Accounts of materials research最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":14.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/mrv006i005_1938591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144447723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biphen[n]arene-Based Supramolecular Materials","authors":"Zhixue Liu, Junyi Chen and Chunju Li*, ","doi":"10.1021/accountsmr.5c00071","DOIUrl":"10.1021/accountsmr.5c00071","url":null,"abstract":"<p >Macrocycles play pivotal roles in supramolecular chemistry and materials science because of their distinctive molecular recognition capabilities and versatile applications in self-assembly. However, traditional macrocycles, such as cyclodextrins, calixarenes, cucurbiturils, and pillararenes, have inherent limitations in terms of cavity size and structural variety, which restrict their ability to encapsulate guest molecules of varying sizes and their potential in constructing multifunctional materials. To address these challenges, our group has developed a simple, universal, and modular strategy for constructing functional macrocycles, termed biphen[<i>n</i>]arenes. This approach leverages structure- or function-oriented modular replacement of reactive, functional, and linking modules. Therefore, biphen[<i>n</i>]arenes with customized cavity size and molecule depth can effectively encapsulate guests from small molecules to biomacromolecules. On the other hand, different from modification of side chains, incorporation of functional primitives into the biphen[<i>n</i>]arene scaffold can leave active sites on both edges to induce additional moieties to improve recognition potency or integrate extra application functionality. These characteristics provide significant advantages in the construction of diverse supramolecular materials.</p><p >This Account summarizes the research progress on biphen[<i>n</i>]arene-based supramolecular materials across three major areas: (a) Biomedical materials. By customizing the sizes, shapes, and portal substituents of biphen[<i>n</i>]arenes to match the structural features of biomedical molecules such as drugs, bioactive peptides, and macromolecular biotoxins, we have constructed a series of water-soluble biphen[<i>n</i>]arenes with exceptional recognition capabilities. These biphen[<i>n</i>]arenes demonstrate a range of promising applications, including reversing neuromuscular blockers, combating bacterial infections, delivering peptide agents, detoxifying macromolecular biotoxins, and disassembling fibrous proteins. (b) Luminescent materials. We developed a series of luminescent macrocycles by introducing diverse fluorophores and phosphors onto biphen[<i>n</i>]arene skeletons, which displayed enhanced emission compared to the corresponding monomers. The modular approach provides an efficient and universal strategy for enhancing solid-state emission, termed macrocyclization-induced fluorescence/phosphorescence enhancement. Additionally, structurally diverse luminescent macrocycle cocrystals have been obtained, where solid-state luminescence can be precisely tuned by controlling donor–acceptor stoichiometric ratios and molecular packing modes. (c) Adsorption and separation materials. Biphen[<i>n</i>]arenes and cages exhibit impressive separation capabilities for industrially important mixtures owing to their advanced architectures and diverse supramolecular interactions. These include the separation of <i>cis</i>","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"765–778"},"PeriodicalIF":14.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Assisted Material Discovery: A Small Data Approach","authors":"Qionghua Zhou*,&nbsp;Xinyu Chen and Jinlan Wang*,&nbsp;","doi":"10.1021/accountsmr.1c00236","DOIUrl":"10.1021/accountsmr.1c00236","url":null,"abstract":"<p >The data-driven paradigm, represented by the famous machine learning paradigm, is revolutionizing the way materials are discovered. The inductive nature of the data-driven approach gives it great speed of prediction but also brings with it a heavy reliance on material data. However, unlike its success with text and images, which are supported by big data, materials data tend to be small data. Building a large database of materials is a good solution but not a permanent one. The cost of materials data is much higher than that of text or images, and the size of the materials database at this stage is far from sufficient. We will continue to face a shortage of materials data for a long time to come, making small data approaches necessary for machine learning based materials discovery.