About

Axel van de Walle is a Professor of Engineering at Brown University, specializing in Materials Science within the field of Computational Engineering. He is involved in the Master’s in Data-Enabled Computational Engineering and Science program at Brown University. His research focuses on computational approaches in engineering and materials science, contributing to the advancement of data-enabled methods in these fields. He serves as an advisor and is actively engaged in academic and research activities at Brown University, located in Providence, RI.

Research topics

• Computer Science
• Political Science
• Artificial Intelligence
• Geography
• Econometrics
• Medicine
• Economics
• Business
• Operations research
• Engineering
• Actuarial science
• Machine Learning
• Environmental health
• World Wide Web
• Statistics
• Computational chemistry
• Composite material
• Data science
• Metallurgy
• Meteorology
• Chemistry
• Physics
• Thermodynamics
• Materials science

Selected publications

• SimplySQS: An automated and reproducible workflow for special quasirandom structure generation with ATAT

  Journal of Computational Science · 2026-03-18

  preprintOpen accessSenior author

  The special quasirandom structure (SQS) method is widely used for modeling disordered materials under periodic boundary conditions, with the ATAT mcsqs module being one of the most established implementations. However, SQS generation with mcsqs typically relies on manual preparation of input files, ad hoc execution scripts, and post-processing steps, which introduces user-dependent errors and limits reproducibility. Here, we present SimplySQS ( https://simplysqs.com ), an automated and reproducible workflow for SQS generation that is delivered through an online, interactive interface. SimplySQS guides users through structure import, compositional and supercell definition, and cluster parameter selection, while automatically generating all required ATAT input files and a single all-in-one execution script that encapsulates the complete search process. By standardizing input preparation, execution, and output analysis, the framework minimizes errors associated with manual file handling and enables consistent reproducibility of SQS searches. The workflow is demonstrated on the Pb 1- x Sr x TiO 3 (PSTO, including PbTiO 3 (PTO) and SrTiO 3 (STO)) perovskite system. SQSs spanning the entire concentration range were generated using a single automated bash script produced by SimplySQS , after which all resulting structures were subjected to geometry optimization using a universal machine-learning interatomic potential (MACE MATPES-r²SCAN-0). This approach reliably reproduced the experimentally observed cubic-to-tetragonal transition near x ≈ 0.5, with lattice parameters deviating by less than 1% in the cubic region ( x > 0.5) and less than 4% in the tetragonal region ( x ≤ 0.5). Overall, SimplySQS transforms SQS generation with ATAT into an intuitive, reproducible, and systematic framework for modeling disordered materials.

  PublisherDOI

• Density Functional Theory ToolKit (DFTTK) to automate first-principles thermodynamics via the quasiharmonic approximation

  Computational Materials Science · 2025-07-15

  article
  PublisherDOI

• Xtdb, an Xml Based Format for Calphad Databases

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Density Functional Theory ToolKit (DFTTK) to Automate First-Principles Thermodynamics via the Quasiharmonic Approximation

  ArXiv.org · 2025-04-23

  preprintOpen access

  The Helmholtz energy is a key thermodynamic quantity representing available energy to do work at a constant temperature and volume. Despite a well-established methodology from first-principles calculations, a comprehensive tool and database are still lacking. To address this gap, we developed an open-source Density Functional Theory Tool Kit (DFTTK), which automates first-principles thermodynamics using the quasiharmonic approximation (QHA) for Helmholtz energy predictions. This Python-based package provides a solution for automating the calculation and analysis of various contributions to Helmholtz energy, including the static total energy contributions at 0 K in terms of DFT-based energy-volume curves, vibrational contributions from the Debye-Gruneisen model and phonons, and thermal electronic contributions via the electronic density of states. The QHA is also implemented to calculate the Gibbs energy and associated properties at constant temperature and pressure. The present work demonstrates DFTTK's capabilities through case studies on a simple FCC Al and various collinear magnetic configurations of Invar Fe3Pt, where DFTTK enumerates all unique configurations and their associated multiplicities. DFTTK is freely available on GitHub, and its modular design allows for the easy addition of new workflows.

