Related papers: Optimized tandem catalyst patterning for CO$_2$ re…
Machine learning is ideally suited for the pattern detection in large uniform datasets, but consistent experimental datasets on catalyst studies are often small. Here we demonstrate how a combination of machine learning and first-principles…
Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEAs) offer a vast compositional space for tuning such…
We discuss the problem of the optimal design of a micro-tubular fuel cell applying an inverse homogenization technique. Fuel cells are extremely clean and efficient electrochemical power generation devices, made up of a…
The use of highly active and robust catalysts is crucial for producing green hydrogen by water electrolysis as we strive to achieve global carbon neutrality. Noble metals like platinum are currently used in industry for the hydrogen…
Transformers have revolutionized AI in natural language processing and computer vision, but their large computation and memory demands pose major challenges for hardware acceleration. In practice, end-to-end throughput is often limited by…
Adsorption energy distributions (AEDs) have emerged as a powerful and increasingly adopted descriptor for catalytic performance in high-entropy alloys and, more recently, in conventional metallic alloy nanocrystal catalysts. By accounting…
Catalyst design is crucial for materials synthesis, especially for complex reaction networks. Strategies like collaborative catalytic systems and multifunctional catalysts are effective but face challenges at the nanoscale. Carbon nanotube…
Efficient and selective CO2 electroreduction into value-added chemicals and fuels emerged as a significant approach for CO2 conversion, however, it relies on catalysts with controllable product selectivity and reaction paths. In this work,…
As power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An…
High quality AI solutions require joint optimization of AI algorithms, such as deep neural networks (DNNs), and their hardware accelerators. To improve the overall solution quality as well as to boost the design productivity, efficient…
A model for impedance of a PEM fuel cell cathode catalyst layer under simultaneous application of potential and oxygen concentration perturbations is developed and solved. The resulting expression demonstrates dramatic lowering of the layer…
Efficient discovery of electrocatalysts for electrochemical energy conversion reactions is of utmost importance to combat climate change. With the example of the oxygen reduction reaction we show that by utilising a data-driven discovery…
Single-atom catalysts have attracted significant attention due to their exceptional atomic utilization and high efficiency in a range of catalytic reactions. However, these systems often face thermodynamic instability, leading to…
The development of quantum networks (QNs) relies on efficient mechanisms for distributing entanglement among multiple quantum users (QUs) under practical system constraints. This paper investigates the problem of entanglement rate…
Tunneling field-effect transistors (TFETs) based on 2D materials are promising steep sub-threshold swing (SS) devices due to their tight gate control. There are two major methods to create the tunnel junction in these 2D TFETs: electrical…
Oxygen transport membranes(OTMs)have provided great opportunities in the last decades but are suffering from the trade-off effect between stability and oxygen permeability. Here, we report a group of new planar dual-phase mixed…
Nanoporous Cu (NPC), synthesized by chemical dealloying of brass, holds significant potential for catalysis of electrochemical CO2 and CO reduction, owing to the optimal binding energy of Cu with *CO and *H intermediates, and the abundance…
The successful synthesis of high entropy alloy (HEA) nanoparticles, a long-sought goal in materials science, opens a new frontier in materials science with applications across catalysis, electronics, structural alloys, and energetic…
Effective water management is essential for the optimal performance of PEM fuel cells. We have developed an impedance model for liquid water transport through the membrane and coupled it with the two-phase model for cathode side impedance.…
We study the current dynamics of coupled atomic condensates flowing in two ring-shaped optical potentials. We provide a specific setup where the ring-ring coupling can be tuned in experimentally feasible way. It is demonstrated that the…