</p><p >In this Account, we focus on small data strategies developed over the past few years and the scenarios in which they are used. In the first part, we discuss two general strategies, active learning and transfer learning, which are ways of adding new data efficiently and using existing data, respectively. The key to active learning is the sampling strategy, which determines the speed of convergence and the predictive range of the machine learning model. For transfer learning, adversarial training is introduced to extend the scope of this strategy, allowing for knowledge transfer across materials and properties. We also discuss other small data approaches for special cases, such as material search with zero initial data and model training on multisource experimental data. In the second part, we focus on the construction of material descriptors and reduction of their dimensionality. We have developed a crystal-graph-based descriptor specifically for two-dimensional materials. It can encode both structural and atomic information and also has a flexible multilayer format for different target properties. Since the dimensionality of the material descriptor is limited by the amount of data, specially designed dimensionality reduction strategies are also discussed. In the third part, we discuss model interpretability. Several examples are given to illustrate how model-based and data-based interpretation strategies can be used to help us understand the machine learning model and its prediction results.</p><p >The Account concludes with our perspectives on the latest developments in generative AI (in particular, large language model and diffusion model) and explainable AI, which could be powerful tools in the future of machine learning assisted material discovery.</p>","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"685–694"},"PeriodicalIF":14.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144122766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Derivative Chemistry of Ag29 Nanoclusters","authors":"Honglei Shen,&nbsp;Xi Kang* and Manzhou Zhu*,&nbsp;","doi":"10.1021/accountsmr.5c00083","DOIUrl":"10.1021/accountsmr.5c00083","url":null,"abstract":"&lt;p &gt;Metal nanoclusters represent a unique class of nanomaterials with monodisperse sizes, atomically precise structures, and rich physicochemical properties, and they find wide applications in optics, catalysis, and biomedicine. The strong quantum size effects and discrete electronic energy levels endow metal nanoclusters with structure-dependent properties, where any perturbation of their compositions or structures induces significant variations in their properties. This makes the research of metal nanoclusters particularly exciting but also challenging, as small changes in their atomic composition or arrangement can result in substantial differences in their behavior. As a result, the study of metal nanoclusters follows a node-style research pattern, wherein major breakthroughs often lead to new insights into their structural and functional properties. However, despite these advances, the systematic exploration of these materials remains highly challenging. In recent years, there has been increasing interest in the development of unified theoretical models that can predict and control the properties of metal nanoclusters, potentially making them ideal candidates for programmable nanomaterials. Key examples of well-studied nanoclusters include Au&lt;sub&gt;25&lt;/sub&gt;(SR)&lt;sub&gt;18&lt;/sub&gt; and Ag&lt;sub&gt;44&lt;/sub&gt;(SR)&lt;sub&gt;30&lt;/sub&gt;, which have provided valuable insights into the fundamental principles of metal nanocluster chemistry. Nevertheless, given the vast differences observed among various cluster frameworks, there is an urgent need to develop new models and explore versatile approaches for the preparation of nanoclusters with tunable functionalities. In this regard, our research group has focused on advancing the derivative chemistry of Ag&lt;sub&gt;29&lt;/sub&gt;-templated nanoclusters.&lt;/p&gt;&lt;p &gt;In this Account, we emphasize our progress in investigating the derivative chemistry of Ag&lt;sub&gt;29&lt;/sub&gt; nanoclusters, focusing on several key areas, such as their controlled preparation, structural determination, molecular-level structural regulation, supramolecular ordered assembly, and the exploration of structure–property relationships. Initially, we provide a comprehensive overview of the structural manipulation of Ag&lt;sub&gt;29&lt;/sub&gt; nanoclusters on the molecular scale, highlighting various molecular operations that enable precise control over their properties. These operations include kernel alloying, ligand engineering, and counterion regulation, which serve as fundamental strategies for tuning the composition and structure of these