利用机器学习零距离发现高性能、低成本有机电池材料

IF 14.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Jaehyun Park, Farshud Sorourifar, Madhav R. Muthyala, Abigail M. Houser, Madison Tuttle, Joel A. Paulson* and Shiyu Zhang*, 
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引用次数: 0

摘要

有机电极材料(OEM)由碳、氮和氧等丰富元素组成,为依赖有限金属资源的传统电极材料提供了可持续的替代品。有机化合物结构的多样性提供了几乎无限的设计空间;然而,通过爱迪生式的试错方法探索这一空间既昂贵又耗时。在这项工作中,我们开发了一个新框架 SPARKLE,它将计算化学、分子生成和机器学习结合起来,实现了对 OEM 的零射中预测,同时平衡了回报(比能量)、风险(可溶性)和成本(可合成性)。我们证明,在内插法和外推法任务上,SPARKLE 明显优于其他黑盒机器学习算法。通过在超过 67 万种有机化合物的设计空间中部署 SPARKLE,我们识别出了≈5000 种新型 OEM 候选化合物。我们合成了其中的 27 种,并将其制成纽扣电池进行实验测试。在 SPARKLE 发现的 OEM 中,62.9% 超过了基准性能指标,比仅凭直觉选择的 OEM 提高了 3 倍(20.8% 基于六年的实验室经验)。在 27 种候选 OEM 中,性能最好的 OEM 所表现出的比能量和循环稳定性都超过了最先进的水平,而合成成本却只有最先进水平的一小部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Zero-Shot Discovery of High-Performance, Low-Cost Organic Battery Materials Using Machine Learning

Zero-Shot Discovery of High-Performance, Low-Cost Organic Battery Materials Using Machine Learning

Organic electrode materials (OEMs), composed of abundant elements such as carbon, nitrogen, and oxygen, offer sustainable alternatives to conventional electrode materials that depend on finite metal resources. The vast structural diversity of organic compounds provides a virtually unlimited design space; however, exploring this space through Edisonian trial-and-error approaches is costly and time-consuming. In this work, we develop a new framework, SPARKLE, that combines computational chemistry, molecular generation, and machine learning to achieve zero-shot predictions of OEMs that simultaneously balance reward (specific energy), risk (solubility), and cost (synthesizability). We demonstrate that SPARKLE significantly outperforms alternative black-box machine learning algorithms on interpolation and extrapolation tasks. By deploying SPARKLE over a design space of more than 670,000 organic compounds, we identified ≈5000 novel OEM candidates. Twenty-seven of them were synthesized and fabricated into coin-cell batteries for experimental testing. Among SPARKLE-discovered OEMs, 62.9% exceeded benchmark performance metrics, representing a 3-fold improvement over OEMs selected by human intuition alone (20.8% based on six years of prior lab experience). The top-performing OEMs among the 27 candidates exhibit specific energy and cycling stability that surpass the state-of-the-art while being synthesizable at a fraction of the cost.

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来源期刊
CiteScore
24.40
自引率
6.00%
发文量
2398
审稿时长
1.6 months
期刊介绍: The flagship journal of the American Chemical Society, known as the Journal of the American Chemical Society (JACS), has been a prestigious publication since its establishment in 1879. It holds a preeminent position in the field of chemistry and related interdisciplinary sciences. JACS is committed to disseminating cutting-edge research papers, covering a wide range of topics, and encompasses approximately 19,000 pages of Articles, Communications, and Perspectives annually. With a weekly publication frequency, JACS plays a vital role in advancing the field of chemistry by providing essential research.
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