Designing multi-functional alloys requires exploring high-dimensional composition-structure-property spaces, yet current tools are limited to low-dimensional projections and offer limited support for sensitivity or multi-objective tradeoff reasoning. We introduce AlloyLens, an interactive visual analytics system combining a coordinated scatterplot matrix (SPLOM), dynamic parameter sliders, gradient-based sensitivity curves, and nearest neighbor recommendations. This integrated approach reveals latent structure in simulation data, exposes the local impact of compositional changes, and highlights tradeoffs when exact matches are absent. We validate the system through case studies co-developed with domain experts spanning structural, thermal, and electrical alloy design.

翻译：设计多功能合金需要探索高维的成分-结构-性能空间，然而现有工具仅限于低维投影，且对敏感性或多目标权衡推理的支持有限。本文提出AlloyLens，一种交互式可视化分析系统，它集成了协调散点图矩阵（SPLOM）、动态参数滑块、基于梯度的敏感性曲线和最近邻推荐功能。该集成方法能够揭示仿真数据中的潜在结构，展现成分变化的局部影响，并在缺乏精确匹配时突出权衡关系。我们通过与领域专家合作开展的结构、热学和电学合金设计案例研究，验证了该系统的有效性。