experimentation (HTE) and automatic feature engineering (AFE) with active learning to acquire comprehensive catalyst knowledge. The framework is demonstrated for oxidative coupling of methane (OCM), where active learning is continued until the machine learning model achieves robustness for each of the BaO-, CaO-, La₂O₃-, TiO₂-, and ZrO₂-supported catalysts, with 333 catalysts newly tested. The resulting models are utilized to extract catalyst design rules, revealing key synergistic combinations in high-performing catalysts. Moreover, we propose a method for transferring knowledge between supports, showing that features refined on one support can improve predictions on others. This framework advances the understanding of catalyst design and promotes reliable machine learning.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2454219"},"PeriodicalIF":7.4,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11792127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143190376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-throughput evaluation of half-metallicity of Co₂MnSi Heusler alloys using composition-spread films and spin-integrated hard X-ray photoelectron spectroscopy.","authors":"Ryo Toyama, Shunsuke Tsuda, Yuma Iwasaki, Thang Dinh Phan, Susumu Yamamoto, Hiroyuki Yamane, Koichiro Yaji, Yuya Sakuraba","doi":"10.1080/14686996.2024.2439781","DOIUrl":"10.1080/14686996.2024.2439781","url":null,"abstract":"<p><p>We demonstrate high-throughput evaluation of the half-metallicity of Co₂MnSi Heusler alloys by spin-integrated hard X-ray photoelectron spectroscopy (HAXPES) of composition-spread films performed with high-brilliance synchrotron radiation at NanoTerasu, which identifies the optimum composition showing the best half-metallicity. Co_75-<i>x</i> Mn _<i>x</i> Si₂₅ composition-spread thin films for <i>x</i> = 10-40% with a thickness of 30 nm are fabricated on MgO(100) substrates using combinatorial sputtering technique. The <i>L</i>2₁-ordering and (001)-oriented epitaxial growth of Co₂MnSi are confirmed by X-ray diffraction for <i>x</i> = 18-40%. The valence band HAXPES spectra exhibit a systematic compositional dependence and the smallest photoemission intensity at the Fermi level (<i>E</i> _F) for a slightly Mn-rich composition of <i>x</i> = 27%. The density of states (DOS) for <i>L</i>2₁-ordered Co₂MnSi with different Mn compositions obtained from first-principles calculation also show the smallest total DOS at <i>E</i> _F for <i>x</i> = 27% because of the formation of a clear half-metallic gap in the minority spin channel and the less localized <i>d</i>-states in the majority spin channel, indicating the best half-metallic nature of this composition. Our experimental results demonstrate that high-throughput evaluation of half-metallicity is possible even with spin-integrated HAXPES by capturing systematic changes in the electronic structures through the measurements on the composition-spread film. Moreover, the anisotropic magnetoresistance (AMR) of the composition-spread film is measured for electric current directions along the [110] and [100] of Co₂MnSi. Previous studies indicated that a larger negative AMR ratio is a signature of a higher spin polarization. The largest negative AMR ratio is observed for <i>x</i> = 27% for both current directions, which also supports the best half-metallicity for this off-stoichiometric composition.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2439781"},"PeriodicalIF":7.4,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11721931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multicrystalline informatics: a methodology to advance materials science by unraveling complex phenomena","authors":"Noritaka Usami, Kentaro Kutsukake, Takuto Kojima, Hiroaki Kudo, Tatsuya Yokoi, Yutaka Ohno","doi":"10.1080/14686996.2024.2396272","DOIUrl":"https://doi.org/10.1080/14686996.2024.2396272","url":null,"abstract":"Multicrystalline materials play a crucial role in our society. However, their microstructure is complicated, and there is no universal approach to achieving high performance. Therefore, a methodology is necessary to answer the fundamental question of how we should design and create microstructures. ‘Multicrystalline informatics’ is an innovative approach that combines experimental, theoretical, computational, and data sciences. This approach helps us understand complex phenomena in multicrystalline materials and improve their performance. The paper covers various original research bases of multicrystalline informatics, such as the three-dimensional visualization of crystal defects in multicrystalline materials, the machine learning model for predicting crystal orientation distribution, network analysis of multicrystalline structures, computational methods using artificial neural network interatomic potentials, and so on. The integration of these research bases proves to be useful in understanding unexplained phenomena in complex multicrystalline materials. The paper also presents examples of efficient optimization of the growth process of high-quality materials with the aid of informatics, as well as prospects for extending the methodology to other materials.","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"41 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracking the evolution of the morphology and stress distribution of SIS thermoplastic elastomers under tension using atomic force microscopy","authors":"Ling Gao, Haonan Liu, Xiaobin Liang, Makiko Ito, Ken Nakajima","doi":"10.1080/14686996.2024.2402685","DOIUrl":"https://doi.org/10.1080/14686996.2024.2402685","url":null,"abstract":"Styrene-based ABA-type triblock copolymers and their blends are widely investigated thermoplastic elastomers (TPEs). The design of tough TPE