Physics-grounded multi-agent systems (AdsMind) for adsorption configuration discovery will exhibit coalition-based equilibrium deviations when applied to heterogeneous catalyst surfaces under operating conditions, where agent coordination failures predict surface reconstruction errors in scalable Harmony-Search global optimization.
Physics-grounded multi-agent systems (AdsMind) for adsorption configuration discovery will exhibit coalition-based equilibrium deviations when applied to heterogeneous catalyst surfaces under operating conditions, where agent coordination failures predict surface reconstruction errors in scalable Harmony-Search global optimization.
Adversarial Debate Score
38% survival rate under critique
Expert panel critique
Independent views, each critiquing the hypothesis on its own — the score rewards genuine disagreement and discounts consensus.
Supporting Research Papers
- AdsMind: A Physics-Grounded Multi-Agent System for Self-Correcting Discovery of Adsorption Configurations on Heterogeneous Catalyst Surfaces
Identifying the lowest-energy surface-adsorbate configuration is critical for modeling heterogeneous catalysis, yet exhaustive exploration with ab initio calculations is computationally prohibitive. M...
- Scalable Prediction of Complex Surface Reconstructions under Operating Conditions via Harmony-Search-Based Global Optimization
The dynamic structural evolution of catalyst surfaces under operating conditions dictates catalytic performance, yet capturing these reconstructions atomically remains challenging. Global optimization...
- OptiAgent: End-to-End Optimization Modeling via Multi-Agent Iterative Refinement
We propose OptiAgent, a multi-agent framework that, given a natural language description of an Operations Research problem, is able to output a solver-ready mathematical formulation as well as executa...
- Selectivity- and Activity-Aware Catalyst Descriptors for CO₂ Hydrogenation on Alloy Nanocatalysts using Machine-Learned Force Fields
Adsorption energy distributions (AEDs) have emerged as a powerful and increasingly adopted descriptor for catalytic performance in high-entropy alloys and, more recently, in conventional metallic allo...
- EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery
LLM-based agents have shown increasing potential in automating scientific discovery. Given an optimizable metric and an execution environment, they can propose, validate, and iterate scientific soluti...
Computational Result
An LLM's reading of the literature — not computational verification.
Multi-agent systems may influence adsorption but require further validation.
Method: literature_meta · Result: inconclusive · Confidence: 60%
Formal Verification
Z3 checks whether the hypothesis is internally consistent, not whether it is empirically true.