MultiPhaseWorld: A Multimodal Benchmark for Structural Evolution in Multiphase Systems

Large language models (LLMs) and multimodal large language models (MLLMs) are increasingly applied to scientific problems. However, existing scientific benchmarks primarily evaluate factual knowledge and static structure understanding, leaving evolution reasoning in diverse chemical environments underexplored. We introduce $MultiPhaseWorld$, a multimodal benchmark for evaluating scientific reasoning over structural evolution in multiphase systems. Multiphase systems involve complex interactions across phases and diverse chemical environments, making structural evolution challenging to understand. At the same time, this complexity provides a rich setting for evaluating the reasoning capabilities of LLMs and MLLMs across multiple scales, including adsorbate, surface, interface, layer, and bulk environment. MultiPhaseWorld contains 11,075 text and multimodal questions across 28 tasks and 14 capability dimensions, organized into four progressive levels: $Multiphase$ $Structure$ $Perception$, $Perturbation$ $Response$ $Reasoning$, $Structural$ $Evolution$ $Reasoning$, and $Structural$ $Prediction$. The benchmark is built from 336 solid-solid and 400 solid-gas systems. Controlled structural perturbations, structural optimization, and molecular dynamics simulations are used to generate structural responses, evolved structures, and evolution trajectories. The strongest models achieve only 58% average accuracy on text tasks and 51% on multimodal tasks, remaining more than 20 percentage points below the expert performance. Fine-grained results further reveal limitations in integrating physicochemical knowledge, reasoning about evolution relationships, and resolving subtle structural changes. Overall, current models show partial understanding of chemical information, but remain limited in linking explicit perturbations to structural responses, tracking state evolution, and predicting perturbation effects.