nanoclusters. Tens of Ag&lt;sub&gt;29&lt;/sub&gt; cluster derivatives with comparable compositions and constructions are presented, and the corresponding structure–property correlations are disclosed as well. Then, we summarize the research progress regarding Ag&lt;sub&gt;29&lt;/sub&gt; clusters at the supramolecular level, which involves the self-assembly of Ag&lt;sub&gt;29&lt;/sub&gt; nanoclusters into supracrystalline aggregates or host–guest assemblies in both crystalline and sol","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"779–793"},"PeriodicalIF":14.7,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144104308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrochemical Performance of Li Metal Anodes in Conjunction with LLZO Solid-State Electrolyte","authors":"Kostiantyn V. Kravchyk*,&nbsp;Matthias Klimpel,&nbsp;Huanyu Zhang and Maksym V. Kovalenko*,&nbsp;","doi":"10.1021/accountsmr.5c00124","DOIUrl":"10.1021/accountsmr.5c00124","url":null,"abstract":"","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 7","pages":"794–798"},"PeriodicalIF":14.7,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/accountsmr.5c00124","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144104312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chemically Inert Atomic Passivation Shell for Stable Semiconductor Nanocrystals","authors":"Congyang Zhang*,&nbsp;Zhichun Li,&nbsp;Mingming Liu,&nbsp;Qun Wan,&nbsp;Weilin Zheng and Liang Li*,&nbsp;","doi":"10.1021/accountsmr.4c00366","DOIUrl":"10.1021/accountsmr.4c00366","url":null,"abstract":"&lt;p &gt;The 2023 Nobel Prize in Chemistry has recognized the important discovery and development of QDs. Colloidal semiconductor nanocrystals (NCs), known as quantum dots (QDs), have attracted increased attention for a wide range of potential applications, such as displays, lighting, photovoltaics, and biological imaging, because of their high quality and size-dependent optical properties. To obtain high-quality semiconductor NCs with reduced surface defects and boosted photoluminescence emission, semiconductor shell-based surface engineering is a commonly used strategy. However, the terminated semiconductor surface is likely not immune to photodegradation or chemical degradation behavior. Insulating matrix encapsulation was demonstrated to be an alternative way to resolve the stability issue, but the bulk and insulating feature of the matrix could restrain the electrical activity and solution processability for device applications of NCs. As a compromise, the chemically inert atomic passivation shell (CIAPS) could be the ideal approach to break the above-mentioned trade-off and promote practical optoelectronic applications. The CIAPS on semiconductor NCs can protect the NCs from the surrounding environment physically and isolate photogenerated excitons from the external photochemical reactions while maintaining access to charge injection or transport for device applications.&lt;/p&gt;&lt;p &gt;In this Account, we summarize our recent progress in the CIAPS strategy on semiconductor NCs. First, we highlight the general consideration of the shell material of CIAPS from the aspects of material stability, the significance of the atomic shell coating, and nondestructive synthesis. Based on these guidelines, chemically stable metal oxide and metallic salt with an atomic thin layer are selected as target CIAPS, and in situ doping (and chemical oxidation) and post-treatment are suitable methodologies. Specifically, we systematically discuss the stabilization effect of the CIAPS strategies on semiconductor NCs, including CdSe, InP, and CsPbX&lt;sub&gt;3&lt;/sub&gt;. Second, some advanced characterization methods are included in the discussion as well, such as high-resolution aberration-corrected scanning transmission electron microscopy, X-ray absorption near edge structure and extended X-ray absorption fine structure spectroscopy, chemical etching, and related depth-dependent elemental analysis, facilitating the fundamental understanding of the CIAPS strategy and stabilization mechanism on semiconductor NCs. Third, the CIAPS strategy enables the stabilization of semiconductor NCs on a single-particle level and retains their electrical properties, showing great application potential. Therefore, the important role and potential application of CIAPS are discussed, including electroluminescent LEDs and radiation detection. Finally, the challenges and opportunities are prospected as well to guide the future development of the CIAPS strategy and derived semiconductor NCs. We anticipate ","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"708–719"},"PeriodicalIF":14.