用供应链风险优化合金设计，兼顾性能与可持续性。
Supply Risk-Aware Alloy Discovery and Design
- 结合语言模型与文本分析预测原料供应风险
- 通过批量贝叶斯优化找到性能与风险平衡的高熵合金
- 适用于关注可持续性的材料研发团队
材料设计是创新的关键驱动力，但忽视材料及其供应链中的技术、经济和环境风险，可能导致不可持续且高风险的解决方案。为此，我们提出一种新的风险感知设计方法，将供应链意识设计策略融入材料开发过程。该方法利用现有语言模型和文本分析，构建专用模型以预测材料原料的供应风险指数。为高效探索多目标、多约束的设计空间，采用批量贝叶斯优化（BBO），识别出在性能与供应风险之间达到帕累托最优的高熵合金（HEAs）。以MoNbTiVW体系为例，在四种场景下验证了该方法的有效性，凸显将供应风险纳入设计过程的重要性。通过同时优化性能与供应风险，确保所开发合金不仅高性能，而且可持续且经济可行。这一整合方法标志着材料发现与设计迈向未来的重要一步：全面考虑可持续性、供应链动态及全生命周期分析。
原文摘要 · Abstract (English)
Materials design is a critical driver of innovation, yet overlooking the technological, economic, and environmental risks inherent in materials and their supply chains can lead to unsustainable and risk-prone solutions. To address this, we present a novel risk-aware design approach that integrates Supply-Chain Aware Design Strategies into the materials development process. This approach leverages existing language models and text analysis to develop a specialized model for predicting materials feedstock supply risk indices. To efficiently navigate the multi-objective, multi-constraint design space, we employ Batch Bayesian Optimization (BBO), enabling the identification of Pareto-optimal high entropy alloys (HEAs) that balance performance objectives with minimized supply risk. A case study using the MoNbTiVW system demonstrates the efficacy of our approach in four scenarios, highlighting the significant impact of incorporating supply risk into the design process. By optimizing for both performance and supply risk, we ensure that the developed alloys are not only high-performing but also sustainable and economically viable. This integrated approach represents a critical step towards a future where materials discovery and design seamlessly consider sustainability, supply chain dynamics, and comprehensive life cycle analysis.
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