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Workshop Sat, Dec 12, 2026 • 8:00 AM – 5:00 PM AEDT Hall 2

AI4Mat-NeurIPS-2026: NeurIPS-2026 Workshop on AI for Accelerated Materials Design

Santiago Miret ⋅ Mara Schilling-Wilhelmi ⋅ N M Anoop Krishnan ⋅ Vijay K Narasimhan ⋅ Stefano Martiniani

[ OpenReview]

Abstract

AI4Mat-NeurIPS-2026 explores applications of AI to materials via: (1) AI-Guided Materials Design; (2) Automated Chemical Synthesis; and (3) Automated Material Characterization. As the focused meeting point for the AI-for-materials community at NeurIPS, the workshop emphasizes structured, expert-driven dialogue on making machine learning more impactful for real-world materials discovery. As reasoning models mature and self-driving laboratories come online, a timely question arises: how does compute translate into genuine scientific discovery, and how do we close the gap between algorithmic progress and deployment in messy, real experiments? Our two main sessions address this: Scaling Laws for Materials Reasoning: From Compute to Scientific Discovery examines reasoning models and the utility of compute; Automating Discovery That Delivers: When AI Meets the Messiness of Real Experiments tackles the critical challenges of real-world experimental data collection. Beyond invited talks, a substantial portion of the program is devoted to contributed spotlights, a poster session, and a town hall. Building on previous AI4Mat workshops, we strengthen this community through in-depth peer feedback on spotlight presentations, an expanded travel grant program, and a dedicated focus collection in a high-impact journal. Our location preference is Sydney to broaden the reach of the AI4Mat community.

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Schedule

Time zone: Conference local time zone

High-fidelity Off-equilibrium Dataset and Universal Interatomic Potentials for Li-Halide Solid-State Electrolytes

Jiyoon Kim ⋅ Chuhong Wang ⋅ Aayush R Singh ⋅ ⋅ Shivang Agarwal ⋅ AJ Nish ⋅ Paul Abruzzo ⋅ Maciej Polak ⋅ ⋅ Ang Xiao ⋅ Omar Allam

Preference-Aware Multi-Objective Bayesian Optimization for AI-Guided Polymer Design

Hideyuki Masui ⋅ Keisuke Ando

Out-of-the-Box Tabular Foundation Models for Bayesian Optimization in Materials Discovery

Klemens Flöge ⋅ Simon Bing ⋅ Leo Grinsztajn ⋅ Eliott Kalfon ⋅ Lennart Purucker ⋅ Noah Hollmann ⋅ Frank Hutter

ASE-Bench: An Atomic Simulation Benchmark for Agentic Materials Discovery

Seokhyun Choung ⋅ Jeong Han

LLM Agents for Hypotheses Generation and Experimental Design in Heterogeneous Catalysis

Anna Kelmanson ⋅ Philippe Schwaller

A Structure-to-Density Model for Trajectory-Free Lithium Transport Screening

Kunmin Jang ⋅ Dongin Kim ⋅ Woojin Bae ⋅ Jaewon Bae ⋅ Chanyoung Park

Benchmarking Bayesian optimization strategies across compositional landscapes

Abigale Monasterial ⋅ Thorben Prein ⋅ Matthias Stosiek ⋅ Jennifer Rupp ⋅ Patrick Rinke

Disentangling Distribution Shifts in Polymer Property Prediction with Metadata, Physical Descriptors, and Group-Aware Evaluation

Hiroto Yokoyama ⋅ Takahiro Umemoto ⋅ Akiko Kumada ⋅ Masahiro Sato

Why Did Bayesian Optimization Recommend This Recipe? Action-Level Decomposition of Value and Uncertainty

Minseong Kim ⋅ JunyoungLee ⋅ Jiwoo Lee ⋅ Jinwon Yoon

LLMs as Acquisition Policies for Finite-Pool Materials Optimization: A Controlled Study

Dino-Rober Demir ⋅ Florian Le Bronnec ⋅ Rio Yokota

MiAD: Mirage Atom Diffusion for De Novo Crystal Generation

Andrei Okhotin ⋅ Maksim Nakhodnov ⋅ Nikita Kazeev ⋅ Mikhail Lazarev ⋅ Andrey Ustyuzhanin ⋅ Dmitry Vetrov

uMOF: A Universal Database, Benchmark, and Machine-Learning Interatomic Potentials for Metal--Organic Frameworks