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144087962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenothiazine Polymers as Versatile Electrode Materials for Next-Generation Batteries","authors":"Birgit Esser*,&nbsp;Isabel H. Morhenn and Michael Keis,&nbsp;","doi":"10.1021/accountsmr.5c00053","DOIUrl":"10.1021/accountsmr.5c00053","url":null,"abstract":"<p >Organic battery electrode materials are key enablers of different postlithium cell chemistries. As a p-type compound with up to two reversible redox processes at relatively high potentials of 3.5 and 4.1 V vs. Li/Li⁺, phenothiazine is an excellently suited redox-active group. It can easily be functionalized and incorporated into polymeric structures, a prerequisite to obtain insolubility in liquid battery electrolytes. Phenothiazine tends to exhibit π-interactions (π*−π*-interactions) to stabilize its radical cationic form, which can increase the stability of the oxidized form but can also strongly influence its cycling performance as a battery electrode material. In recent years, we investigated a broad range of phenothiazine-based polymers as battery electrode materials, providing insight into the effect of π-interactions on battery performance, leading to design principles for highly functional phenothiazine-based polymers, and enabling the investigation of full cells. We observed that π-interactions are particularly expressed in “mono”-oxidized forms of poly(3-vinyl-<i>N</i>-methylphenothiazine) (PVMPT) and are enabled in the battery electrode due to the solubility of oxidized PVMPT in many carbonate-based liquid electrolytes. PVMPT dissolves during charge and is redeposited during discharge as a stable film on the positive electrode, however, still retaining half of its charge. This diminishes its available specific capacity to half of the theoretical value. We followed three different strategies to mitigate dissolution and inhibit the formation of π-interactions in order to access the full specific capacity for the one-electron process: Adjusting the electrolyte composition (type and ratio of cyclic vs. linear carbonate), encapsulating PVMPT in highly porous conductive carbons or cross-linking the polymer to X-PVMPT. All three strategies are excellently suited to pursue full-cell concepts using PVMPT or X-PVMPT as positive electrode material. The extent of π-interactions could also be modified by structural changes regarding the polymer backbone (polystyrene or polynorbornene) or exchanging the heteroatom sulfur in phenothiazine by oxygen in phenoxazine. By changing the molecular design and attaching electron-donating methoxy groups to the phenothiazine units, its second redox process can be reversibly enabled, even in carbonate-based electrolytes. Studies by us as well as others provided a selection of high-performing phenothiazine polymers. Their applicability was demonstrated as positive electrode in full cells of different configurations, including dual-ion battery cells using an inorganic or organic negative electrode, anion-rocking-chair cells as examples of all-organic batteries, or even an aluminum battery with a performance exceeding that of aluminum-graphite battery cells. In changing the design concept to conjugated phenothiazine polymers, a higher intrinsic semiconductivity can result, enabling the use of a lesse","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"754–764"},"PeriodicalIF":14.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/accountsmr.5c00053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144087959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chemistry of Two-Dimensional Materials for Sustainable Energy and Catalysis","authors":"Xiao Wang,&nbsp;Wei Gu,&nbsp;Pratteek Das,&nbsp;Chenyang Li,&nbsp;Zhong-Tao Li* and Zhong-Shuai Wu*,&nbsp;","doi":"10.1021/accountsmr.4c00406","DOIUrl":"10.1021/accountsmr.4c00406","url":null,"abstract":"<p >Two-dimensional (2D) materials form a large and diverse family of materials with extremely rich compositions, ranging from graphene to complex transition metal derivatives. They exhibit unique physical, chemical, and electronic properties, making 2D materials highly promising in the fields of sustainable energy storage and electrocatalysis. Although significant progress has been made in the design and performance optimization of 2D materials, challenges persist, particularly in energy storage and electrocatalysis. A key issue is the restacking or aggregation of these materials in the powder form, which hinders ion transport and reduces their overall performance by limiting the effective surface area. In this Account, we delve into the latest advancements made by our team in the chemistry of 2D materials toward sustainable electrochemical energy storage