Self-supported electrode based on two-dimensional NiPS3 for supercapacitor application

Advanced development of anion-exchange membrane electrolyzers for hydrogen production: from anion-exchange membranes to membrane electrode assemblies

Anion-exchange membrane water electrolysis (AEMWE) has attracted attention owing to its operation in alkaline environments, which offers the advantage of not requiring the use of precious metals. Additionally, AEMWE exhibits higher kinetics in the hydrogen evolution reaction, enabling higher hydrogen production efficiency. The anion-exchange membrane (AEM) fabrication, catalyst design, and membrane electrode assembly (MEA) are crucial for enhancing the total water electrolysis performance. There is an urgent need to summarize the advances in the development of AEMWE to pave the way for the commercialization of AEMWE. In this review, first, the fundamental principles of AEMWE technology are introduced. Second, the optimization of AEM with high ion conductivity and high stability through innovative synthetic methods are discussed in detail. Third, the designs of catalysts to increase the reaction rates by regulating the OH-adsorption environment and relieving OH blockage are introduced. Last but not least, a systematic summary of the concepts of 3D-ordered MEA, 3D-unified MEA, and 3D-self-supported MEA is presented. This review would be helpful to enhance the overall performance of AEMWE and promote the development of green hydrogen energy.

Reliable Memristor Crossbar Array Based on 2D Layered Nickel Phosphorus Trisulfide for Energy-Efficient Neuromorphic Hardware

Designing reliable and energy-efficient memristors for artificial synaptic arrays in neuromorphic computing beyond von Neumann architecture remains a challenge. Here, memristors based on emerging layered nickel phosphorus trisulfide (NiPS3 ) are reported that exhibit several favorable characteristics, including uniform bipolar nonvolatile switching with small operating voltage (<1 V), fast switching speed (< 20 ns), high On/Off ratio (>102 ), and the ability to achieve programmable multilevel resistance states. Through direct experimental evidence using transmission electron microscopy and energy dispersive X-ray spectroscopy, it is revealed that the resistive switching mechanism in the Ti/NiPS3 /Au device is related to the formation and dissolution of Ti conductive filaments. Intriguingly, further investigation into the microstructural and chemical properties of NiPS3 suggests that the penetration of Ti ions is accompanied by the drift of phosphorus-sulfur ions, leading to induced P/S vacancies that facilitate the formation of conductive filaments. Furthermore, it is demonstrated that the memristor, when operating in quasi-reset mode, effectively emulates long-term synaptic weight plasticity. By utilizing a crossbar array, multipattern memorization and multiply-and-accumulate (MAC) operations are successfully implemented. Moreover, owing to the highly linear and symmetric multiple conductance states, a high pattern recognition accuracy of ≈96.4% is demonstrated in artificial neural network simulation for neuromorphic systems.

Unraveling and leveraging in situ surface amorphization for enhanced hydrogen evolution reaction in alkaline media

Surface amorphization provides electrocatalysts with more active sites and flexibility. However, there is still a lack of experimental observations and mechanistic explanations for the in situ amorphization process and its crucial role. Herein, we propose the concept that by in situ reconstructed amorphous surface, metal phosphorus trichalcogenides could intrinsically offer better catalytic performance for the alkaline hydrogen production. Trace Ru (0.81 wt.%) is doped into NiPS3 nanosheets for alkaline hydrogen production. Using in situ electrochemical transmission electron microscopy technique, we confirmed the amorphization process occurred on the edges of NiPS3 is critical for achieving superior activity. Comprehensive characterizations and theoretical calculations reveal Ru primarily stabilized at edges of NiPS3 through in situ formed amorphous layer containing bridging S22- species, which can effectively reduce the reaction energy barrier. This work emphasizes the critical role of in situ formed active layer and suggests its potential for optimizing catalytic activities of electrocatalysts.

Machine-learning-accelerated screening of single metal atoms anchored on MnPS3 monolayers as promising bifunctional oxygen electrocatalysts

Searching for bifunctional oxygen electrocatalysts with good catalytic performance to promote the oxygen evolution/reduction reactions (OER/ORR) is of great significance to the development of sustainable and renewable clean energy. Herein, we performed density functional theory (DFT) and machine-learning (DFT-ML) hybrid computations to investigate the potential of a series of single transition metal atoms anchored on the experimentally available MnPS₃ monolayer (TM/MnPS₃) as the bifunctional electrocatalysts for the ORR/OER. The results revealed that the interactions of these metal atoms with MnPS₃ are rather strong, thus guaranteeing their high stability for practical applications. Remarkably, the highly efficient ORR/OER can be achieved on Rh/MnPS₃ and Ni/MnPS₃ with lower overpotentials than those of metal benchmarks, which can be further rationalized by establishing the volcano and contour plots. Furthermore, the ML results showed that the bond length of TM atoms with the adsorbed O species (d_TM-O), the number of d electrons (N_e), the d-center (ε_d), the radius (r_TM) and the first ionization energy (I_m) of the TM atoms are the primary descriptors featuring the adsorption behavior. Our findings not only suggest novel highly efficient bifunctional oxygen electrocatalysts, but also provide cost-effective opportunities for the design of single-atom catalysts using the DFT-ML hybrid method.