Theo jaffrelot inizan ⋅ Prathami Divakar Kamath ⋅ Alin m elena ⋅ Kristin Persson

Evaluating LLMs for Automated SEM Powder Characterization Workflows

Stephen Price ⋅ Kiran G Judd ⋅ Danielle L Cote ⋅ Elke A. Rundensteiner

The A to D in DMTA (Design, Make, Test, and Analyze): Agentic Analysis for Self-Driving Labs

Yimeng Liu ⋅ Eric Isbrandt ⋅ Felix Katzenburg ⋅ Kevin P. Greenman ⋅ Han Hao ⋅ Yang Cao ⋅ Varinia Bernales ⋅ Alan Aspuru-Guzik

From Recipes to Transitions: An Observability Audit for Materials World Models

Cyrus Moazami

Long Horizon Resilience Optimization as an AI Challenge: A Soft Actuator Case Study

Ang Leo Li ⋅ ⋅ Mihai Duduta

GEMBench: Separating Distribution Matching from Discovery in Crystal Generation

Andrei Okhotin ⋅ Mikhail Lazarev

Out-of-training properties in frozen interatomic potential embeddings are decodable and ordered by physical scale

Natalija Stepurko ⋅ Joonatan Laulainen

Verifiable pXRD: Hill-climbing pXRD structure determination with LLM agents

Samuel Chen ⋅ Jiaru Bai ⋅ Austin Cheng ⋅ Alan Aspuru-Guzik

Reliable End-to-End Materials Literature Mining with Prediction Based OOD Detection

Somin Kim ⋅ Minhyeong Cho ⋅ Heedong Kim ⋅ Youngjae Kim ⋅ Kyungwoo Song

Experimental validation of an LLM-hypothesized Fe-Mn-Al-Ni-Si-C alloy: phase stability governs the absence of super-elasticity

Frank Cai

HEAgent: Autonomous Large Language Model-Driven Framework for High-Entropy Alloy Electrocatalyst Discovery

Hoyun Kim ⋅ Seokhyun Choung ⋅ Jeong Han

Structure–Curvature Proposal Learning for Potential-Energy-Landscape Graph Construction

Haoyu Li ⋅

Scalable Bayesian Optimization of Composite Functions for Image-Based Inverse Problems in Materials Characterization

Dasol Yoon ⋅ Poompol Buathong ⋅ Chia-Hao Lee ⋅ David A Muller ⋅ Peter Frazier

Let CSP Be Your ANCHOR: Adaptive Crystal Search over Frozen Structure Priors

Emma Hovmand ⋅ Jonas Elsborg ⋅ Melih Kandemir ⋅ Arghya Bhowmik

STEM-Bank-26: An Open Dataset of Analytical Scanning Transmission Electron Microscopy Images and Spectra

George G Hollyer ⋅

Are Scaling Laws of Universal MLIPs Universal?

Richard Tomsett ⋅ Theo Keane ⋅ Anthony Onwuli ⋅ Robert M Forrest ⋅ Jonathan Bean

A symmetry-informed active-configuration search tool for equilibrium surface coverage prediction in materials discovery

Stavros Ntioudis ⋅ Li Shen

ReaXpert: A Synthesis Condition Design Agent Built with Evolutionary Prompt Optimization

Mingxuan Li ⋅ ⋅ ⋅ Sven Jager ⋅ Yasser Jangjou

Reducing cross-sample prediction churn in scientific machine learning

Gordan Prastalo ⋅ Kevin Maik Jablonka

XRDiff: Crystal Structure Prediction from Powder X-Ray Diffraction Data Using Diffusion Models

Nofit Segal ⋅ Akshay Subramanian ⋅ Mingda Li ⋅ Benjamin K Miller ⋅ Rafael Gomez-Bombarelli

MLIP Embeddings Predict Extraordinary Materials

Luis Carretero López ⋅ Nofit Segal ⋅ Sathya Edamadaka ⋅ Rafael Gomez-Bombarelli

EMOS: A Modular Framework for Interoperable AI Workflows in Electronic Materials Discovery

Atish Narasinha Dixit ⋅ Alexandros Keros ⋅ Ben D Rowlinson ⋅ Shashank Mishra ⋅ Themis Prodromakis ⋅ Jacqueline M Cole ⋅ Subramanian Ramamoorthy

Autonomous Experiments in Infinite Dimensions: A Case Study in Bioformulation Phase Mapping

Kiran Vaddi ⋅ Qian Yang ⋅

How Large Language Models Learn Materials Science

Vineeth Venugopal ⋅ Elsa Olivetti

HALLMARK: Benchmarking AI for Materials Selection and Design by Regret Against Known Optima

