Anton O. Oliynyk

princeton university

H指数:25

被引数:3,900

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Achieving a Scalable Machine Learning Workflow for Crystal Structure Discovery with Experimental Validations

实现一种可扩展的用于晶体结构发现的机器学习工作流程，并辅以实验验证

Digital Discovery

IF5.6

2026-05-260

OAAI

Disentangling Structural Patterns in Quaternary Germanides with Materials Informatics and Exploratory Synthesis: RE4IrInGe4 (RE = Y; Ce–Nd; Sm; Gd; Ho–Er) Series

利用材料信息学和探索性合成方法解析四元锗化物的结构模式：RE4IrInGe4 (RE = Y; Ce–Nd; Sm; Gd; Ho–Er) 系列

Inorganic Chemistry

IF4.7

2026-03-310

PRE

Improving Thermal Cycling Stability and Magnetocaloric Efficiency via Orbital Competition and Entropy Engineering in Rare-Earth Rhodium Indium Layered Intermetallics

通过轨道竞争和熵工程改善稀土铑铟层状金属间化合物的热循环稳定性和磁热效率

Chemistry of Materials

IF7

2026-02-180

PRE

Exploring Feature Engineering for Crystal Structure Classification: Interactive Applications of PCA and PLS-DA Clustering

探索晶体结构分类的特征工程：PCA和PLS-DA聚类的交互式应用

Journal of Chemical Education

IF2.9

2026-01-010

PRE

Investigating mechanical properties through defect chemistry in hard binary phosphide material Ta3P

通过缺陷化学研究硬质二元磷化物材料Ta₃P的力学性能

SOLID STATE COMMUNICATIONS

IF2.4

2025-11-010

PRE

Dataset of prototype structures adopted by intermetallic compounds with AB stacking

金属间化合物中采用AB堆叠的原型结构数据集

DATA IN BRIEF

IF1.4

2025-10-011

OAAI

Composition and structure analyzer/featurizer for explainable machine-learning models to predict solid state structures

DIGITAL DISCOVERY

IF5.6

2025-01-011

Thermoelectric Material Performance (zT) Predictions with Machine Learning

基于机器学习的热电材料性能 (zT) 预测

ACS APPLIED MATERIALS & INTERFACES

IF8.2

2024-12-170

PRE

Interpretable Machine Learning Model on Thermal Conductivity Using Publicly Available Datasets and Our Internal Lab Dataset

CHEMISTRY OF MATERIALS

IF7

2024-07-032

PRE

The crystal and electronic structure of RE23Co6.7In20.3 (RE = Gd-Tm, Lu): A new structure type based on intergrowth of AlB2-and CsCl-type related slabs

JOURNAL OF ALLOYS AND COMPOUNDS

IF6.3

2024-03-012

OAAI

Interpretable Machine Learning in Solid-State Chemistry, with Applications to Perovskites, Spinels, and Rare-Earth Intermetallics: Finding Descriptors Using Decision Trees

INORGANIC CHEMISTRY

IF4.7

2023-06-307

PRE

Revealing Hidden Patterns through Chemical Intuition and Interpretable Machine Learning: A Case Study of Binary Rare-Earth Intermetallics RX

CHEMISTRY OF MATERIALS

IF7

2023-01-304

PRE

Experimentally validated machine learning predictions of ultralow thermal conductivity for SnSe materials

JOURNAL OF MATERIALS CHEMISTRY C

IF5.1

2023-01-019

PRE

Trends in Bulk Compressibility of Mo2-x,WxBC Solid Solutions

CHEMISTRY OF MATERIALS

IF7

2022-03-080

PRE

Three Rh-rich ternary germanides in the Ce-Rh-Ge system

JOURNAL OF SOLID STATE CHEMISTRY

IF3.5

2021-12-013

PREAI

Ternary Rare-Earth-Metal Nickel Indides RE23Ni7In4 (RE = Gd, Tb, Dy) with Yb23Cu7Mg4-Type Structure

INORGANIC CHEMISTRY

IF4.7

2021-11-214

PREAI

Preface to the special issue on machine learning and data-driven design of materials issue in computational materials science

COMPUTATIONAL MATERIALS SCIENCE

IF3.3

2021-07-010

PREAI

Finding the Next Superhard Material through Ensemble Learning

ADVANCED MATERIALS

IF26.8

2020-12-0455

OAAI

Coloured intermetallic compounds LiCu2Al and LiCu2Ga

有色金属间化合物LiCu2Al和LiCu2Ga

JOURNAL OF SOLID STATE CHEMISTRY

IF3.5

2020-12-015

PREAI

Significant Variability in the Photocatalytic Activity of Natural Titanium-Containing Minerals: Implications for Understanding and Predicting Atmospheric Mineral Dust Photochemistry

ENVIRONMENTAL SCIENCE & TECHNOLOGY

IF11.3

2020-10-1524

PREAI

Anton O. Oliynyk

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