separates materials properties from the latent space by conditioning to make inverse materials design more efficient and transparent. It combines labeled and unlabeled data for improved efficiency ...

Inverse design, which the group's work addresses, quite literally attempts the problem in reverse. "Human researchers do what they're good at: envisioning novel and useful particle architectures.

A research team including members from the University of Michigan have unveiled a new observational technique that's ...

Over the past decade, generative deep learning models have been applied successfully to the design of novel drug molecules, ... Materials Science; December 13, 2023 dialog. ...

Inverse design is a fast-growing technique for developing new materials and devices that are specialized for highly specific uses. Starting from a desired functionality, inverse-design algorithms work ...

Predicting the emergent properties of a material from a microscopic description is a scientific challenge. Machine learning and reverse-engineering have opened new paradigms in the understanding and ...

The hot-end components of high-performance high-speed aircraft need to meet performance requirements such as long service life, wide temperature range oxidation resistance and ablation resistance.

A new publication from Opto-Electronic Advances, 10.29026/oea.2023.220018 discusses inverse design and realization of an optical cavity-based displacement transducer with arbitrary responses.

Machine learning and reverse-engineering have opened new paradigms in the understanding and design of materials. However, this approach for the design of soft materials is highly non ... Inverse ...