Ivan Trofimov

When Simulation Bias Breaks Conformal Coverage

Pranshu Nautiyal ⋅ Akshath Sharma ⋅ Tanush S ⋅ Mithil Shah ⋅ Akhil Narayanan ⋅ Oliver Loy ⋅ Patrick Feng ⋅ Laksh Patel ⋅ Aarav Lala ⋅ Andrew Bae ⋅ Soham Batra ⋅ Siddharth Karuturi

Multimodal Fusion for Accurate Molecular Property Prediction

Jimin Han ⋅ Jeong Han

BranchIP: Learning Adaptive Equivariant Computation for Interatomic Potentials

Laura Zichi ⋅ Gil Harari ⋅ Chuin W Tan ⋅ Albert Zhu ⋅ Marc Descoteaux ⋅ Menghang Wang ⋅ H. Kung ⋅ Boris Kozinsky

Per-Element Spectral Conditioning Addresses a Bottleneck in NMR-Conditioned Graph Diffusion

Róbert Veres ⋅ Nicolas Schmid ⋅ Florian Grötschla ⋅ Joël Mathys ⋅ Marc-Olivier Ebert ⋅ Roger Wattenhofer

Difference Transition Matching for Crystal Structure Generation

Ibuki Okuda ⋅ Izumi Takahara ⋅ Teruyasu Mizoguchi

Beyond Static Accuracy: Ensemble-Dependent Reliability of Universal Machine-Learned Interatomic Potentials in Hybrid Amorphous Membranes

Ryuya Kanda ⋅ Meguru Yamazaki ⋅ Shintaro Izumi ⋅ Atsuki Inoue ⋅ Hiroshi KAWAGUCHI ⋅ Yasufumi Sakai

Robot Foundation Models in the Materials Lab: Benchmarks, Embodiments, and Open Challenges

Izumi Takahara ⋅ Teruyasu Mizoguchi

Bridging Prediction and Planning: From Synthesis Temperature Distributions to Optimization-Guided Experiments

Jaewon Bae ⋅ Seungyun Shin ⋅ Chanyoung Park

Atomistic Language Models Understand and Generate Materials

Sathya Edamadaka ⋅ Krithik Ramesh ⋅ Ju Li ⋅ Rafael Gomez-Bombarelli

Benchmarking featurisation methods for segmenting HRTEM images

Alexandros Keros ⋅ Thiara de Alwis ⋅ Ben D Rowlinson ⋅ Themis Prodromakis

Tape-Free Interatomic Potentials: Exact Conservative Forces without Automatic Differentiation

Kin Long Kelvin Lee ⋅ Fabio Falcioni

Topology-Informed Active Learning for Sequential Materials Screening

Yueqi Cao ⋅ Jixiang Qing

MFM: Evidence-Aware Material Representations for Industrial Materials Discovery

Eduardo Soares ⋅ Jordi Ferrer Orri

A Simulator-Free Surrogate for Ferroelectric Phase-Fields via an Exact Fourier State-Space Model and Neural Operator

Matthew Ju ⋅ Yingheng Tang ⋅ Kangan Wang ⋅ Haozhi Sha

A Prototype-Guided Solver for Crystal Structure Determination from Powder X-ray Diffraction

Yusei Ito ⋅ Yuki Nishihori ⋅ Kanta Ono

Training Large Language Models for Effective Small-Molecule Design with Synthetic Task Scaling

Frank Hu ⋅ Shriram Chennakesavalu ⋅ Zichen Wang ⋅ Patricia Suriana ⋅ Bodhi Vani ⋅ Kirill Shmilovich ⋅ Kangway Chuang ⋅ Colin Grambow

Towards a universal model for spin--orbit coupled Wannier Hamiltonians

Alexander Tyner

GXTNet: Balancing Accuracy and Cost for Molecular Dynamics

Hongjun Yang ⋅ Sung Moon Ko ⋅ Sehui Han ⋅ Changyoung Park

Overlap-Aware Clean-Region Prediction for Autonomous STEM

Yuqing Huang ⋅ Henry Chan ⋅ ⋅ ⋅ Yuzi Liu

When More Domain Data Is Not Enough: Continual Pretraining for Protected-Peptide Solubility

Alexander A Lobo ⋅ Marc Saouda ⋅ Urvi Awasthi ⋅ Leonid Zhukov

Position: Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery

Harshit Bisht ⋅ Vinay Kumar ⋅ Kevin Maik Jablonka ⋅ Mausam ⋅ N M Anoop Krishnan

Evidence-Gated Dynamic Campaign Control for Materials Discovery

Sissi Feng ⋅ Jia En Yee ⋅ ⋅ ⋅ Yang Bai ⋅ Zeqing Bao ⋅ REN ZEKUN

Investigating Composite Modeling in Multi-Objective Bayesian Optimization for Scientific Design

