Deeper Insights into Flame Retardancy of Polymers by Interpretable, Quantifiable, yet Accurate Machine-learning Model DOI
Ran Wang, Teng Fu,

Yajie Yang

et al.

Polymer Degradation and Stability, Journal Year: 2024, Volume and Issue: unknown, P. 110981 - 110981

Published: Sept. 1, 2024

Language: Английский

When Machine Learning Meets 2D Materials: A Review DOI Creative Commons
Bin Lu, Yuze Xia,

Yuqian Ren

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(13)

Published: Jan. 26, 2024

Abstract The availability of an ever‐expanding portfolio 2D materials with rich internal degrees freedom (spin, excitonic, valley, sublattice, and layer pseudospin) together the unique ability to tailor heterostructures made by in a precisely chosen stacking sequence relative crystallographic alignments, offers unprecedented platform for realizing design. However, breadth multi‐dimensional parameter space massive data sets involved is emblematic complex, resource‐intensive experimentation, which not only challenges current state art but also renders exhaustive sampling untenable. To this end, machine learning, very powerful data‐driven approach subset artificial intelligence, potential game‐changer, enabling cheaper – yet more efficient alternative traditional computational strategies. It new paradigm autonomous experimentation accelerated discovery machine‐assisted design functional heterostructures. Here, study reviews recent progress such endeavors, highlight various emerging opportunities frontier research area.

Language: Английский

Citations

47

Recent advances in zinc-ion dehydration strategies for optimized Zn–metal batteries DOI
Haoyu Li, Sijie Li,

Ruilin Hou

et al.

Chemical Society Reviews, Journal Year: 2024, Volume and Issue: 53(15), P. 7742 - 7783

Published: Jan. 1, 2024

Aqueous Zn-metal batteries have attracted increasing interest for large-scale energy storage owing to their outstanding merits in terms of safety, cost and production. However, they constantly suffer from inadequate density poor cycling stability due the presence zinc ions fully hydrated solvation state. Thus, designing dehydrated structure can effectively address current drawbacks aqueous batteries. In this case, considering lack studies focused on strategies dehydration ions, herein, we present a systematic comprehensive review deepen understanding zinc-ion regulation. Two fundamental design principles component regulation pre-desolvation are summarized environment formation interfacial desolvation behavior. Subsequently, specific strategy based distinct carefully discussed, including preparation methods, working mechanisms, analysis approaches performance improvements. Finally, general summary issues addressed using strategies, four critical aspects promote presented as an outlook, involving updating (de)solvation theories, revealing evolution, enhancing techniques developing functional materials. We believe that will not only stimulate more creativity optimizing electrolytes but also provide valuable insights into other battery systems.

Language: Английский

Citations

39

Advanced Organic–Inorganic Hybrid Materials for Optoelectronic Applications DOI
Kun Zhou,

Bingyu Qi,

Zhongwei Liu

et al.

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 9, 2024

Abstract Research on organic–inorganic hybrid materials (OIHMs) has experienced explosive growth in the past decades. The diversity of organic components allows for introduction various spatial scales, functional groups, and polarities, while inorganic provide higher hardness, heat resistance, stability, their flexible combination facilitates formation diverse structures. Furthermore, simple cost‐effective synthesis methods, such as room temperature solution processes mechanochemical techniques, enable precise control over materials' properties at different thus achieving adjustable structure–performance relationships. This review will discuss recent research progress OIHMs within field optoelectronics related optoelectronic device applications. According to dimension nature interface, this divides into four structural categories. ongoing revealed applications fields solar cells, light‐emitting devices, detectors, memristors. As an outlook, potential perovskite 0D metal halide materials, which are currently most studied, enhancing performance stability is discussed.

Language: Английский

Citations

19

Machine learning for perovskite solar cell design DOI

Hui Zhan,

Min Wang, Xiang Yin

et al.

Computational Materials Science, Journal Year: 2023, Volume and Issue: 226, P. 112215 - 112215

Published: April 30, 2023

Language: Английский

Citations

28

Ramifications of Ion Migration in 2D Lead Halide Perovskites DOI
Preethi Susan Mathew, Junsang Cho, Prashant V. Kamat

et al.

ACS Energy Letters, Journal Year: 2024, Volume and Issue: 9(3), P. 1103 - 1114

Published: Feb. 21, 2024

Lower dimensional or 2D halide perovskites, with their versatile structural and functional properties, are known to improve the performance room temperature stability of perovskite solar cells. One would expect perovskites be more resistant ion migration compared 3D counterparts because presence bulky organic cations. However, recent findings show that indeed is prevalent in similar perovskites. Halide manifests itself segregation under photoirradiation as well exchange between physically paired films different ions. Besides migration, cation spacer cations A-site also seen when 2D/3D subjected light thermal stress. It important recognize importance while incorporating cells other optoelectronic devices, it can detrimental for achieving streamlined long-term stability. This Perspective discusses reports on operational conditions (at elevated given built-in bias) presents a few mitigating strategies.

Language: Английский

Citations

15

Machine Learning for Screening Small Molecules as Passivation Materials for Enhanced Perovskite Solar Cells DOI
Xin Zhang, Bin Ding, Yao Wang

et al.

