Materials Science
For many traditional innovation-driven organizations, scientific data is generated to answer specific immediate research questions and then archived to protect IP, with little attention paid to the future value of reusing the data to answer other similar or tangential questions.
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In the digital era, robust data tools are crucial for all companies and the science-driven industries like the life sciences, materials science, and chemistry are no exception.
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As a company that delivers Digital Transformation for Science, part of our job at Enthought is to understand the trends that will affect how our clients do their science. Below are three trends that caught our attention in 2022 that we predict will take center stage in 2023. ChatGPT This one just showed up on…
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Introduction If you have used TensorFlow before, you know how easy it is to create a simple neural network model using the Keras API. Just create an instance of the Sequential model class, add the number of desired layers and accompanying layer nodes, define the activation functions to be used by each layer, and compile…
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“Digital transformation”, “machine learning”, and “artificial intelligence” are buzzwords heard in every industry, from the boardroom to the lab. We asked Dr. Michael Heiber, lead of Enthought’s Materials Informatics solutions, about what these technology trends mean for the future of materials and chemical labs and product development. Q: What are some of the top challenges…
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SEMICON West 2021 lived up to its status as the signature conference for the extended microelectronics supply chain. Business and technology leaders, researchers, and analysts from across the semiconductor industry connected in-person and virtually for a 360 view of technological and market trends. Enthought Takeaways Authors: Michael Heiber, Application Engineer, Materials Science Solutions Group; Tim…
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At this year’s SEMI Strategic Materials Conference, leaders in the semiconductor industry across the supply chain came together to discuss the big challenges and opportunities that are likely to emerge over the next 5 years. Our Takeaways Authors: Michael Heiber, Application Engineer, Materials Science Solutions Group, Tim Diller, Director of Digital Transformation Services, Materials Science…
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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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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…
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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…
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