Ricky Ye ⋅ Sahas Goli ⋅ Muhammad Ali ⋅ Poompol Buathong ⋅ Peter Frazier

Grounding Materials-AI Evaluation in Experimental Outcomes: An Open Challenge for Materials Discovery Benchmarks

Ivan Golov ⋅ Anton Gavrilov

RetroMol: Knowledge Distillation of Energy-Based Retrosynthesis Models

Rudra Sondhi ⋅ Edwin Chacko ⋅ Rodrigo Vargas-Hernandez

ComMat: Complex Material Datasets and Benchmarks for Graph Machine Learning

Trung-Kien Nguyen ⋅ Alain Kadar ⋅ Han Zhang ⋅ Wenbing Wu ⋅ Ahmet E Emre ⋅ Yves J Ndje ⋅ Sharon Glotzer ⋅ Robert A Riggleman ⋅ Nicholas Kotov ⋅ Paul Bogdan

RiskTriage: Calibrating When Physical Validation Is Needed in Computational Catalyst Discovery

Susanna Di Vita ⋅ Philippe Schwaller

Physics-Guided Curriculum Learning for Nonlinear Mixture Modeling and Discovery

Mahyar Rajabi Kochi ⋅ Josh Goldman ⋅ Mohamad Moosavi

Human–AI Discovery of Governing Reaction Principles for Geological Hydrogen Production

Abhishek Soni ⋅ ⋅ ⋅ ⋅ ⋅ Haihui Lan ⋅ ⋅

SprayBench: Benchmarking LLMs on Open-Ended Materials Reasoning in Additive Manufacturing

Stephen Price ⋅ Bryer C Sousa ⋅ Ronan Flynn ⋅ Kiran G Judd ⋅ Elke A. Rundensteiner ⋅ Danielle L Cote

Beyond Number Extraction: Scientific Fidelity of Local Language Models for XRD Crystallite-Size Extraction

Ebie Mavelil Sam ⋅ RENI GEORGE

Do Scientific Inductive Biases Help? Validation for Low-Data Mixture Property Prediction

Keng-Te Liao ⋅ Milton (Chen-wei) Lin ⋅ PO JUI SUN

Risk-Controlled DFT Selection for Machine-Learned Interatomic Potentials

Kun Ryu ⋅ Yeo Jin Jung ⋅ Ying S Meng ⋅ Claire Donnat

Self-Supervised Pretraining for Instrument-Robust Representations of Scattering Data

Darin Merchant ⋅ Nofit Segal ⋅ Miguel Steiner ⋅ Rafael Gomez-Bombarelli

MDGYM: Benchmarking AI Agents on Molecular Simulations

Vinay Kumar ⋅ Satyendra Rajput ⋅ Mausam ⋅ N M Anoop Krishnan

Surrogate Models for Stochastic Al–Cu Phase-Field Solidification

Simon Savukoski ⋅ Tatu Pinomaa

MOFSeq-2: A Space-Group-Aware MOF Sequence Representation for Free Energy Prediction

Andre Niyongabo Rubungo

Bayesian Optimisation for Automated Nuclear Magnetic Resonance Shimming

Jashvir Rathore ⋅ Han Hao ⋅ Mikkel Jordahn ⋅ John Willes ⋅ Gary Tom ⋅ Jasper Snoek ⋅ Varinia Bernales ⋅ James Harrison ⋅ Alan Aspuru-Guzik

Chemical Out-of-Distribution Reliability of Tabular Foundation Models for Small-Data Materials Prediction

Preyansh Srivastava

PolyGLOT: Graph-Token Language Modeling for Unified Polymer Property Prediction and Programmable Generation

Tianle Yue ⋅ Ying Li

Diversity Sampling Costs Labels Near the Training Pool and Saves Them Far From It

Satoki Muto ⋅ Akiko Kumada ⋅ Masahiro Sato

Decision-Time Representations in Closed-Loop Bimetallic Nanoparticle Design

Sibasankar Panigrahy ⋅ Ankit Patidar

Synthetic Crystal Data Generation for Diffusion Pretraining in Material Property Prediction

