MolGX, a part of IBM's overarching strategy that aims to accelerate the discovery of new materials by 10 to 100 times, uncovers materials from the property targets of a given product. By observing and selecting a dataset, MolGX leverages generative models to produce molecules from chemical properties like "solubility in water" and "heatability." The platform trains an AI model to predict chemical characteristics within given parameters and synthesizes molecular structures based on the model built. Breakthroughs in the discovery of new materials span from pure chance, to trial-and-error approaches, to design by analogy to existing systems," Seiji Takeda, technical lead of material discovery at IBM, wrote in a blog post. IBM has released a free trial version of MolGX trained using a built-in dataset, which the company applied internally to the development of a new photoacid generator -- a key material in electronics manufacturing.

IBM today announced the launch of the Molecule Generation Experience (MolGX), a cloud-based, AI-driven molecular design platform that automatically invents new molecular structures. MolGX, a part of IBM's overarching strategy that aims to accelerate the discovery of new materials by 10 to 100 times, uncovers materials from the property targets of a given product. The chemical sciences have made strides in the discovery of novel and useful materials over the past decades. For example, in the area of polymers, the recent development of thermoplastics has had an influence on applications ranging from new paints to clothing fibers. But while the discovery of new materials is the driving force in the expansion and improvement of industrial products, the vastness of chemical space likely exceeds the ability of human experts to explore even a fraction of it.