and catalysis. We begin by highlighting some of the representative 2D materials developed by our team, such as fluorine-modified graphene and transition metal telluride nanosheets. These materials, with their atomic-scale thickness, offer significant advantages over traditional bulk materials by circumventing issues such as limited active surface area, extended ion transport pathways, and complex manufacturing processes, thereby providing innovative approaches for the development of high-performance materials. Next, the key synthesis strategies that have been pivotal in our research are summarized. Techniques such as electrochemical exfoliation, solid-state lithiation and exfoliation, and ion-adsorption chemical strategies have enabled precise control over the ionic and electronic conductivities, lateral dimensions, and internal atomic configurations of 2D materials. These methodologies not only facilitate the preparation of 2D materials with tailored properties, but also support the scalable production of high-quality materials. Furthermore, we outline the broad applications of 2D energy materials across various domains. In alkali-based batteries, these materials have been instrumental in enhancing battery performance, including extending the cycle life and improving the charge–discharge efficiency. They also contribute to increased energy and power densities in aqueous-based batteries and supercapacitor–battery hybrid devices. In the realm of metal-free anodes, they play a crucial role in inhibiting metal dendrite growth, thereby enhancing battery safety. Additionally, in energy catalysis, they demonstrate superior catalytic activity, promoting efficient energy conversion. In microscale electrochemical energy storage devices, they meet the demands for high power and energy density, propelling the advancement of miniaturized energy storage solutions. Lastly, we address the critical challenges confronting 2D energy materials and offer a perspective on future directions. While significant progress has been achieved in 2D material research, challenges persist in synthesis, performance optimizati","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"695–707"},"PeriodicalIF":14.7,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143945993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surface-Active Catalysts for Interfacial Gas–Liquid–Solid Reactions","authors":"Kang Wang,&nbsp;Badri Vishal and Marc Pera-Titus*,&nbsp;","doi":"10.1021/accountsmr.5c00026","DOIUrl":"10.1021/accountsmr.5c00026","url":null,"abstract":"&lt;p &gt;Multiphase reactions combining gas and liquid phases and a solid catalyst are widespread in the chemical industry. The reactions are typically affected by the low gas solubility in liquids and poor mass transfer from the gas phase to the liquid, especially for fast reactions, leading to much lower activity than the intrinsic catalytic activity. In practice, high pressure, temperature, and cosolvents are required to increase the gas solubility and boost the reaction rate. Gas–liquid–solid (G-L-S) microreactors based on particle-stabilized (Pickering) foams rather than conventional surfactant-stabilized foams can increase the contact between the gas and liquid phases, together with surface-active catalytic particles, and dramatically accelerate G-L-S reactions. Unlike surfactants, surface-active catalytic particles can be recycled and reused and reduce coalescence, Ostwald ripening, and aggregation by adsorbing selectively at the G-L interface, promoting stability.&lt;/p&gt;&lt;p &gt;In this Account, we present first a taxonomy of microstructured G-L-(S) interfaces to build G-L-S microreactors (catalytic membrane contactors, microdroplets, micromarbles, microbubbles, and particle-stabilized bubbles/foams). Within this taxonomy, we provide a critical appraisal of surface-active catalytic particles to engineer particle-stabilized aqueous and oil foams. We address the fundamental thermodynamics and dynamics aspects of particle adsorption at the G-L interface and examine the foaming stabilization mechanisms. We further enumerate the possible interactions between particles and G-L interfaces and elucidate how the interfacial self-assembly of surface-active particles can discourage foam destabilization mechanisms. We also discuss strategies for the synthesis of surface-active particles, including surface modification of preformed hydrophilic particles, synthesis of organic–inorganic hybrids, coprecipitation, and bottom-up synthesis, including methods for depositing catalytic centers. Various types of particles capable of stabilizing foams are identified including silica particles modified with hydrophobic and hydrophilic chains, silica