Webinar Q&A: Accelerating Product Reformulation with Machine Learning

Category: Materials Science, Transformation

In our recent C&EN Webinar: Accelerating Consumer Products Reformulation with Machine Learning, we demonstrated how to leverage digital tools and technology to bring new products to market faster. The webinar was well attended by scientists, engineers, and business leaders across the product development spectrum eager to learn how these concepts can be applied to their …
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Machine Learning in Materials Science

Category: Materials Science, Technology, Transformation

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 judgement. And …
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Enthought Announces Formation of Digital Transformation, Materials Science Advisory Boards

Category: Materials Science, News

Austin, TX – June 15, 2021 – Enthought, the leading provider of technologies and services that deliver digital innovation to science-driven companies, is experiencing rapid growth as companies look to accelerate their adoption of new technologies, such as artificial intelligence and machine learning, in response to COVID-19. In support of Enthought’s growth, strategic vision and …
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Up the ‘Digital Level’ of Your R+D Lab

Category: Materials Science, Transformation

Image: 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 …
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Enthought at the 2020 Materials Research Society Conference

Category: Materials Science, Technology

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., Applications Engineer 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 research and …
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