materials with high strength and resilience requires further clarification of the relationship between microstructure and macroscopic properties of stretched samples. Here, we applied atomic force microscopy (AFM)-based quantitative nanomechanical mapping to study the deformation behavior of poly(styrene-<i>b</i>-isoprene-<i>b</i>-styrene) blends under tension. The results indicated that the glassy polystyrene (PS) domains deformed and inhomogeneous stress distributions developed in the initial stretching stage. At 200% strain, the glassy PS domains started to crack. The change in the peak value in the JKR Young’s modulus diagram during stretching was consistent with the stress – strain curve. Analysis of the particles before and after stretching suggested that the glassy domains separated and reorganized during stretching.","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"17 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust and orange-yellow-emitting Sr-rich polytypoid α-SiAlON (Sr3Si24Al6N40:Eu2+) phosphor for white LEDs","authors":"Mehdi Estili, Rong-Jun Xie, Kohsei Takahashi, Shiro Funahashi, Tohru S. Suzuki, Naoto Hirosaki","doi":"10.1080/14686996.2024.2396276","DOIUrl":"https://doi.org/10.1080/14686996.2024.2396276","url":null,"abstract":"Nitrides and oxynitrides isostructural to α-Si₃N₄ (<i>M</i>-α-SiAlON, <i>M</i> = Sr, Ca, Li) possess superb thermally stable photoluminescence (PL) properties, making them reliable phosphors for high-power solid-state lighting. However, the synthesis of phase-pure Sr-α-SiAlON still remains a great challenge and has only been reported for Sr below 1.35 at.% as the large size of Sr²⁺ ions tends to destabilize the α-SiAlON structure. Here, we succeeded to synthesize the single-phase powders of a unique ‘Sr-rich’ polytypoid α-SiAlON (Sr₃Si₂₄Al₆N₄₀:Eu²⁺) phosphor with three distinctive Sr/Eu luminescence sites using a solid-state remixing-reannealing process. The Sr content of this polytypoid structure exceeds those of a few previously reported structures by over 200%. The phase purity, composition, structure, and PL properties of this phosphor were investigated. A single phase can be obtained by firing the stoichiometric mixtures of all-nitride precursors at 2050°C under a 0.92 MPa N₂ atmosphere. The Sr₃Si₂₄Al₆N₄₀:Eu²⁺ shows an intense orange-yellow emission, with the emission maximum of 590 nm and internal/external quantum efficiency of 66%/52% under 400 nm excitation. It also has a quite small thermal quenching, maintaining 93% emission intensity at 150°C. In comparison to Ca-α-SiAlON:Eu²⁺, this Sr counterpart shows superior quantum efficiency and thermal stability, enabling it to be an interesting orange-yellow down-conversion luminescent material for white LEDs. The experimental confirmation of the existence of such ‘Sr-rich’ SiAlON systems, in a single-phase powder form, paves the way for the design and synthesis of novel ‘Sr-rich’ SiAlON-based phosphor powders with unparalleled properties.","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"17 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive data network for data-driven study of battery materials","authors":"Yibin Xu, Yen-Ju Wu, Huiping Li, Lei Fang, Shigenobu Hayashi, Ayako Oishi, Natsuko Shimizu, Riccarda Caputo, Pierre Villars","doi":"10.1080/14686996.2024.2403328","DOIUrl":"https://doi.org/10.1080/14686996.2024.2403328","url":null,"abstract":"Data-driven material research for property prediction and material design using machine learning methods requires a large quantity, wide variety, and high-quality materials data. For battery materials, which are commonly polycrystalline, ceramics, and composites, multiscale data on substances, materials, and batteries are required. In this work, we develop a data network composed of three interlinked databases, from which we can obtain comprehensive data on substances such as crystal structures and electronic structures, data on materials such as chemical composition, structure, and properties, and data on batteries such as battery composition, operation conditions, and capacity. The data are extracted from research papers on solid electrolytes and cathode materials, selected by screening more than 330 thousand papers using natural language processing tools. Data extraction and curation are carried out by editors specialized in material science and trained in data standardization.","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"2 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of the surface morphology of alkaline-earth metal oxides on the oxidative coupling of methane.","authors":"Nobutsugu Hamamoto, Takakazu Kawahara, Ryoto Hagiwara, Kohei Matsuo, Kodai Matsukawa, Yoyo Hinuma, Takashi Toyao, Ken-Ichi Shimizu, Takashi Kamachi","doi":"10.1080/14686996.2024.2435801","DOIUrl":"https://doi.org/10.1080/14686996.2024.2435801","url":null,"abstract":"<p><p>Alkaline-earth metal oxides with the rocksalt structure, which are simple ionic solids, have attracted attention in attempts to gain fundamental insights into the properties of metal oxides. The surfaces of alkaline-earth metal oxides are considered promising catalysts for the oxidative coupling of methane (OCM); however, the development of such catalysts remains a central research topic. In this paper, we performed first-principles calculations to investigate the ability of four alkaline-earth metal oxides (MgO, CaO, SrO, and BaO) to catalyze the OCM. We adopted five types of surfaces of rocksalt phases as research targets: the (100), (110), stepped (100), oxygen-terminated octopolar (111), and metal-terminated octopolar (111) surfaces. We found that the formation energy of surface O vacancies is a good descriptor for the adsorption energy of a H atom and a methyl radical. The energies related to the OCM mechanism show that, compared with the most stable surface, the minor surfaces better promote the C - H bond cleavage of methane. However, as the trade-off for this advantage, the minor surfaces exhibit increased affinity for the methyl radical. On the basis of this trade-off relationship between properties, we identified several surfaces that we expect to be promising OCM catalysts. Our investigation of the temperature dependence of the Gibbs free energy indicated that, at higher temperatures, the step (100) surface exhibits properties that might benefit the OCM mechanism.