Machine guided optimization of organic semiconductor films for light activated antimicrobial and antiviral surfaces

用于光激活抗菌和抗病毒表面的有机半导体薄膜的机器引导优化

• 批准号: 2606008
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2606008
• 关键词: Machine; guided; optimization; organic; semiconductor

Antimicrobial resistance (AMR) and the spread of infection is an area of grave concern globally and needs urgent attention. We are in the midst of COVID19 but how do we halt its progression and prepare for or even prevent the next pandemic? Infection mediated by contaminated surfaces is critical to the spread of disease. Our multidisciplinary team is developing an entirely novel application of plastic electronic materials to generate reactive oxygen species (ROS) and develop them into antimicrobial surfaces. We ask the following question: Do our lightactivated antimicrobial surfaces provide a feasible mechanism of infection control? In this project, we wish to use robotic synthetic chemistry and machine learning approaches to develop the next generation of LAMS (Lightactivated Antimicrobial Surfaces) to destroy microbes on surfaces and limit the spread of infection.We have exploited light-absorbing films based on solution processable organic/inorganic semiconductors typically used in solar energy research as a platform to develop novel antimicrobial coatings. When these coatings are exposed to ambient, visible light and oxygen, ROS, including superoxide, are generated which is subsequently able to destroy bacteria and viruses. