Sustainable and green energy sources are in high demand to meet the current human energy needs and environmental requirements. Hydrogen energy, with the highest energy density and zero carbon emission, is considered a potential solution. Hydrogen is primarily produced by splitting water. Rationally designed electrocatalysts are required to promote the cathodic hydrogen evolution reaction (HER) and the anodic oxygen evolution reaction (OER). Organic polymer matrices provide new opportunities for electrocatalytic water splitting due to their special physical and chemical characteristics and thermal stability. This article explains the role of organic polymers in electrocatalytic water decomposition from three aspects: ion-conductive polymers, conjugated conductive polymers, and carbon materials derived from organic polymers. We hope that this article will provide more rational ideas and promote the design of organic polymers for water-splitting electrocatalysis, and furnish more technical insights for the future of water electrolysis.

The electrochemical reaction that involves the splitting of water into hydrogen and oxygen gas is the superior technique for sustainable energy conversion and storage without the environmentally damaging effects of fossil fuels. To date, a large number of electrocatalysts have been used for electrochemical water splitting (EWS). Nowadays, the quest for a universal pH stable bifunctional electrocatalyst that can efficiently enhance the hydrogen and oxygen evolution reactions (HERs and OERs) is gaining significant interest in the research community. This approach avoids the divergence in the pH of the electrolyte for OER and HER activity and effectively reduces the difficulty and system cost in practical EWS. This article highlights engineering strategies and challenges in designing prospective universal pH-stable electrocatalysts with feasible OER and HER pathways for full water splitting over a wide pH range.

Hydrogen production from water electrolysis with renewable energy input has been the focus of tremendous attention, as hydrogen is widely advocated as a clean energy carrier. In order to realize large-scale hydrogen generation from water splitting, it is essential to develop competent and robust electrocatalysts that will substantially decrease the overpotential requirement and improve energy efficiency. Recent advances in electrocatalyst design reveal that interfacial engineering is an effective approach in tuning the adsorption–desorption abilities of key catalytic intermediates on active sites, accelerating electron transfer, and stabilizing the active sites for long-term operation. Consequently, a large number of hybrid electrocatalysts consisting of metal/compound interfaces have been demonstrated to exhibit superior performance for electrocatalytic hydrogen evolution from water. This article highlights examples of these hybrid electrocatalysts, including noble metal and non-noble metal candidates interfaced with a variety of compounds. Specific emphasis is placed on the synthetic methods, reaction mechanisms, and electrocatalytic activities, which are envisioned to inspire the design and development of further improved electrocatalysts for hydrogen evolution from water splitting on an industrial scale.

This is the third and final part of a series in MRS Bulletin on achieving a path to a green card in the United States as it relates to scientific researchers. Following articles will focus on more specific aspects of the immigration process and go into more depth using practical examples.

Electrochemical water splitting is one of the promising energy-conversion technologies to utilize intermittent renewable energy and produce hydrogen for clean energy. Pyrite-type transition-metal dichalcogenides have great potential to be applied for energy conversion. This article reviews recent progress in the performance of pyrite-type nanomaterials on the hydrogen evolution reaction, including an overview of crystal and electronic structure of pyrites and the principles of improving electrocatalytic activity and stability for S-based, Se-based, ternary, and other pyrites.

Water-splitting electrolysis, using a renewable power source, has been widely considered as a promising energy conservation and storage technology that is environmentally friendly. In order to lower the required energy barrier and to improve the energy-conversion efficiency of hydrogen evolution and oxygen evolution on the electrodes, highly efficient and durable electrocatalysts are essential. To date, various preparation methods and theoretical models have been developed to accelerate the catalyst design and to further understand the associated electrocatalytic mechanism. In this issue of MRS Bulletin, all aspects of non-noble metal-based electrocatalysts for water splitting involving standard methodology, surface electronic structure engineering, morphology design, interface effects, pH operation range, activity descriptors, and operational stability are discussed. These discussions indicate the importance of materials innovations for the realization of highly efficient and durable electrocatalysts for large-scale cost-effective water splitting.

Applying machine learning (ML) methods to accelerate the search for new materials with improved properties has gained increasing attention in recent years. Using nonadaptive ML approaches that do not have an iterative feedback loop can perform poorly in extrapolations at previously unexplored search space, especially when trained on small data sets. We performed numerical simulations on two data sets that exhibit distinct composition–property relationships and explored the relative efficacies of adaptive ML strategies in identifying the optimal material composition with the highest. Adaptive ML methods show promise for extrapolation and find compositions with properties better than those in the training data, but the rate of discovery is dictated by the nuances of the composition–property landscape. The outcome of this work has key implications in developing strategies that employ ML methods for navigating a vast search space of combinatorial possibilities.