Aamod Jayakrishnan Varma ⋅ Shuyi Jia ⋅ Victor Fung

Chemical filters for ultra-high-throughput materials screening and generation

Kinga Mastej ⋅ ⋅ Hyunsoo Park ⋅ Anthony Onwuli ⋅ Masahiro Negishi ⋅ Aron Walsh

Representing Molecules in Their Physical Context through Molecular Dynamics

Fernando Javier Carmona Esteva ⋅ Mahyar Rajabi Kochi ⋅ Ella Miray Rajaonson ⋅ Benjamin Sanchez-Lengeling ⋅ Mohamad Moosavi

Simulation Based Inference for Multi-component Nanoparticle Scattering

Pranav Kakhandiki ⋅ Sean Gasiorowski ⋅ Samuel Klein ⋅ Anjani K Maurya ⋅ Christopher J Tassone

Generative Pipeline for the Discovery of Single-Phase Immersion Coolants for Data Centres

Tammo Dukker ⋅ Oliver R Gittus ⋅ Erich A Müller

Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport

Malte Franke ⋅ Stefan P. Schmid ⋅ Žarko Ivković ⋅ Kjell Jorner ⋅ Andreas Krause

Ghost Atoms: Flexible Crystal Generation With Voronoi Tessellations

Konstantin Dubovskiy ⋅ Thomas Egg ⋅ Philipp Höllmer ⋅ Stefano Martiniani

MOF-VERIFY: A Failure-Aware Agentic Harness for MOF Hypothesis Verification

Donghyun Lee ⋅ Taehoon Lee ⋅ GeonHee Ahn ⋅ Jieun Kim ⋅ Jihyun Park ⋅ Suyeon Cho ⋅ Yoona Kim ⋅ Chaerim Shin ⋅ Hoi R Moon ⋅ Jonggeol Na ⋅ Sukho Hong ⋅ Jihwan OH ⋅ Soo Kyung Kim

What Do LLMs Use to Judge Synthesis Recipes? An Experimental Analysis on 240 Solid-State Syntheses

Derek van Tilborg ⋅ ⋅ Harry Sevi ⋅ ⋅ ⋅ Aikaterini Savvidou ⋅ ⋅ ⋅ Joonatan Laulainen

Quasiparticle Energies That Will Not Be Computed: A Calibrated Release for 2D Semiconductors

Jiwoo Lee ⋅ JunyoungLee ⋅ Minseong Kim ⋅ Jinwon Yoon

ED-CSP: Crystal Structure Prediction from Electron Diffraction

Germain Poloudenny ⋅ Yael Fregier ⋅ Arnaud Demortière

Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

Van Khoa Nguyen ⋅ Alexandros Kalousis

Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist

Kiyoung Seong ⋅ Nayoung Kim ⋅ Sungsoo Ahn

TAME: Element-wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction

Robert Schiller ⋅ Christoph Weisser ⋅ Klaus-Robert Müller ⋅ ⋅ Parastoo Semnani

TRACE: Adaptive Trust-Region Bayesian Optimization for Open-Ended Molecular Design

Madhav Muthyala ⋅ Mahsa Askari ⋅ Farshud Sorourifar ⋅ Evan Zhou ⋅ Joseph A Gauthier ⋅ Joel Paulson

Structure-Adaptive Generative Atom Substitution

Changyoung Park ⋅ Minsub Um ⋅ Sehui Han

Gauge Informed Gating for Conservative Machine Learning Interatomic Potentials

Sung Moon Ko ⋅ Sehui Han

On the uncertainty in atomistic diffusion models

Jonas Vestergaard Jensen ⋅ François Cornet ⋅ Mikkel Jordahn ⋅ Michael Andersen ⋅ Mikkel Schmidt

Multimodal LLM-Assisted Diagnosis of Cryptic Failure Modes in High-Throughput Experimentation: A Case Study in Gold Nanorod Synthesis

Riya Patel ⋅ Gabriela Briceno ⋅ Amirali Aghazadeh ⋅ Vida Jamali

From Force Accuracy to Reliable Molecular Dynamics: Limits and Guarantees for Unconstrained MLIPs

Prajwal Ananth ⋅ Shuwen Yue

Designing Ligated Nanoclusters with Flow Matching and Natural Language

Luca Schaufelberger ⋅ Aline Hartgers ⋅ Laura Mismetti ⋅ Rémi Schlama ⋅ Aman Govind Soni ⋅ Malte Franke ⋅ Edvin Fako ⋅ Marvin Alberts ⋅ Andreas Krause ⋅ Philippe Schwaller ⋅ Kjell Jorner

Which alloy composition, what process parameters? Inferring the recipe from optimized metallic microstructure and texture