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(30)

Published: March 27, 2024

Abstract Utilization of small molecules as passivation materials for perovskite solar cells (PSCs) has gained significant attention recently, with hundreds demonstrating effects. In this study, a high‐accuracy machine learning model is established to identify the dominant molecular traits influencing and efficiently screen excellent among molecules. To address challenge limited available dataset, novel evaluation method called random‐extracted recoverable cross‐validation (RE‐RCV) proposed, which ensures more precise reduced error. Among 31 examined features, dipole moment identified, hydrogen bond acceptor count, HOMO‐LUMO gap affecting passivation, offering valuable guidance selection The predictions are experimentally validate three representative molecules: 4‐aminobenzenesulfonamide, 4‐Chloro‐2‐hydroxy‐5‐sulfamoylbenzoic acid, Phenolsulfonphthalein, exhibit capability increase absolute efficiency values by over 2%, champion 25.41%. This highlights its potential expedite advancements in PSCs.

Language: Английский

Citations

10

Trap State Passivation for Stabilizing Perovskite Solar Cells via Multifunctional Molecules DOI Open Access
Rabindranath Garai, Ritesh Kant Gupta, Parameswar Krishnan Iyer

et al.

Accounts of Materials Research, Journal Year: 2023, Volume and Issue: 4(7), P. 560 - 565

Published: June 21, 2023

ADVERTISEMENT RETURN TO ISSUEViewpointNEXTTrap State Passivation for Stabilizing Perovskite Solar Cells via Multifunctional MoleculesRabindranath GaraiRabindranath GaraiDepartment of Chemistry, Indian Institute Technology Guwahati, Guwahati 781 039, Assam, IndiaMore by Rabindranath GaraiView Biographyhttps://orcid.org/0000-0002-1339-8666, Ritesh Kant GuptaRitesh GuptaCentre Nanotechnology, GuptaView Biographyhttps://orcid.org/0000-0002-2125-120X, and Parameswar Krishnan Iyer*Parameswar IyerDepartment IndiaCentre India*[email protected]More IyerView Biographyhttps://orcid.org/0000-0003-4126-3774Cite this: Acc. Mater. Res. 2023, 4, 7, 560–565Publication Date (Web):June 21, 2023Publication History Received17 October 2022Published online21 June 2023Published inissue 28 July 2023https://pubs.acs.org/doi/10.1021/accountsmr.2c00207https://doi.org/10.1021/accountsmr.2c00207article-commentaryACS PublicationsCopyright © 2023 Accounts Materials Research. Co-published ShanghaiTech University American Chemical Society. All rights reserved.Request reuse permissionsArticle Views1463Altmetric-Citations5LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum full text article downloads since November 2008 (both PDF HTML) across all institutions individuals. These metrics regularly updated to reflect usage leading up last few days.Citations number other articles citing this article, calculated Crossref daily. Find more information about citation counts.The Altmetric Attention Score is a quantitative measure attention that research has received online. Clicking on donut icon will load page at altmetric.com with additional details score social media presence given article. how calculated. Share Add toView InAdd Full Text ReferenceAdd Description ExportRISCitationCitation abstractCitation referencesMore Options onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Defects,Layers,Molecules,Passivation,Perovskites Get e-Alerts

Language: Английский

Citations

17

Film-forming polymer nanoparticle strategy for improving the passivation and stability of perovskite solar cells DOI Creative Commons
Zhenyu Jia, Ran Wang, Lei Zhu

et al.

Energy & Environmental Science, Journal Year: 2024, Volume and Issue: 17(19), P. 7221 - 7233

Published: Jan. 1, 2024

Highly deformable crosslinked polymer particles enhance perovskite solar cell passivation and stability by binding distributing throughout the film.

Language: Английский

Citations

8

Surface matrix regulation of perovskite quantum dots for efficient solar cells DOI

Shuhuai Xiao,

Xinyi Mei,

Xiaoliang Zhang

et al.

Energy & Environmental Science, Journal Year: 2024, Volume and Issue: 17(16), P. 5756 - 5794

Published: Jan. 1, 2024

This review comprehensively discusses the latest advances in surface matrix regulation of perovskite quantum dots and proposes opportunities challenges for high-performance solar cells.

Language: Английский

Citations

7

Machine-Learning-Assisted Design of Buried-Interface Engineering Materials for High-Efficiency and Stable Perovskite Solar Cells DOI
Qi Zhang, Han Wang, Qiangqiang Zhao

et al.

ACS Energy Letters, Journal Year: 2024, Volume and Issue: unknown, P. 5924 - 5934

Published: Nov. 20, 2024

Buried-interface engineering is crucial to the performance of perovskite solar cells. Self-assembled monolayers and buffer layers at buried interface can optimize charge transfer reduce recombination losses. However, complex mechanisms difficulty in selecting suitable functional groups pose great challenges. Machine learning (ML) offers a powerful tool for screening identifying effective structures modification. Our ML-driven approach led preparation two promising organic molecules, PAPzO PAPz, which exhibit synergistic interactions with SnO2 perovskites. These molecules decrease trap densities, elongate carrier lifetimes, retard crystallization. PAPzO, stronger binding energy better aligned levels, enables power conversion efficiency (PCE) 26.04% long-term stability, maintaining 91.24% its original PCE after 1,200 h continuous maximum point tracking. This ML-integrated marks significant advancement development efficient stable photovoltaics.

Language: Английский

Citations

6