Metal-organic frameworks (MOFs) are porous materials that can be applied to modern technologies in energy storage, gas separation, carbon dioxide capture, catalysis, and many other areas. There are an ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

In the rapidly evolving landscape of modern manufacturing and engineering, a new technology is emerging as a crucial enabler-Data-Model Fusion (DMF). A recent review paper published in Engineering ...

Computational modeling and simulation of nanomaterials strongly complement physical experiments. They enable the prediction of characteristics and processes under conditions difficult to replicate or ...

NEW YORK--(BUSINESS WIRE)--Schrödinger, Inc. (Nasdaq: SDGR), whose physics-based computational platform is transforming the way therapeutics and materials are discovered, today announced that it is ...

The traditional approach to artificial intelligence development relies on discrete training cycles. Engineers feed models vast datasets, let them learn, then freeze the parameters and deploy the ...

Electro- and photocatalytic materials are central to enabling sustainable energy conversion processes such as water splitting, CO 2 reduction, oxygen reduction, and ammonia synthesis. These reactions ...

Train professional engineers in advanced methods of engineering analysis and modeling for exploration, simulation and optimization of mechanical engineering systems. Develop theoretical understanding ...

Faculty opportunities in Computational Modeling, Simulation, and Energy Sustainability. Conduct pioneering research in reservoir simulation, optimization, and decarbonization. Collaborate with ...

Over the past decade, structural biology has been profoundly transformed by advances in computational power, algorithmic ...