Copertina

Bridging Theory and Experiment in Materials Discovery: Machine-Learning-Assisted Prediction of Synthesizable Structures

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xin, Yu, Liu, Peng, Xie, Zhuohang, Mi, Wenhui, Gao, Pengyue, Zhao, Hong Jian, Lv, Jian, Wang, Yanchao, Ma, Yanming
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Materials Science Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Theory of polarization-switchable electrical conductivity anisotropy in nonpolar semiconductors
di: Zhao, Hong Jian, et al.
Pubblicazione: (2024)

Deep learning generative model for crystal structure prediction
di: Luo, Xiaoshan, et al.
Pubblicazione: (2024)

High-Pressure Crystal Structure Database
di: Wang, Zhenyu, et al.
Pubblicazione: (2026)

Recent advancements and challenges in orbital‐free density functional theory
di: Qiang Xu, et al.
Pubblicazione: (2024)

Projecting Molecules into Synthesizable Chemical Spaces
di: Luo, Shitong, et al.
Pubblicazione: (2024)

Nonlocal free-energy density functional for warm dense matter
di: Ma, Cheng, et al.
Pubblicazione: (2024)

CrystalFlow: A Flow-Based Generative Model for Crystalline Materials
di: Luo, Xiaoshan, et al.
Pubblicazione: (2024)

Remarkable Optoelectronic Characteristics of Synthesizable Square‐Octagon Haeckelite Structures: Machine Learning Materials Discovery
di: Ehsan Alibagheri, et al.
Pubblicazione: (2024)

A Synthesizability-Guided Pipeline for Materials Discovery
di: Prein, Thorben, et al.
Pubblicazione: (2025)

Self-Optimizing Machine Learning Potential Assisted Automated Workflow for Highly Efficient Complex Systems Material Design
di: Li, Jiaxiang, et al.
Pubblicazione: (2025)

The nature of polar distortions in ferroelectrics
di: Zhao, Hong Jian, et al.
Pubblicazione: (2025)

Fast and stable tight-binding framework for nonlocal kinetic energy density functional reconstruction in orbital-free density functional calculations
di: Chen, Yongshuo, et al.
Pubblicazione: (2024)

Remarkable Optoelectronic Characteristics of Synthesizable Square‐Octagon Haeckelite Structures: Machine Learning Materials Discovery (Adv. Funct. Mater. 27/2024)
di: Ehsan Alibagheri, et al.
Pubblicazione: (2024)

Engineering ferroelectricity in monoclinic hafnia
di: Zhao, Hong Jian, et al.
Pubblicazione: (2023)

Recent Advances in Machine Learning‐Assisted Design and Development of Polymer Materials
di: Longyu Ma, et al.
Pubblicazione: (2025)

The anti-symmetric and anisotropic symmetric exchange interactions between electric dipoles in hafnia
di: Yu, Longju, et al.
Pubblicazione: (2023)

Impact of Data Bias on Machine Learning for Crystal Compound Synthesizability Predictions
di: Davariashtiyani, Ali, et al.
Pubblicazione: (2024)

Electrically switchable non-relativistic Zeeman spin splittings in collinear antiferromagnets
di: Yu, Longju, et al.
Pubblicazione: (2025)

Bridging Crystal Structure and Material Properties via Bond-Centric Descriptors
di: Zhang, Jian-Feng, et al.
Pubblicazione: (2026)

Systematic study of one-point kinetic energy density functionals for atomic nuclei
di: Shang, Tian Shuai, et al.
Pubblicazione: (2026)

Evaluating Molecule Synthesizability via Retrosynthetic Planning and Reaction Prediction
di: Liu, Songtao, et al.
Pubblicazione: (2024)

Discovery of High-Temperature Superconducting Ternary Hydrides via Deep Learning
di: Wang, Xiaoyang, et al.
Pubblicazione: (2025)

Synthesizability Prediction of Crystalline Structures with a Hierarchical Transformer and Uncertainty Quantification
di: Ebrahimzadeh, Danial, et al.
Pubblicazione: (2025)

Beyond Predicted ZT: Machine Learning Strategies for the Experimental Discovery of Thermoelectric Materials
di: Athar, Shoeb, et al.
Pubblicazione: (2026)

Conditional Generative Modeling for Amorphous Multi-Element Materials
di: Li, Honglin, et al.
Pubblicazione: (2025)

Rapid Assessment of Virtually Synthesizable Chemical Structures via Support Vector Machine Models
di: Yuto Iwasaki, et al.
Pubblicazione: (2025)

General theory for longitudinal nonreciprocal charge transport
di: Zhao, Hong Jian, et al.
Pubblicazione: (2024)

Anomalous Hall effect from nonlinear magnetoelectric coupling
di: Yu, Longju, et al.
Pubblicazione: (2024)

Is Large Language Model All You Need to Predict the Synthesizability and Precursors of Crystal Structures?
di: Song, Zhilong, et al.
Pubblicazione: (2024)

A Novel Approach to Eliminating Hallucinations in Large Language Model-Assisted Causal Discovery
di: Sng, Grace, et al.
Pubblicazione: (2024)

A Synthesizable RTL Implementation of Predictive Coding Networks
di: Oh, Timothy
Pubblicazione: (2026)

Machine Learning‐Based Distraction‐Free Method for Measuring the Optical Displacement of Long‐Span Bridge Structures
di: Shanshan Yu, et al.
Pubblicazione: (2024)

Bridging the Synthesizability Gap in Perovskites by Combining Computations, Literature Data, and PU Learning
di: Desai, Rushik, et al.
Pubblicazione: (2025)

Accelerating Complex Materials Discovery with Universal Machine-Learning Potential-Driven Structure Prediction
di: An, Yuqi, et al.
Pubblicazione: (2026)

Bridging Theory and Data: Correcting Nuclear Mass Models with Interpretable Machine Learning
di: Lu, Yanhua, et al.
Pubblicazione: (2026)

The influence of specimen size and strength on the shock properties of concretes: Experimental and mesomechanical analysis
di: Mei Li, et al.
Pubblicazione: (2025)

Copula Entropy: Theory and Applications
di: Ma, Jian
Pubblicazione: (2025)

Semiconducting Borophene Realized via Hydrogenation‐Driven Structural Reconstruction
di: Meiling Xu, et al.
Pubblicazione: (2025)

Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
di: Gao, Wenhao, et al.
Pubblicazione: (2024)

Data-driven design of high-temperature superconductivity among ternary hydrides under pressure
di: Jiang, Bowen, et al.
Pubblicazione: (2024)