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2435801"},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142954231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling hydrogen-assisted fatigue crack growth in low-carbon steel focusing on thermally activated hydrogen-dislocation interaction.","authors":"Osamu Takakuwa, Yuhei Ogawa","doi":"10.1080/14686996.2024.2436345","DOIUrl":"https://doi.org/10.1080/14686996.2024.2436345","url":null,"abstract":"<p><p>Hydrogen-assisted (HA) fatigue crack growth (FCG) occurs in ferritic steels, wherein H-dislocation interaction plays a vital role. We aim to model the HAFCG mechanism based on the <i>obstruction of dislocations</i> within the crack tip zone. Our modeling framework is as follows: H is condensed into crack tip and trapped by dislocations; these H significantly decrease dislocation mobility; stress relief via crack blunting is suppressed; localized brittle fracture triggers HAFCG. This model was substantiated experimentally in H₂ gas at various load frequencies and temperatures. Theoretical formulations were established considering the thermal equilibrium of H-trapping and dislocation breakaway from the H atmosphere.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2436345"},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703130/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142954292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating machine learning with advanced processing and characterization for polycrystalline materials: a methodology review and application to iron-based superconductors.","authors":"Akiyasu Yamamoto, Akinori Yamanaka, Kazumasa Iida, Yusuke Shimada, Satoshi Hata","doi":"10.1080/14686996.2024.2436347","DOIUrl":"10.1080/14686996.2024.2436347","url":null,"abstract":"<p><p>In this review, we present a new set of machine learning-based materials research methodologies for polycrystalline materials developed through the Core Research for Evolutionary Science and Technology project of the Japan Science and Technology Agency. We focus on the constituents of polycrystalline materials (i.e. grains, grain boundaries [GBs], and microstructures) and summarize their various aspects (experimental synthesis, artificial single GBs, multiscale experimental data acquisition via electron microscopy, formation process modeling, property description modeling, 3D reconstruction, and data-driven design methods). Specifically, we discuss a mechanochemical process involving high-energy milling, in situ observation of microstructural formation using 3D scanning transmission electron microscopy, phase-field modeling coupled with Bayesian data assimilation, nano-orientation analysis via scanning precession electron diffraction, semantic segmentation using neural network models, and the Bayesian-optimization-based process design using BOXVIA software. As a proof of concept, a researcher- and data-driven process design methodology is applied to a polycrystalline iron-based superconductor to evaluate its bulk magnet properties. Finally, future challenges and prospects for data-driven material development and iron-based superconductors are discussed.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2436347"},"PeriodicalIF":7.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143024414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Poly(_L-lysine)-<i>block</i>-poly(ethylene glycol)-<i>block</i>-poly(_L-lysine) triblock copolymers for the preparation of flower micelles and their irreversible hydrogel formation.","authors":"Yuta Koda, Yukio Nagasaki","doi":"10.1080/14686996.2024.2432856","DOIUrl":"https://doi.org/10.1080/14686996.2024.2432856","url":null,"abstract":"<p><p>Poly(_L-lysine)-<i>block</i>-poly(ethylene glycol)-<i>block</i>-poly(_L-lysine) (PLys-<i>block</i>-PEG-<i>block</i>-PLys) triblock copolymers formed polyion complex (PIC) with poly(acrylic acid) (PAAc) or sodium poly(styrenesulfonate) (PSS), leading to the formation of flower micelle-type nanoparticles (Nano^Lys/PAAc or Nano^Lys/PSS) with tens of nanometers size in water at a polymer concentration of 10 mg/mL. The flower micelles exhibited irreversible temperature-driven sol-gel transitions at physiological ionic strength, even at low polymer concentrations such as 40 mg/mL, making them promising candidates for injectable hydrogel applications. Rheological studies showed that the chain length of PLys segments and the choice of polyanions significantly impacted irreversible hydrogel formation, with PSS being superior to PAAc for the formation. The incorporation of silica gel nanoparticles into the PIC flower micelles also resulted in irreversible gelation phenomena. The highest storage modulus exceeded 10 kPa after gelation, which is sufficient for practical applications. This study demonstrates the potential of these PIC-based hydrogels as biomaterials with tunable properties for biomedical applications.</p>","PeriodicalId":21588,"journal":{"name":"Science and Technology of Advanced Materials","volume":"26 1","pages":"2432856"},"PeriodicalIF":7.4,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142954293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}