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A review highlights improvements in synthesizing and stabilizing multielement nanoparticles. 

Solar-thermal evaporation is a promising technology for energy-efficient desalination, but salt accumulation on solar absorbers and system longevity are the major challenges that hinder its widespread application. In this study, we present a sustainable Janus wood evaporator that overcomes these challenges and achieves a record-high evaporation efficiencies in hypersaline water, one of the most difficult water sources to treat via desalination. The Janus wood evaporator has asymmetric surface wettability, where the top layer acts as a hydrophobic solar absorber with water blockage and salt resistance, while the bottom hydrophilic wood layer allows for rapid water replenishment and superior thermal insulation. An evaporation efficiency of 82.0% is achieved for 20% NaCl solution under 1 sun, and persistent salt-resistance is observed during a 10-cycle long-term test. To ensure the environmental impact of the Janus wood evaporator, for the first time, a life cycle assessment (LCA) is conducted to compare this Janus wood evaporator with the emerging Janus evaporators, indicating a functional and more sustainable opportunity for off-grid desalination and humanitarian efforts. 

Wood materials are being reinvented to carry superior properties for a variety of new applications. Cutting‐edge nanomanufacturing transforms traditional bulky and low‐value woods into advanced materials that have desired structures, durability, and functions to replace nonrenewable plastics, polymers, and metals. Here, a first prospect report on how novel nanowood materials have been developed and applied in water and associated industries is provided, wherein their unique features and promises are discussed. First, the unique hierarchical structure and associated properties of the material are introduced, and then how such features can be harnessed and modified by either bottom‐up or top‐down manufacturing to enable different functions for water filtration, chemical adsorption and catalysis, energy and resource recovery, as well as energy‐efficient desalination and environmental cleanup are discussed. The study recognizes that this is a nascent but very promising field; therefore, insights are offered to encourage more research and development. Trees harness solar energy and CO2 and provide abundant carbon‐negative materials. Once harvested and utilized, it is believed that advanced wood materials will play a vital role in enabling a circular water economy. 

The rapid increase in both quantity and complexity of data that are being generated daily in the field of environmental science and engineering (ESE) demands accompanied advancement in data analytics. Advanced data analysis approaches, such as machine learning (ML), have become indispensable tools for revealing hidden patterns or deducing correlations for which conventional analytical methods face limitations or challenges. However, ML concepts and practices have not been widely utilized by researchers in ESE. This feature explores the potential of ML to revolutionize data analysis and modeling in the ESE field, and covers the essential knowledge needed for such applications. First, we use five examples to illustrate how ML addresses complex ESE problems. We then summarize four major types of applications of ML in ESE: making predictions; extracting feature importance; detecting anomalies; and discovering new materials or chemicals. Next, we introduce the essential knowledge required and current shortcomings in ML applications in ESE, with a focus on three important but often overlooked components when applying ML: correct model development; proper model interpretation; and sound applicability analysis. Finally, we discuss challenges and future opportunities in the application of ML tools in ESE to highlight the potential of ML in this field.