The generative-AI-dossier

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The Energy, Resources & Industrials Generative AI Dossier Expediting experiments and design (Materials Design) Generative AI empowers materials designers to explore a wider design space, optimize material properties, and expedite the discovery of new materials. Audio Code Issue/opportunity Developing new materials is challenging, costly, and time-consuming, and one reason is that the chemical space is vast and complex while the number of chemically feasible molecules is unknown. What is more, the materials discovery, development, and optimization process attracts different complexities at each stage, increasing the time required to reach a final design. How Generative AI can help Streamline experimental process Using Generative AI to determine the most efficient experimental procedures for probing or optimizing materials can streamline the experimental stages of development by removing redundant experiments and undertaking those that are cost and time optimized. High-entropy alloy (HEA) engineering Traditional techniques for developing HEAs with excellent physical, chemical, and mechanical properties are time-consuming and costly, making generative modelling a promising alternative development pathway. 01 02 03 04 05 06 3D/Specialized ACCELERATING INNOVATION Image Video Text 34
The Energy, Resources & Industrials Generative AI Dossier Expediting experiments and design Managing risk and promoting trust 01 02 Security Intellectual property or a competitive advantage could be compromised by using Generative AI in materials design, as models trained on proprietary or sensitive data could potentially reveal valuable insights or design strategies to competitors. Responsible Companies should be mindful to identify and mitigate unintended negative ramifications of materials designed with the support of Generative AI, such as long-term environmental impacts from materials that cannot be manufactured in responsible and sustainable ways. 03 04 05 06 Potential benefits Fueling innovation Generative AI applications have the capability to rapidly generate and prioritize a wide range of virtual materials with diverse compositions and structures. This virtual screening process allows researchers to identify potential candidates for specific applications or material properties much more quickly than traditional experimental methods. Bringing down costs Through efficiency savings and the rationalization and/or elimination of experiment consumables, the organization can reduce development costs. Enabling discovery Generative AI maximizes the likelihood of discovering materials with superior properties by leveraging its ability to efficiently explore and navigate a vast design space of potential materials. 35
Page 1 and 2: The Generative AI Dossier A selecti
Page 3 and 4: Introduction The advent of Generati
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Conclusion 01 Getting the most valu
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Endnotes 01 1. “Overview,” Urba
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