Wan‐Jian Yin

Engineering · Physical Sciences

61h-index18.7kcitations223works10.62yr avg
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Research Topics

Perovskite Materials and Applications(87), Chalcogenide Semiconductor Thin Films(74), Quantum Dots Synthesis And Properties(63), Machine Learning in Materials Science(33), Graphene research and applications(30)

Publications223 total

Discovery of Interpretable Physical Laws in Materials via Language-Model-Guided Symbolic Regression
arXiv (Cornell University)·2026Open Access
Discovery of Interpretable Physical Laws in Materials via Language-Model-Guided Symbolic Regression
arXiv (Cornell University)·2026Open Access
Water-Promoted Molar-Level Photocatalysis and Spontaneous Product Separation with Near-Unity Quantum Efficiency
Journal of the American Chemical Society·2025
Trace Oxygen‐Assisted Synthesis of High‐Quality Graphene with Improved Electrical Performance
Advanced Materials·2025· 2 cited
Atomistic and Oxophilic Ce Raises the Inertia of CO Intermediates Toward Enhanced Electrocatalytic Methanation
Small·2025
Machine-Learning Potential Molecular Dynamics Reveals the Critical Role of Flexibility in Solid–Liquid Nanofluidic Friction
ACS Nano·2025· 1 cited
Controllable synthesis and application exploration of graphene materials
Chinese Science Bulletin (Chinese Version)·2025Open Access
Paradigm shift in materials science driven by artificial intelligence: methods, platforms, and frontiers of applications
Chinese Science Bulletin (Chinese Version)·2025Open Access
Growth mechanism of graphene-skinned glass fibre fabrics driven by various carbon sources
Nano Research·2025· 1 citedOpen Access
Catalytic mechanism towards CVD-grown wafer-size graphene on 4H-SiC (0001) and ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="mathml_Z-20250725101211" display="inline" overflow="scroll"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mn mathvariant="bold">000</mml:mn> </mml:mrow> <mml:mover> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mn mathvariant="bold">1</mml:mn> </mml:mrow> <mml:mo accent="false">¯</mml:mo> </mml:mover> </mml:mrow> </mml:math>) using dimer carbon sources
Nano Research·2025Open Access
De Novo Inverse Design Superhard C–N Compounds via Global Machine Learning Interatomic Potentials and Multiobjective Optimization Algorithm
The Journal of Physical Chemistry Letters·2025· 1 cited
Elemental augmentation of machine learning interatomic potentials
Computational Materials Today·2025· 2 citedOpen Access
Kinetic Process of Graphene Growth from Dual‐Carbon Sources on Alpha Alumina
Small·2024· 1 cited
Interfacial Coupling Induced Discrete Orientation of Epitaxial Graphene on High‐Index Cu Substrates
Advanced Functional Materials·2024· 1 cited
Carbon–Oxygen Radical Assisted Growth of Defect‐Free Graphene Films Using Low‐Temperature Chemical Vapor Deposition
Small·2024· 7 cited
Strain regulation retards natural operation decay of perovskite solar cells
Nature·2024· 123 citedOpen Access
Computational design of energy‐related materials: From first‐principles calculations to machine learning
Wiley Interdisciplinary Reviews Computational Molecular Science·2024· 6 cited
Theoretical investigations on hydroxyl carbon precursor fueled growth of graphene on transition metal substrates
Nano Research·2024· 5 cited
Machine learning enables the discovery of 2D Invar and anti-Invar monolayers
Nature Communications·2024· 7 citedOpen Access
Graphene-skinned alumina fiber fabricated through metalloid-catalytic graphene CVD growth on nonmetallic substrate and its mass production
Nature Communications·2024· 29 citedOpen Access
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Frequent Co-authors

Su‐Huai Wei(19), Yanfa Yan(18), Zhenzhu Li(7), Ji‐Hui Yang(6), Mowafak Al‐Jassim(6), Tingting Shi(5), Qingde Sun(5), Wallace C. H. Choy(5), Xin-Gao Gong(5), Yelong Wu(3), Rui Chen(3), Xiwen Chen(3), Ji‐Sang Park(3), Xia Zhou(3), Jingyu Sun(3), Baicheng Weng(2), Zhilong Song(2), Qingyu Yan(2), Houwen Tang(2), John A. Turner(2)