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Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions
The Journal of Physical Chemistry Letters ( IF 4.8 ) Pub Date : 2018-01-19 00:00:00 , DOI: 10.1021/acs.jpclett.7b02895 Dilip Krishnamurthy 1 , Vaidish Sumaria 1 , Venkatasubramanian Viswanathan 1
The Journal of Physical Chemistry Letters ( IF 4.8 ) Pub Date : 2018-01-19 00:00:00 , DOI: 10.1021/acs.jpclett.7b02895 Dilip Krishnamurthy 1 , Vaidish Sumaria 1 , Venkatasubramanian Viswanathan 1
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Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔGopt. We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.
中文翻译：
识别电催化反应正确描述符的最大可预测性方法
通常使用密度泛函理论（DFT）计算来确定新的候选材料，这些候选材料的活动接近热力学或比例关系所施加的基本极限。DFT计算与固有的不确定性相关，这限制了描绘具有高活性的材料（可区分性）的能力。DFT中错误估计功能的开发使不确定性能够通过活动预测模型传播。在这项工作中，我们演示了一种通过热力学活动模型传播不确定性的方法，从而导致计算活动的概率分布以及由此产生的期望值。定义了一个新指标“预测效率”，G opt。我们证明了四个重要的电化学反应的框架：氢气释放，氯释放，氧气还原和氧气释放。未来的研究可以利用预期的活性和预测效率来显着提高高活性材料候选物的预测准确性。
更新日期：2018-01-19
中文翻译：
识别电催化反应正确描述符的最大可预测性方法
通常使用密度泛函理论（DFT）计算来确定新的候选材料，这些候选材料的活动接近热力学或比例关系所施加的基本极限。DFT计算与固有的不确定性相关，这限制了描绘具有高活性的材料（可区分性）的能力。DFT中错误估计功能的开发使不确定性能够通过活动预测模型传播。在这项工作中，我们演示了一种通过热力学活动模型传播不确定性的方法，从而导致计算活动的概率分布以及由此产生的期望值。定义了一个新指标“预测效率”，G opt。我们证明了四个重要的电化学反应的框架：氢气释放，氯释放，氧气还原和氧气释放。未来的研究可以利用预期的活性和预测效率来显着提高高活性材料候选物的预测准确性。
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