自动寻找最佳液体配方，让表面润湿性精准可控
RAISE: A self-driving laboratory for interfacial property formulation discovery
- 机器人闭环系统自动调配液体并测接触角
- 每分钟可测1个接触角，支持多目标优化
- 适合需要精准调控润湿性的材料研发人员
表面润湿性是生物医疗器件、涂层和纺织品的关键设计参数。接触角测量可量化液-固相互作用，且强烈依赖于液体配方。本文提出机器人自主成像表面评估系统（RAISE），一个闭环自驱动实验室，能够将液体配方优化与表面润湿性评估相连接。RAISE包含完整的实验调度器，可混合液体成分形成不同配方，将液滴转移至高通量平台，并利用抓取-放置相机工具实现自动化液滴图像采集。系统还配备自动图像处理流程以测量接触角。该闭环实验调度器与贝叶斯优化（BO）客户端集成，可根据历史接触角数据迭代探索新配方，以满足用户设定的目标。系统以高通量方式运行，测量速率达约每分钟1个接触角。我们展示了RAISE在探究表面活性剂润湿性及组合配方补偿纯度差异方面的应用。多目标贝叶斯优化表明，可通过目标导向的优度评分，精准找到符合特定应用需求的最优配方，该评分优先考虑目标接触角范围内的配方、最少表面活性剂用量及最低成本。本工作证明了RAISE在闭环系统中自主关联液体配方与接触角测量的能力，利用多目标优化高效识别出符合研究人员定义标准的最优配方。
原文摘要 · Abstract (English)
Surface wettability is a critical design parameter for biomedical devices, coatings, and textiles. Contact angle measurements quantify liquid-surface interactions, which depend strongly on liquid formulation. Herein, we present the Robotic Autonomous Imaging Surface Evaluator (RAISE), a closed-loop, self-driving laboratory that is capable of linking liquid formulation optimization with surface wettability assessment. RAISE comprises a full experimental orchestrator with the ability of mixing liquid ingredients to create varying formulation cocktails, transferring droplets of prepared formulations to a high-throughput stage, and using a pick-and-place camera tool for automated droplet image capture. The system also includes an automated image processing pipeline to measure contact angles. This closed loop experiment orchestrator is integrated with a Bayesian Optimization (BO) client, which enables iterative exploration of new formulations based on previous contact angle measurements to meet user-defined objectives. The system operates in a high-throughput manner and can achieve a measurement rate of approximately 1 contact angle measurement per minute. Here we demonstrate RAISE can be used to explore surfactant wettability and how surfactant combinations create tunable formulations that compensate for purity-related variations. Furthermore, multi-objective BO demonstrates how precise and optimal formulations can be reached based on application-specific goals. The optimization is guided by a desirability score, which prioritizes formulations that are within target contact angle ranges, minimize surfactant usage and reduce cost. This work demonstrates the capabilities of RAISE to autonomously link liquid formulations to contact angle measurements in a closed-loop system, using multi-objective BO to efficiently identify optimal formulations aligned with researcher-defined criteria.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。