Mahish Kumar Guru ⋅ Jan Bohlen ⋅ Louam lemjid ⋅ Marius Tacke ⋅ Roland Aydin ⋅ Noomane B Khalifa

Navigating Literature Retrieval in Material Space

Thomas M Pruyn ⋅ Mohamad Moosavi

Evaluating Conditioning of a Vision-Language Model for SEM Fractography

Tanisha Gnanasekaran ⋅ El Tayeb Bentria ⋅ Amine Haboub

CatEdit: A Generative Editing Framework for Heterogeneous Catalyst Discovery

Igon Kim ⋅ Jeong Han

POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles

Nicolas Menet ⋅ Andreas Krause ⋅ Abbas Rahimi

FrOGS: Discrete Neural Sampler for Independent Alloy Configurations Across Chemical Conditions

Kyucheol Min ⋅ Elyssa Hofgard ⋅ Tess Smidt

Openclatura: An Open and Inspectable IUPAC Naming Tool for Molecular Discovery Workflows

Adrian Mirza ⋅ Kevin Maik Jablonka ⋅ Rostislav Fedorov

Does System Size Matter in Uncertainty Quantification for Machine Learning Interatomic Potentials?

Chayaphol Lortaraprasert ⋅ Nontawat Charoenphakdee ⋅ Wenwen Li ⋅ Yong-Bin Zhuang ⋅ Yuta Tsuboi

Learning Shared Crystal-Language Representations through Progressive Alignment

Xianrong Liu ⋅ David M Segura ⋅ Jeremy Goumaz ⋅ Philippe Schwaller ⋅ Tong Xie

Manufacturability-Constrained Surrogate Inverse Design of Disordered Photonic Crystals for Ultrathin Silicon Photovoltaics

Joseph Kopel ⋅ Taiki Shinokawa ⋅ Marcus Cheung

Overcoming Diffusion Underestimation in Generative Molecular Dynamics of TiO2-SiO2 Membranes via Displacement-Weighted Fine-Tuning

Yuko Kinoshita ⋅ Meguru Yamazaki ⋅ Shintaro Izumi ⋅ Atsuki Inoue ⋅ Hiroshi KAWAGUCHI ⋅ Yasufumi Sakai

Blind spots and strengths of LLMs in predicting chemical reaction conditions and incompatibilities

Theo Neukomm ⋅ Daniel Armstrong ⋅ Philippe Schwaller

Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

Thomas Egg ⋅ Harry Sullivan ⋅ Maya M Martirossyan ⋅ Philipp Höllmer ⋅ Cheng Zeng ⋅ Adrian Roitberg ⋅ Mingjie Liu ⋅ Richard Hennig ⋅ Sapna Sarupria ⋅ Ellad Tadmor ⋅ Stefano Martiniani

Extending Phase-Diagram Screening for Silicon Metallurgy: a Compact Pipeline Co-designed with a Ferroalloys Manufacturer

Eduardo Abenza Severa ⋅ David Garcia Valcarce ⋅ Ana R Bernal ⋅ César A Garrido ⋅ Álvaro C Santiago ⋅ MARIA CARMEN ASENSIO ⋅ Roberto Gómez-Espinosa Martín

Charge-aware knowledge distillation of foundation interatomic potentials

Jinuk Moon ⋅ Jeong Han

Accelerating Materials Discovery With Active Thermodynamic Surface Shape Mapping

Andrew Tipping ⋅ Robert Huggins ⋅ Ray Yang ⋅ Robert B Wexler ⋅ Roman Garnett

Curated Knowledge is the Critical Path to an AI Co-Scientist for Materials Discovery

Liana Alves ⋅ Guangchi Lee ⋅ Tatiana Kuznetsova ⋅ Runtian Gao ⋅ Sohae Kim ⋅ Ye Li ⋅ Nico Mohr ⋅ Ross Fu ⋅ Julian Burschka

SIGMol: Enabling Molecular Design with Flow Map Chemical Language Models

Steven Dunne ⋅ Sebastian Ibarraran ⋅ Frank Hu

Ferrogen: Generative Pipeline for Guided Search of Novel Ferroelectric Material for Logic and Memory

Yuan Sheng Fang ⋅ Dmitri E Nikonov ⋅ Ikenna Odinaka ⋅ Alan Kalitsov ⋅ Roza Kotlyar ⋅ Arnab Kabiraj ⋅ Benjamin W Chen ⋅ Shundan Xiao ⋅ Brian Demsky ⋅ Chryston B Meng ⋅ Chang Wei Kang ⋅ Teck L Tan ⋅ Zhang Jia ⋅ Jin Hongmei ⋅ Debo Olaosebikan ⋅ Sasikanth Manipatruni ⋅ Amrita Mathuriya

