9 citations · 42 across the 16 of their papers we have counts for
16 papers
LEIA: Learned Environment for Interactive Architected Materials
Haiqian Yang, Yuan Cao, Markus J. Buehler
World models have enabled interactive exploration of game environments and robotic manipulation, but physical engineering remains beyond their reach: real materials exhibit nonline…
A Category-Theoretic Framework from Biological Mechanics to Engineered Stimulus-Response Systems
Lee Marom, Skylar Tibbits, Gioele Zardini +1
Natural materials achieve adaptive behavior through hierarchical organization and coupled mechanisms across scales. Their translation into engineering, however, remains largely heu…
Autonomous Agents Coordinating Distributed Discovery Through Emergent Artifact Exchange
Fiona Y. Wang, Lee Marom, Subhadeep Pal +4
We present ScienceClaw + Infinite, a framework for autonomous scientific investigation in which independent agents conduct research without central coordination, and any contributo…
AI-Guided Human-In-the-Loop Inverse Design of High Performance Engineering Structures
Dat Quoc Ha, Md Ferdous Alam, Markus J. Buehler +2
Inverse design tools such as Topology Optimization (TO) can achieve new levels of improvement for high-performance engineered structures. However, widespread use is hindered by hig…
Generative Artificial Intelligence Extracts Structure-Function Relationships from Plants for New Materials
Rachel K. Luu, Jingyu Deng, Mohammed Shahrudin Ibrahim +4
Large language models (LLMs) have reshaped the research landscape by enabling new approaches to knowledge retrieval and creative ideation. Yet their application in discipline-speci…
Autonomous Inorganic Materials Discovery via Multi-Agent Physics-Aware Scientific Reasoning
Alireza Ghafarollahi, Markus J. Buehler
Conventional machine learning approaches accelerate inorganic materials design via accurate property prediction and targeted material generation, yet they operate as single-shot mo…
AutomataGPT: Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata
Jaime A. Berkovich, Noah S. David, Markus J. Buehler
Cellular automata (CA) provide a minimal formalism for investigating how simple local interactions generate rich spatiotemporal behavior in domains as diverse as traffic flow, ecol…
Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles
Alireza Ghafarollahi, Markus J. Buehler
Advances in artificial intelligence (AI) promise autonomous discovery, yet most systems still resurface knowledge latent in their training data. We present Sparks, a multi-modal mu…
Revealing diatom-inspired materials multifunctionality
Ludovico Musenich, Daniele Origo, Filippo Gallina +2
Diatoms have been described as nanometer-born lithographers because of their ability to create sophisticated three-dimensional amorphous silica exoskeletons. The hierarchical archi…
Rapid and Automated Alloy Design with Graph Neural Network-Powered LLM-Driven Multi-Agent Systems
Alireza Ghafarollahi, Markus J. Buehler
A multi-agent AI model is used to automate the discovery of new metallic alloys, integrating multimodal data and external knowledge including insights from physics via atomistic si…
LifeGPT: Topology-Agnostic Generative Pretrained Transformer Model for Cellular Automata
Jaime A. Berkovich, Markus J. Buehler
Conway's Game of Life (Life), a well known algorithm within the broader class of cellular automata (CA), exhibits complex emergent dynamics, with extreme sensitivity to initial con…
SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning
Alireza Ghafarollahi, Markus J. Buehler
A key challenge in artificial intelligence is the creation of systems capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex pat…
Multicell-Fold: geometric learning in folding multicellular life
Haiqian Yang, Anh Q. Nguyen, Dapeng Bi +2
During developmental processes such as embryogenesis, how a group of cells fold into specific structures, is a central question in biology that defines how living organisms form. E…
AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence
Alireza Ghafarollahi, Markus J. Buehler
The design of alloys is a multi-scale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting exp…
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design
Eric L. Buehler, Markus J. Buehler
We report a mixture of expert strategy to create fine-tuned large language models using a deep layer-wise token-level approach based on low-rank adaptation (LoRA). Starting with a…
ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning
A. Ghafarollahi, M. J. Buehler
Designing de novo proteins beyond those found in nature holds significant promise for advancements in both scientific and engineering applications. Current methodologies for protei…