Sara Kadkhodaei

University of Illinois Chicago — United States

Materials Science · Physical Sciences

12h-index700citations32works3.02yr avg
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Research Topics

Machine Learning in Materials Science(13), X-ray Diffraction in Crystallography(7), High Temperature Alloys and Creep(5), Nuclear Materials and Properties(4), Advanced Chemical Physics Studies(3)

Publications32 total

Defect Energy Formalism for CALPHAD Thermodynamics of Dilute Point Defects: Application
SSRN Electronic Journal·2026Open Access
Leveraging Large Language Models to Address Data Scarcity in Machine Learning for Graphene Synthesis
SSRN Electronic Journal·2026Open Access
Resiliency, morphology, and entropic transformations in high-entropy oxide nanoribbons
Science·2025· 14 cited
Stabilizing lithium superoxide formation in lithium-air batteries by Janus chalcogenide catalysts
Nano Energy·2024· 5 cited
Impact of data bias on machine learning for crystal compound synthesizability predictions
Machine Learning Science and Technology·2024· 7 citedOpen Access
Defect energy formalism for CALPHAD thermodynamics of dilute point defects: Theory
Physical Review Materials·2024· 1 cited
Defect energy formalism for CALPHAD thermodynamics of dilute point defects: Theory
arXiv (Cornell University)·2024· 1 citedOpen Access
Impact of Data Bias on Machine Learning for Crystal Compound Synthesizability Predictions
arXiv (Cornell University)·2024Open Access
Heat radiation mitigation in rare-earth pyrosilicate composites: A first principles investigation of refractive index mismatch
Ceramics International·2024· 1 citedOpen Access
Improving <i>ab initio</i> diffusion calculations in materials through Gaussian process regression
Physical Review Materials·2024· 1 cited
Formation energy prediction of crystalline compounds using deep convolutional network learning on voxel image representation
Communications Materials·2023· 14 citedOpen Access
Enhancing ab initio diffusion calculations in materials through Gaussian process regression
arXiv (Cornell University)·2023Open Access
Voxel Image of Crystals for High-Throughput Materials Screening: Formation Energy Prediction by a Deep Convolutional Network
2023Open Access
Computational design of corrosion-resistant and wear-resistant titanium alloys for orthopedic implants
Materials Today Communications·2022· 26 citedOpen Access
Antibiotic Resistance among <i>Escherichia coli</i> Isolates, Antimicrobial Peptides and Cell Membrane Disruption to the Control of <i>E. coli</i> Infections
IntechOpen eBooks·2022Open Access
Understanding the role of anharmonic phonons in diffusion of bcc metals
Physical Review Materials·2022· 8 cited
Computational Design of Corrosion-Resistant and Wear-Resistant Titanium Alloys for Permanent Joint Implants
SSRN Electronic Journal·2022Open Access
Understanding the role of anharmonic phonons in diffusion of bcc metal
arXiv (Cornell University)·2021Open Access
Predicting synthesizability of crystalline materials via deep learning
Communications Materials·2021· 40 citedOpen Access
Cluster Expansion of Alloy Theory: A Review of Historical Development and Modern Innovations
JOM·2021· 38 cited
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Frequent Co-authors

Ali Davariashtiyani(9), Axel van de Walle(6), Seyyedfaridoddin Fattahpour(5), Qi‐Jun Hong(4), Ruoshi Sun(3), Adetoye H. Adekoya(3), Noel Siony(2), Otgonsuren Lundaajamts(2), Hessam Shahbazi(2), Pardis Seraji(2), Ilias Papailias(2), Amin Salehi‐Khojin(2), Busheng Wang(2), Samad Hajinazar(2), Eva Zurek(2), Amir M. Orvati Movaffagh(2), Teng Zhang(1), Xiaoyan Li(1), Huajian Gao(1), Zahra Kadkhodaie(1)