OMatG-flash: An All-Atom Flow Map with Reinforce Adjoint Matching for Scalable Materials Discovery

Thomas Egg ⋅ Harry Sullivan ⋅ Ellad Tadmor ⋅ Stefano Martiniani

DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion

Zhuotao Jin ⋅ Xiaoyun Wang ⋅ Nicholas Brawand ⋅ Roman Zubatyuk ⋅ Atul Thakur ⋅ Eric Qu ⋅ Boris Kozinsky ⋅ Justin Smith

Does Geometry Matter? Comparing Fingerprint, Graph, and 3D Pretraining for Molecular Property Prediction

Hossein Zaremehrjerdi ⋅ Zachary T Gardner ⋅ Rebekah Duke ⋅ Marjan Saadati ⋅ Chad Risko ⋅ Baskar Ganapathysubramanian

Towards a General-Purpose Model for the Chemistry Discovery Workflow

Laura Mismetti ⋅ Mariana Alves ⋅ Carlo Baldassari ⋅ Rhyan Barrett ⋅ Sarah de Ruiter ⋅ Serafina Di Gioia ⋅ Mara Graziani ⋅ Flavia Iovane ⋅ Anna Kelmanson ⋅ Rémi Schlama ⋅ Federico Zipoli ⋅ Uros Zivanovic ⋅ Andreas Krause ⋅ Rui Moreira ⋅ Cecilia M Rodrigues ⋅ Philippe Schwaller ⋅ Tiago Rodrigues ⋅ Teodoro Laino ⋅ Jannis Born ⋅ Marvin Alberts

Towards Agentic AI for Homogeneous Catalyst Design

Miquel Àngel Puigdomènech ⋅ Sarina Kopf ⋅ Philippe Schwaller

PROBIXI - Self-Calibrating (PROB)ab(I)listic Peak Detection for Serial (X)-Ray Crystallograph(I)c Data

Ryan ODea ⋅ ⋅

Attributing MLIP Force Predictions to Atom Groups via Model-Deviation-Gated Deletion

Meguru Yamazaki ⋅ Yuta Yoshimoto ⋅ Naoki Matsumura ⋅ Hong Gao ⋅ ⋅ Yasufumi Sakai

\texttt{UMA-DOS}: Transfer Learning from Pretrained Atomistic Models for Density of States Prediction

Klea Ziu Ziu ⋅ Ayala V Cohen ⋅ Yusei Ito ⋅ Aidar Alimbayev ⋅ Leeor Kronik ⋅ Martin Takac

Multi-Objective Generative Discovery of Liquid Organic Hydrogen Carriers

Seoyeon Kim ⋅ Jeongwoo Kwon ⋅ Hyunwoo Yook ⋅ Min Kwon ⋅ Jeong Han

A Carrier-Limited Release Ceiling in Electrospun Nanofiber Drug Delivery for Regenerative Endodontics: Machine Learning on a Twenty-Five-Run Experimental Dataset

Nura Brimo ⋅ Dilek Ç Serdaroğlu

Higher-Order Materials Synthesis: From Provenance Completion to Resource-Constrained Planning

Indra Priyadarsini S ⋅ Anna P Carrieri ⋅ Sina Klampt ⋅ Seiji Takeda ⋅ Lisa Hamada ⋅ Onur Boyar ⋅ Akihiro Kosugi

Rank-optimal neural representation of EBSD resolves subgrains and enables their quantitative analysis

I-Tzu Huang ⋅ Marat Latypov

Combining Physical and Retrieved Empirical Priors for Solid-State Synthesis Condition Prediction

Woojin Bae ⋅ Hyunsung Jang ⋅ Jaewon Bae ⋅ Chanyoung Park

A Representation Problem: Discretization Enables Band Gap Steering in Crystal-Generating LLMs

Delia McGrath ⋅ Hasan Amin

ROBAT: A Hierarchical Transformer with Rotary Position Embeddings for Generalizable Battery Health Prediction

Inseop Kim ⋅ Junhyeong Lee ⋅ Jungjoon Yoo ⋅ Chan-Woo Lee

Steering Flexible-Size Molecular Generation\\via RL on Trans-Dimensional Flows

Adrien Goldszal ⋅ Malte Franke ⋅ Andreas Krause

Agentic Retrieval for Bio-Based Recovery of Critical and Near-Critical Minerals

Viktoriia Baibakova

ePattern: More Views Improve Composition-Free Crystal Retrieval from Sparse Electron Diffraction

