Artificial Intelligence and Machine Learning to Crack Crystal Growth

人工智能和机器学习破解晶体生长难题

• 批准号: 10039771
• 金额: $ 1.27万
• 依托单位: CRYSTALGROWER LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10039771
• 关键词: Artificial; Intelligence; Machine; Learning; Crack

**Crystal**_Grower_ Ltd is a scientific software company, spun out from The University of Manchester, that produces software to model how crystals grow. Everyone is aware of crystals in nature, diamonds, salt, snowflakes but also the shells of molluscs and even the focussing components in shark eyes. What people may be less aware of is that crystals are the active components of almost every functional material that we use in our everyday life: pharmaceuticals, such as aspirin and paracetamol; the electronic elements inside your computer; the materials used for storing hydrogen for a hydrogen economy or removing carbon dioxide from the atmosphere for an improved environment. All these crystals are produced by growing them in the laboratory and represent a multi-billion pound global and UK manufacturing market. However, in order to control precisely the functionality of these crystals it is critical first to control their growth at the nano/molecular scale. This ensures that the crystals are produced with the required quality and functional properties. The software produced by **Crystal**_Grower_ Ltd helps companies do exactly that by simulating how crystals grow and how this growth changes upon altering laboratory conditions thereby leading to better production outcomes.Much of this simulation relies on comparison of simulated crystals with those produced experimentally which, at present, must be done with significant human intervention. The purpose of this current project is to develop image-based classifiers that would enable our clients to process substantial volumes of data in a more intelligent, automated way. It would take significantly less time to process simulations, reduce human error, particularly at scale, and ultimately enable more rapid insights. This would allow our clients to spend more time focused on developing their products, instead of data analytics. Image classification technology can also enable the future development of advanced simulation steering techniques, reducing the time to solution, whilst consuming fewer computational resources.

** Crystal ** _ Grolower_ Ltd是一家科学软件公司，是从曼彻斯特大学开发的，可生产软件，以建模晶体的增长方式。每个人都知道自然界中的晶体，钻石，盐，雪花，以及软体动物的贝壳，甚至是鲨鱼眼中的集中成分。人们可能不太了解的是，晶体几乎是我们在日常生活中使用的几乎每种功能材料的积极组成部分：药品，例如阿司匹林和扑热息痛；计算机内的电子元素；用于将氢存储用于氢经济的材料或从大气中除去二氧化碳以改善环境。所有这些晶体都是通过在实验室中种植的，代表了数十亿英镑的全球和英国制造市场。但是，为了准确控制这些晶体的功能，首先控制其在纳米/分子尺度上的生长至关重要。这样可以确保晶体具有所需的质量和功能性能。 ** Crystal ** _ Grower_ LTD生产的软件通过模拟晶体的生长方式以及在改变实验室条件后如何变化，从而帮助公司做到这一点，从而导致了更好的生产成果。该模拟的依赖于模拟晶体与实验性的模拟晶体进行比较，目前必须与大量的人类干预进行实验。当前项目的目的是开发基于图像的分类器，以使我们的客户能够以更聪明，自动化的方式处理大量数据。处理模拟，减少人为错误，尤其是在大规模上，并最终使更快的见解将花费大量时间。这将使我们的客户花更多的时间专注于开发其产品，而不是数据分析。图像分类技术还可以使未来的高级模拟转向技术的开发，减少解决方案的时间，同时消耗较少的计算资源。