Development of Understanding and Preparation for Machine learning for Accelerated Carbonation Technology Pelletisation Process - Carbon8

加速碳酸化技术造粒过程的机器学习的理解和准备的发展 - Carbon8

• 批准号: 10091589
• 金额: $ 3.02万
• 依托单位: CARBON8 SYSTEMS LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10091589
• 关键词: Development; Understanding; Preparation; Machine; learning

Carbon8 is a research based start-up that is already a global leader in carbon capture, utilisation and storage (CCUS). Through our Accelerated Carbonation Technology (ACT), we help industry decarbonise while transitioning to a more circular operation. We capture CO2 directly from the source to treat industrial residues and manufacture new materials. The captured carbon is locked into innovative, low-carbon products like lightweight aggregates.The deployment of our product, the CO2ntainer is the realisation of our technology as a compact, mobile CCUS solution. It allows for easy implementation, avoiding disruptions in production and is a solution that can help hard-to-abate sectors today. This project focuses on the variation in the output, using modelling, statistical analysis leading towards machine learning to optimise the output.Our process is both innovative and complex and over the course of operations a significant amount of laboratory and process data has been captured. The intent of this project is to partner with Advanced Sustainable Manufacturing Technologies (ASTUTE). This will bring their skills in advanced statistical analysis and preparation for machine learning to the challenge. The output will be an innovative step forward in the efficiency of the process which can be programmed into the control system of the product.

Carbon8 是一家以研究为基础的初创企业，已成为碳捕获、利用和封存 (CCUS) 领域的全球领导者。通过我们的加速碳酸化技术 (ACT)，我们帮助行业脱碳，同时过渡到更加循环的运营。我们直接从源头捕获二氧化碳来处理工业残留物并制造新材料。捕获的碳被锁定在创新的低碳产品中，例如轻质骨料。我们的产品 CO2ntainer 的部署是我们技术作为紧凑型移动 CCUS 解决方案的实现。它易于实施，避免生产中断，是一种可以帮助当今难以减排的行业的解决方案。该项目重点关注输出的变化，使用建模、统计分析和机器学习来优化输出。我们的流程既创新又复杂，在操作过程中捕获了大量的实验室和过程数据。该项目的目的是与先进可持续制造技术 (ASTUTE) 合作。这将使他们在高级统计分析和机器学习准备方面的技能应对挑战。其输出将是流程效率的创新一步，可以编程到产品的控制系统中。