Raymundo Arróyave

Texas A&M University

H指数:57

被引数:1.1万

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Bayesian-optimization-guided discovery of NiTi(Co,Cu,Pd,Hf,Zr) multi-principal element high-temperature shape memory alloys

贝叶斯优化指导的NiTi(Co,Cu,Pd,Hf,Zr)多主元高温形状记忆合金的发现

Acta Materialia

IF9.3

2026-10-310

PRE

Editorial: “High-Entropy Materials”

编者按：“高熵材料”

Materials Letters

IF2.7

2026-09-150

PRE

Toward autonomous experimentation: Bayesian optimization over problem formulation space for accelerated alloy development

面向自主实验：通过问题表述空间的贝叶斯优化加速合金开发

MATERIALS & DESIGN

IF7.9

2026-07-010

OAAI

Microstructure prediction for Ti-22Al-25Nb in laser powder bed fusion

激光粉末床熔融过程中Ti-22Al-25Nb微观结构预测

Computational Materials Science

IF3.3

2026-07-010

OAAI

Superelastic interlocking metasurfaces enabled by additive manufacturing

通过增材制造实现的超弹性互锁超表面

Materials Today

IF22

2026-05-010

PRE

Good enough is better: feasibility vs. Pareto-optimality in alloy design

足够好是更好的：合金设计中可行性与帕累托最优性的比较

Digital Discovery

IF5.6

2026-05-011

OAAI

Jeweler-in-the-loop: personalized alloy color optimization via preference-based BO

珠宝商在环：基于偏好的贝叶斯优化个性化合金颜色优化

Digital Discovery

IF5.6

2026-03-130

OAAI

Bringing ML to the real world: Rewards are all we need

将机器学习引入现实世界：奖励就是我们所需要的

APL Machine Learning

IF0

2026-03-010

PRE

Predicting Interstitial Solutes in Refractory Complex Concentrated Alloys via a Combined Experimental and Computational Workflow: A Case Study on Oxygen in NbTaTiHf

通过结合实验与计算工作流程预测难熔高熵合金中的间隙溶质：以NbTaTiHf中的氧为例

Acta Materialia

IF9.3

2026-02-120

PRE

Publisher Correction: Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

出版者更正：合金的机器学习势：预测相图和基准精度的详细工作流程

npj Computational Materials

IF11.9

2025-12-190

OAAI

Data-driven framework for printability and geometric quality prediction in 3D concrete printing

基于数据的3D混凝土打印可打印性和几何质量预测框架

Materials & Design

IF7.9

2025-12-110

OAAI

Uncertainty-aware Process-Property Mapping in Laser Directed Energy Deposition of 316L stainless steel

基于不确定性的激光定向能量沉积316L不锈钢过程-属性映射

Journal of Manufacturing Processes

IF6.8

2025-12-100

PREAI

Data-driven insights into composition-property relationships in FCC high entropy alloys

FCC高熵合金成分-性能关系的数据驱动洞察

SCRIPTA MATERIALIA

IF5.6

2025-12-010

PRE

Leveraging Domain Knowledge for Optimal Initialization in Bayesian Materials Optimization

利用领域知识实现贝叶斯材料优化的最优初始化

Digital Discovery

IF5.6

2025-11-200

OAAI

Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

合金的机器学习势：预测相图和基准精度的详细工作流程

npj Computational Materials

IF11.9

2025-11-190

OAAI

Construction and Tuning of CALPHAD Models Using Machine-Learned Interatomic Potentials and Experimental Data: A Case Study of the Pt-W System

基于机器学习原子间势能和实验数据的CALPHAD模型构建与调优：Pt-W体系的案例研究

JOURNAL OF PHASE EQUILIBRIA AND DIFFUSION

IF1.7

2025-11-010

PRE

Accurate and uncertainty-aware multi-task prediction of HEA properties using prior-guided deep Gaussian processes

基于先验引导的深度高斯过程对高熵合金（HEA）性能的精确且具备不确定性感知的多任务预测

npj Computational Materials

IF11.9

2025-10-160

Microstructure-aware bayesian materials design

微观结构感知贝叶斯材料设计

Acta Materialia

IF9.3

2025-09-290

PRE

Analytical gradient-based optimization of CALPHAD model parameters

基于分析梯度法的CALPHAD模型参数优化

Acta Materialia

IF9.3

2025-08-260

PRE

Decoding non-linearity and complexity: deep tabular learning approaches for materials science

解析非线性与复杂性：面向材料科学的深度表格学习方法

Digital Discovery

IF5.6

2025-08-020

OAAI

Raymundo Arróyave

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