Germain Poloudenny ⋅ Arnaud Demortière ⋅ Yael Fregier

MatHarness: Towards Long-Horizon Open-ended AutoResearch for Computational Materials Science

Yanlin Fei ⋅ Li Lei ⋅ Shaolong Chen ⋅ Nazhou Liu ⋅ Xinmiao Yu ⋅ Madalina Ciobanu ⋅ Navan P Singh ⋅ Qingqing Mao ⋅ Ritankar Das

Diagnostic Accuracy Is Not Deployment Value: Decision-Aligned Reliability Evaluation for Foundation MLIPs in Materials Discovery

Harry Sevi ⋅ Joonatan Laulainen

When Do Structure-Aware Pipelines Help Band-Gap Prediction? A Fold-Controlled Representation–Learner Audit from Composition to Graphs on MatBench mp_gap

Wanting Xu

Fully Symmetry-Conditioned Rigid-Body Flow Matching for Molecular-Crystal Structure Prediction

Frank Cai

Constrained Multiphysics Inverse Design of Two-Phase Composites with Differentiable Surrogates

Amit Subrahmanya ⋅ Vishwas Rao ⋅ Michel Schanen ⋅ Fabio Sozio ⋅ Linxi G Li ⋅ Iulian Grindeanu ⋅ Selma Wanna ⋅ Aleksandra Pachalieva ⋅ Mihai Anitescu ⋅

When Do Compact Knowledge Graphs Suffice for Battery-Materials Hypothesis Generation?

Shashwat Sourav ⋅ Viktoriia Baibakova ⋅ Sanjay Das ⋅ Ran Elgedawy ⋅ Emily Herron ⋅ Tirthankar Ghosal

Choosing the Right Representations: Task-Aware Fusion for Multimodal Materials Language Models

Huu Binh Ta ⋅ Alex Morehead ⋅ N. Benjamin Erichson ⋅ Ferdinando Fioretto ⋅ Sandeep Madireddy

AMAM-128: A Segmentation Benchmark for Annotated Metallic Alloy Microstructures

Inbal Cohen ⋅ Idan Z Friedberg ⋅ Yael Templeman ⋅ Ofer Beeri ⋅ Julien Robitaille ⋅ Francis Quintal Lauzon ⋅ Shai Avidan ⋅ Gal Oren

A Three-Stage, Expert-in-the-Loop AI Pipeline for the Discovery of a Cobalt- and Nickel-Free Rock-Salt Li-ion Cathode

Eduardo Abenza Severa ⋅ César A Garrido ⋅ Joao Fonseca ⋅ MARIA CARMEN ASENSIO ⋅ Roberto Gómez-Espinosa Martín

IonBind: RL-aligned Generative Cascade for Selective Ion Binder Design

Heejung Roh ⋅ Elton Pan ⋅

DFT-Agent Bench: What Agent Engineering Buys, and What It Does Not, for Autonomous DFT

Shijie Liu ⋅ Jin Yang ⋅ Weilin Wan ⋅ Jingtao Han ⋅ Jia LI ⋅ Tianqi Deng

Curriculum, Corpus, or RL? Matched-Budget Training Levers for LLM-Driven Crystal Structure Generation with Qwen

Shehroz Ahmad Shoaib ⋅ Burhan SaifAddin ⋅ Trupti Mohanty ⋅ Taylor Sparks

Resonance: From Teacher to Self-Distillation in LLMs for Reaction Prediction

Anagha Aneesh ⋅ Sebastian Ibarraran ⋅ Frank Hu ⋅ Jason Liu ⋅ Grant Rotskoff

Scaling Laws for Materials Reasoning: From Compute to Scientific Discovery

Stefano Falletta

Scaling Laws for Materials Reasoning: From Compute to Scientific Discovery

Savannah Thais

Scaling Laws for Materials Reasoning: From Compute to Scientific Discovery

Yatao Bian

Automating Discovery That Delivers: When AI Meets the Messiness of Real Experiments

Julie Shah

Automating Discovery That Delivers: When AI Meets the Messiness of Real Experiments

Sergei Kalinin

Automating Discovery That Delivers: When AI Meets the Messiness of Real Experiments

Zeyuan Ni

Opening Remarks

Mara Schilling-Wilhelmi ⋅ N M Anoop Krishnan ⋅ Vijay K Narasimhan ⋅ Stefano Martiniani ⋅ Santiago Miret