Materials development often confronts a dilemma as it needs to satisfy multifunctional, often conflicting, demands. For example, thermoelectric conversion requires high electrical conductivity, a high Seebeck coefficient, and low thermal conductivity, despite the fact that these three properties are normally closely correlated. Nanostructuring techniques have been shown to break the correlations to some extent; however, optimal design has been a major challenge due to the extraordinarily large degrees of freedom in the structures. By taking graphene nanoribbons (GNRs) as a representative thermoelectric material, we carried out structural optimization by alternating multifunctional (phonon and electron) transport calculations and Bayesian optimization to resolve the trade-off. As a result, we have achieved multifunctional structural optimization with an efficiency more than five times that achieved by random search. The obtained GNRs with optimized antidots significantly enhance the thermoelectric figure of merit by up to 11 times that of the pristine GNR. Knowledge of the optimal structure further provides new physical insights that independent tuning of electron and phonon transport properties can be realized by making use of zigzag edge states and aperiodic nanostructuring. The demonstrated optimization framework is also useful for other multifunctional problems in various applications.

中文翻译：

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贝叶斯优化的石墨烯热电多功能结构设计。

材料开发通常需要满足多功能（通常是相互冲突）的需求，因而面临两难选择。例如，尽管实际上这三个特性通常紧密相关，但是热电转换需要高电导率，高塞贝克系数和低热导率。纳米结构技术已显示出一定程度的打破了相关性。但是，由于结构中的自由度过高，因此优化设计一直是一项重大挑战。通过以石墨烯纳米带（GNR）为代表的热电材料，我们通过交替进行多功能（声子和电子）传输计算和贝叶斯优化来进行结构优化，以解决这一问题。因此，我们已经实现了多功能结构优化，其效率是随机搜索的五倍以上。获得的具有优化解毒剂的GNR显着提高了热电品质因数，是其原始GNR的11倍。最佳结构的知识进一步提供了新的物理见解，即可以通过使用之字形边缘态和非周期性纳米结构来实现电子和声子传输特性的独立调节。所展示的优化框架对于各种应用程序中的其他多功能问题也很有用。最佳结构的知识进一步提供了新的物理见解，即可以通过使用之字形边缘态和非周期性纳米结构来实现电子和声子传输特性的独立调节。所展示的优化框架对于各种应用程序中的其他多功能问题也很有用。最佳结构的知识进一步提供了新的物理见解，即可以通过使用之字形边缘态和非周期性纳米结构来实现电子和声子传输特性的独立调节。所展示的优化框架对于各种应用程序中的其他多功能问题也很有用。