The A.I. revolution is here, and our expert team is ready to help get your R&D up to speed.
How do you tell if two chemicals are the same? Before the digital age, a chemist would examine a drawing of the structure or check the names and decide if they matched. But with databases of chemicals containing millions or billions of compounds, we need a computer to be able to match chemicals for us.Continue reading "Why Chemical Identifiers are the Unsung Heroes of Innovation"
Aionics is excited to announce today’s launch of its state-of-the-art Molecular Property Prediction Models on Google Cloud. These models, powered by graph neural networks (GNNs), represent a leap forward in materials research and development, and support generative AI-based molecular design processes for energy technologies. The models are completely general – able to process any arbitraryContinue reading "Why Chemical Identifiers are the Unsung Heroes of Innovation"
A rising tide lifts all boats. That’s what we believe at Aionics. When it comes to the study of materials informatics and cheminformatics, the more accessible and robust open source software tools, the better. Although our business relies on us building our own proprietary materials informatics and simulation software, we believe it is important forContinue reading "Why Chemical Identifiers are the Unsung Heroes of Innovation"
The suspense continues about a possibly world-changing discovery By Dr. Shreyas Honrao, Senior Materials Informatics Scientist, and Dr. Austin Sendek, Chief Executive Officer The scientific world has been abuzz for the last two weeks with news of a possible ground-breaking discovery: the world’s first room temperature, ambient pressure superconductor. Dubbed LK-99, this material was firstContinue reading "Why Chemical Identifiers are the Unsung Heroes of Innovation"
In the rapidly advancing field of artificial intelligence, the advent of large language models (LLMs) has brought about significant changes in various domains. One area that stands to benefit immensely from these developments is materials science. Materials scientists traditionally rely on structured data and quantitative structure-property relationship (QSPR) models to extract facts from unstructured data.Continue reading "Why Chemical Identifiers are the Unsung Heroes of Innovation"
