The hydrogenation of CO₂ holds promise for transforming the production of renewable fuels and chemicals. However, the challenge lies in developing robust and selective catalysts for this process. Transition metal oxide catalysts, particularly cobalt oxide, have shown potential for CO₂ hydrogenation, with performance heavily reliant on crystal phase and morphology. Achieving precise control over these catalyst attributes through colloidal nanoparticle synthesis could pave the way for catalyst and process advancement. Yet, navigating the complexities of colloidal nanoparticle syntheses, governed by numerous input variables, poses a significant challenge in systematically controlling resultant catalyst features. We present a multivariate Bayesian optimization, coupled with a data-driven classifier, to map the synthetic design space for colloidal CoO nanoparticles and simultaneously optimize them for multiple catalytically relevant features within a target crystalline phase. The optimized experimental conditions yielded small, phase-pure rock salt CoO nanoparticles of uniform size and shape. These optimized nanoparticles were then supported on SiO₂ and assessed for thermocatalytic CO₂ hydrogenation against larger, polydisperse CoO nanoparticles on SiO₂ and a conventionally prepared catalyst. The optimized CoO/SiO₂ catalyst consistently exhibited higher activity and CH₄ selectivity (ca. 98%) across various pretreatment reduction temperatures as compared to the other catalysts. This remarkable performance was attributed to particle stability and consistent H* surface coverage, even after undergoing the highest temperature reduction, achieving a more stable catalytic species that resists sintering and carbon occlusion.

中文翻译：

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用于 CO2 加氢催化的 CoO 纳米颗粒的多元贝叶斯优化


CO ₂ 的加氢有望改变可再生燃料和化学品的生产。然而，挑战在于为这一过程开发稳健且选择性的催化剂。过渡金属氧化物催化剂，特别是氧化钴，已显示出 CO ₂ 加氢的潜力，其性能严重依赖于晶相和形态。通过胶体纳米粒子合成实现对这些催化剂属性的精确控制可以为催化剂和工艺的进步铺平道路。然而，应对由众多输入变量控制的胶体纳米粒子合成的复杂性，对系统地控制所得催化剂特征提出了重大挑战。我们提出了多元贝叶斯优化，结合数据驱动的分类器，来绘制胶体 CoO 纳米颗粒的合成设计空间，并同时针对目标晶相内的多个催化相关特征对其进行优化。优化的实验条件产生了尺寸和形状均一的小型、纯相岩盐 CoO 纳米颗粒。然后将这些优化的纳米颗粒负载在 SiO ₂ 上，并针对 SiO ₂ 上较大的多分散 CoO 纳米颗粒和常规制备的催化剂评估热催化 CO ₂ 加氢。与其他催化剂相比，优化的 CoO/SiO ₂ 催化剂在各种预处理还原温度下始终表现出更高的活性和 CH ₄ 选择性（约 98%）。 这种卓越的性能归功于颗粒稳定性和一致的 H* 表面覆盖，即使在经历最高温度降低后，也能获得更稳定的催化物质，从而抵抗烧结和碳吸留。