  PublisherOA PDFDOI

• Comparison of Homogeneous and Heterogeneous Ensemble Machine Learning Algorithms for Predicting Wheat Production

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Soliquidy: a descriptor for atomic geometrical confusion

  npj Computational Materials · 2025-02-19 · 3 citations

  articleOpen access

  Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin films (glass/no-glass) with the aflow.org computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such a classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.

  PublisherOA PDFDOI

• XTDB, an XML based format for Calphad databases

  Calphad · 2025-07-23

  articleOpen access

  The calculation of phase diagram (Calphad) method uses models that depend on assessed parameters to describe the thermodynamic properties of materials. These model parameters are assessed by researchers and students using experimental and theoretical data on binary and ternary systems that can be merged to multicomponent databases and used to calculate properties and simulate processes for a wide range of materials. There are several different software using the Calphad method for calculations and they may use slightly different models and database formats. This paper will provide a short background on the current state of database development and proposes a new format based on the eXtensive Markup Language (XML) as a unified database format. This change is particularly important as several new models for the pure elements are currently being introduced in the Calphad databases.

  PublisherDOI

• Soliquidy: a descriptor for atomic geometrical confusion

  ArXiv.org · 2025-01-29

  preprintOpen access

  Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin-films (glass/no-glass) with the aflow.org computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.

  PublisherOA PDFDOI

• A computational free energy reference for mechanically unstable phases

  Calphad · 2025-09-16 · 3 citations

  articleOpen accessSenior authorCorresponding

  The CALPHAD (CALculation of PHAse Diagram) framework relies heavily on the availability of a well-defined free energy for all possible phases, including metastable and even mechanically unstable phases. However, for phases that exhibit mechanical instability, the determination of the free energy represents a challenge, both experimentally and computationally. This situation hinders the seamless integration of experimental and ab initio thermodynamic data. A newly developed method, named “inflection-detection”, provides a practical computational solution to this problem with a sound theoretical basis. Extending upon existing energy calculations at absolute zero, we provide further evidence of this method’s effectiveness by computing the temperature-dependent free energy references for 22 elemental structures involving mechanically unstable phases and showing that they are reasonably consistent with the (often wide) range of values determined in earlier experimental assessments. This suggests the feasibility of a reliable computation-based reference free energy standard for mechanically unstable pure elements. • Free energy of mechanically unstable phases can be efficiently determined using inflection-detection approach. • Method enables the use of standard lattice dynamics calculations to obtain the temperature-dependence of free energies. • Calculated free energies show good agreement with prior CALPHAD estimates based on extrapolations from stable regions.

  PublisherDOI

• A Non-Local Orientation Field Phase-Field Model for Misorientations- and Inclination- Dependent Grain Boundaries

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

Recent grants

• CAREER: Extending the lattice stability framework in ab initio alloy thermodynamics

  NSF · $261k · 2010–2011

• Collaborative research: experimental and computational study of structure and thermodynamics of rare earth oxides above 2000 C

  NSF · $214k · 2018–2022

• Collaborative Research: Rare Earth Materials Under Extreme Conditions

  NSF · $113k · 2022–2026

• The Generalized Cluster Expansion: A Tool for Representing Structure-Property Relationships

  NSF · $306k · 2009–2013

• CDS&E: Systematic Exploration of the High Entropy Alloy Space through High-Dimensional Thermodynamic Modeling from High-Throughput Computations and Experimental Data

  NSF · $380k · 2020–2024

Frequent coauthors

• Qi‐Jun Hong

  Arizona State University

  127 shared

• Micaela Oertel

  Centre National de la Recherche Scientifique

  80 shared

• J. van den Brand

  78 shared

• B. Revenu

  Centre National de la Recherche Scientifique

  70 shared

• Jérôme Novak

  Institut de Recherche en Informatique Fondamentale

  62 shared

• Mark Asta

  University of California, Berkeley

  61 shared

• I. M. Pinto

  Enrico Fermi Center for Study and Research

  54 shared

• A. Heidmann

  52 shared