Your browser does not fully support modern features. Please upgrade for a smoother experience.
Subject:
All Disciplines Arts & Humanities Biology & Life Sciences Business & Economics Chemistry & Materials Science Computer Science & Mathematics Engineering Environmental & Earth Sciences Medicine & Pharmacology Physical Sciences Public Health & Healthcare Social Sciences
Sort by:
Most Viewed Latest Alphabetical (A-Z) Alphabetical (Z-A)
Filter:
All Topic Review Biography Peer Reviewed Entry Video Entry
Topic Review
Single-Atom Versus Dual-Atom Electro-Photocatalysts
The downscaling of active sites to the atomic limit has revolutionized heterogeneous catalysis by maximizing atom utilization efficiency and creating highly uniform coordination centers. A comprehensive comparative analysis of Single-Atom Catalysts (SACs) and Dual-Atom Catalysts (DACs) across electrocatalytic, photocatalytic, and integrated photoelectrochemical applications reveals the distinct mechanistic advantages of multimetallic configurations. The coordination chemistry, electronic metal-support interactions (EMSI), and localized charge dynamics governing these systems dictate their catalytic efficiency. Critically, transitioning from isolated monometallic sites to synergetic homonuclear or heteronuclear diatomic centers breaks the classical adsorption scaling relations that restrict single-atom systems, defining the future trajectory of atomically dispersed catalyst design for complex multi-intermediate reactions.
  • 7
  • 18 Jun 2026
Topic Review
High-Throughput Screening vs. Deep Generative Inverse Design
The discovery of advanced materials is fundamentally transitioning from brute-force, database-dependent computational screening to targeted generative inverse design. High-Throughput Screening (HTS), powered by Density Functional Theory (DFT), provides a forward-mapping approach that remains constrained by the limits of known structural libraries. Conversely, deep generative models utilize artificial intelligence to navigate continuous chemical spaces via backward-mapping. This topic review explores the distinct mechanics of both paradigms, examining foundational chemical space representations alongside advanced deep learning architectures such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Diffusion models. Furthermore, it critically addresses the inherent computational bottlenecks of HTS and the ongoing challenge of material synthesizability in generative AI, charting the future trajectory of autonomous materials discovery.
  • 5
  • 18 Jun 2026
  • Page
  • of
  • 12
Academic Video Service

Quick Survey

Encyclopedia MDPI is conducting a targeted survey to identify the specific barriers hindering efficient research. We invite you to spend 3 minutes defining the priorities for our next generation of structured knowledge tools.
Take Survey