Recharged Catalyst with Memristive Nitrogen Reduction Activity through Learning Networks of Spiking Neurons
Recharged Catalyst with Memristive Nitrogen Reduction Activity through Learning Networks of Spiking Neurons
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DOI：
10.1021/jacs.0c12458
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发表时间：
2021-03-31
影响因子：
15
通讯作者：
Sun, Yan
中科院分区：
文献类型：
--
作者：
Zhou, Gang;Li, Tinghui;Sun, Yan
从N-2到NH3的电催化研究越来越多，因为它为取代目前的Haber-Bosch方法提供了一条环境友好的途径。不幸的是，从N-2到NH3的转化远远低于大规模实施所需的水平。受尖峰神经网络信号记忆的启发，我们开发了可充电催化剂技术，通过可管理的电刺激来激活和记忆最佳催化活性。在这里，我们设计了双面FeReS3 Janus层，它模拟了由阻性开关突触组成的多神经元网络，使一系列有趣的多相转变能够激活未被发现的催化活性；激活能垒通过两个不等价表面之间的活性位点转换而明显降低。电场刺激下FeReS3的法拉第效率为43%，NH3合成的最高速率为203mgh(-1)mg(-1)。此外，这种可充电催化剂显示出前所未有的催化性能，可持续长达216小时，并可通过简单的充电操作重复激活。
Electrocatalysis from N-2 to NH3 has been increasingly studied because it provides an environmentally friendly avenue to take the place of the current Haber-Bosch method. Unfortunately, the conversion of N-2 to NH3 is far below the necessary level for implementation at a large scale. Inspired by signal memory in a spiking neural network, we developed rechargeable catalyst technology to activate and remember the optimal catalytic activity using manageable electrical stimulation. Herein, we designed double-faced FeReS3 Janus layers that mimic a multiple-neuron network consisting of resistive switching synapses, enabling a series of intriguing multiphase transitions to activate undiscovered catalytic activity; the activation energy barrier is clearly reduced via an active site conversion between two nonequivalent surfaces. Electrical field-stimulated FeReS3 demonstrates a Faradaic efficiency of 43% and the highest rate of 203 mu g h(-1) mg(-1) toward NH3 synthesis. Moreover, this rechargeable catalyst displays unprecedented catalytic performance that persists for up to 216 h and can be repeatedly activated through a simple charging operation.