Layered materials as a platform for quantum technologies
Layered materials are taking centre stage in the ever-increasing research effort to develop
material platforms for quantum technologies. We are at the dawn of the era of layered …
material platforms for quantum technologies. We are at the dawn of the era of layered …
[HTML][HTML] MA2Z4 family heterostructures: Promises and prospects
Recent experimental synthesis of ambient-stable MoSi 2 N 4 monolayer has garnered
enormous research interest. The intercalation morphology of MoSi 2 N 4—composed of a …
enormous research interest. The intercalation morphology of MoSi 2 N 4—composed of a …
Two-dimensional semiconductors with high intrinsic carrier mobility at room temperature
Two-dimensional semiconductors have demonstrated great potential for next-generation
electronics and optoelectronics, however, the current 2D semiconductors suffer from …
electronics and optoelectronics, however, the current 2D semiconductors suffer from …
Predicting lattice thermal conductivity via machine learning: a mini review
Y Luo, M Li, H Yuan, H Liu, Y Fang - NPJ Computational Materials, 2023 - nature.com
Over the past few decades, molecular dynamics simulations and first-principles calculations
have become two major approaches to predict the lattice thermal conductivity (κ L), which …
have become two major approaches to predict the lattice thermal conductivity (κ L), which …
From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning
X Chen, S Lu, Q Chen, Q Zhou, J Wang - nature communications, 2024 - nature.com
Data scarcity is one of the critical bottlenecks to utilizing machine learning in material
discovery. Transfer learning can use existing big data to assist property prediction on small …
discovery. Transfer learning can use existing big data to assist property prediction on small …
Toward sustainable ultrawide bandgap van der Waals materials: An ab initio screening effort
The sustainable development of next‐generation device technology is paramount in the face
of climate change and the looming energy crisis. Tremendous effort is made in the discovery …
of climate change and the looming energy crisis. Tremendous effort is made in the discovery …
Data-driven discovery of 2D materials by deep generative models
Efficient algorithms to generate candidate crystal structures with good stability properties can
play a key role in data-driven materials discovery. Here, we show that a crystal diffusion …
play a key role in data-driven materials discovery. Here, we show that a crystal diffusion …
MatGPT: A vane of materials informatics from past, present, to future
Combining materials science, artificial intelligence (AI), physical chemistry, and other
disciplines, materials informatics is continuously accelerating the vigorous development of …
disciplines, materials informatics is continuously accelerating the vigorous development of …
Generalized principles for the descriptor-based design of supported gold catalysts
We postulate generalized principles for determining catalytic descriptors like the adsorption
energy of CO*, across interfacial active sites of gold catalysts having varying coordination …
energy of CO*, across interfacial active sites of gold catalysts having varying coordination …
Machine learning study of the magnetic ordering in 2D materials
Magnetic materials have been applied in a large variety of technologies, from data storage
to quantum devices. The development of two-dimensional (2D) materials has opened new …
to quantum devices. The development of two-dimensional (2D) materials has opened new …