particles functionalized with oleophobic and oleophilic chains, biphenyl-bridged organosilica particles, and surface-active polymers. Finally, we highlight recent advances from our group, including catalytic oxidation, hydrogenation, and tandem reactions, facilitated by tailor-designed surface-active particles in aqueous/nonaqueous foam. The relationship between the structure, properties, and foaming performance of surface-active particles, along with their catalytic efficiency within foams, is elucidated. It is our hope that this Account will inspire innovative designs of surface-active particles with tailored properties for the advancement of industrially relevant multiphase reactions. Looking ahead, developing data-driven computational tools would be highly beneficial, allowing the &lt;i&gt;in silico&lt;/i&gt; design of particles with tai","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"720–729"},"PeriodicalIF":14.7,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/accountsmr.5c00026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging Microelectronic Materials by Design: Navigating Combinatorial Design Space with Scarce and Dispersed Data","authors":"Hengrui Zhang,&nbsp;Alexandru B. Georgescu,&nbsp;Suraj Yerramilli,&nbsp;Christopher Karpovich,&nbsp;Daniel W. Apley,&nbsp;Elsa A. Olivetti,&nbsp;James M. Rondinelli* and Wei Chen*,&nbsp;","doi":"10.1021/accountsmr.5c00011","DOIUrl":"10.1021/accountsmr.5c00011","url":null,"abstract":"&lt;p &gt;The increasing demands of sustainable energy, electronics, and biomedical applications call for next-generation functional materials with unprecedented properties. Of particular interest are emerging materials that display exceptional physical properties, making them promising candidates for energy-efficient microelectronic devices. As the conventional Edisonian approach becomes significantly outpaced by growing societal needs, emerging computational modeling and machine learning methods have been employed for the rational design of materials. However, the complex physical mechanisms, cost of first-principles calculations, and the dispersity and scarcity of data pose challenges to both physics-based and data-driven materials modeling. Moreover, the combinatorial composition–structure design space is high-dimensional and often disjoint, making design optimization nontrivial.&lt;/p&gt;&lt;p &gt;In this Account, we review a team effort toward establishing a framework that integrates data-driven and physics-based methods to address these challenges and accelerate material design. We begin by presenting our integrated material design framework and its three components in a general context. (1) Using text mining and natural language processing techniques, our framework first extracts and organizes relevant information dispersed in the literature. (2) From this initial database of relevant materials, data-driven models can be trained and subsequently employed to perform virtual screening of the unknown materials space. This virtual screening process can identify promising materials families for further investigation, thus narrowing down the candidate space. (3) Within the identified materials families, a Bayesian optimization-based adaptive discovery workflow is applied to search for materials with optimal properties. To extend the capability of Bayesian optimization, which was previously restricted to small data and numerical variables, we developed a family of uncertainty-aware machine learning methods for mixed numerical and categorical variables.&lt;/p&gt;&lt;p &gt;We then provide an example of applying this materials design framework to metal–insulator transition (MIT) materials, a specific type of emerging material with practical importance in next-generation memory technologies. We identify multiple new materials that may display this property in the lacunar spinel and Ruddlesden–Popper perovskite families and propose pathways for their synthesis. The classifiers used to identify new possible MIT materials also identified previously unknown features that may be used for predictive theory for this class of materials. For example, we have identified descriptors derived from ionicity and atom sizes as indicators to MIT behavior.&lt;/p&gt;&lt;p &gt;Finally, we identify some outstanding challenges in data-driven materials design, such as material data quality issues, property–performance mismatch, and validation and deployment. We seek to raise awareness of these overlooked issues ","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"6 6","pages":"730–741"},"PeriodicalIF":14.7,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143910162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}