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Alloying is an effective strategy to modulate a metal catalyst's electronic structure and optimize its performance, but developing a fundamental design principle has been challenging due to the geometric and electronic disturbance between the active atom and its microenvironment. We introduce a descriptor, coordination impact, which combines ligand and structural effects to quantify the influence of neighboring atoms on the electronic structure of the adsorption site. Using first-principles simulations, microkinetic model and experimental data, we thoroughly examine the catalytic performance of RuM alloys for ammonia decomposition using this descriptor. The microenvironment influences the activity of adsorption site by modulating the orbital interaction between the active site and adsorbate. The descriptor follows a volcano-shaped relationship with reaction rates, consistent with Sabatier principle, and the predicted rates are experimentally validated.
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http://dx.doi.org/10.1002/anie.202513385 | DOI Listing |
J Colloid Interface Sci
September 2025
School of Materials Science and Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, PR China; Zhejiang Sci-Tech University Shengzhou Innovation Research Institute, Shengzhou 312400, PR China. Electronic address:
Suppressing photoinduced charge recombination represents a critical challenge in photocatalytic ammonia (NH) decomposition for hydrogen (H) production. Herein, we propose a dual-cocatalyst system comprising plasmonic silver (Ag) and nickel oxide (NiO), which synergistically construct an Ag → titanium dioxide (TiO) → NiO directional electron cascade on TiO surfaces through work-function-induced interfacial charge transfer. The optimized 3 %Ag-1 %NiO-TiO reaches a significantly photocatalytic H production rate of 2366.
View Article and Find Full Text PDFEnviron Sci Technol
September 2025
Advanced Interdisciplinary Institute of Environment and Ecology, Guangdong Provincial Key Laboratory of Wastewater Information Analysis and Early Warning, Beijing Normal University, Zhuhai 519087, China.
Polyamide (PA) nanofiltration (NF) membranes represent a promising approach to safe drinking water production. Yet, selective removal of contaminants while retaining essential minerals remains a critical challenge for cost-effective water treatment processes. Here, we employed ammonia bicarbonate (AB) as an economical additive to modify interfacial polymerization (IP) for developing high-performance NF membranes suitable for drinking water applications.
View Article and Find Full Text PDFBiology (Basel)
August 2025
Engineering Research Center of Polyploid Fish Reproduction and Breeding of the State Education Ministry, College of Life Sciences, Hunan Normal University, Changsha 410081, China.
The lotus-fish co-culture (LFC) system leverages plant-fish symbiosis to optimize aqua-culture environments, enhancing both economic and ecological yields. However, the eco-logical mechanisms of microbial communities in LFC systems remain poorly understood, particularly regarding the functional roles of fungi, archaea, and viruses. This study compared microbiota (viruses, archaea, fungi) in water, sediment, and fish (crucian carp) gut of LFC and intensive pond culture (IPC) systems using integrated metagenomic and environmental analyses.
View Article and Find Full Text PDFEnergy Fuels
August 2025
Aragón Institute of Engineering Research (I3A), Department of Chemical and Environmental Engineering, University of Zaragoza, 50018 Zaragoza, Spain.
The pursuit of environmentally sustainable alternatives to conventional fuels is essential today. Ammonia emerges as a promising candidate, though its inherent disadvantages must be addressed. Co-firing ammonia with fuels exhibiting superior thermochemical properties is one of the most widely accepted solutions.
View Article and Find Full Text PDFJ Chem Theory Comput
September 2025
Department of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.
Discovering chemical reaction pathways using quantum mechanics is impractical for many systems of practical interest because of unfavorable scaling and computational cost. While machine learning interatomic potentials (MLIPs) trained on quantum mechanical data offer a promising alternative, they face challenges for reactive systems due to the need for extensive sampling of the potential energy surface in regions that are far from equilibrium geometries. Unfortunately, traditional MLIP training protocols are not designed for comprehensive reaction exploration.
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