Materials Science

Machine Learning in Materials Science

Aug 10, 2021

The process of materials discovery is complex and iterative, requiring a level of expertise to be done effectively. Materials workflows that require human judgement present a specific challenge to the discovery process, which can be leveraged as an opportunity to introduce digital technologies.  In the lab, many tasks require manual data collection and judgment. And…

Read More

Digital-centric R&D Laboratories

Feb 16, 2021

To have a transformative impact, labs must reinvent workflows through digital technologies and skills, adopting a strong data culture. Innovation through digital-centric systems confidently produces new materials that meet customer specifications orders of magnitude faster than before, enabling broader business transformation.  Authors: Chris Farrow, Ph.D., VP Materials Science Solutions and Michael Heiber, Manager, Materials Informatics…

Read More

Up the ‘Digital Level’ of Your R+D Lab

Dec 8, 2020

A key role of materials and chemistry R&D researchers is to invert the primary function of their labs – that of creating materials from chemical structures, formulations and processes – to one of determining the inputs that will produce materials with the desired properties with minimal iteration. This process can be significantly accelerated by ‘leveling…

Read More

Enthought at the 2020 Materials Research Society Conference

Nov 24, 2020

Machine learning classification model learns complex printability window for inkjet printed polymer films using data from automated formulation and printing system. Authors: Michael Heiber, Ph.D., Manager, Materials Informatics and Frank Longford, Ph.D., Scientific Software Developer The Materials Research Society (MRS) is a global community of materials researchers, built to promote the advancement of interdisciplinary materials…

Read More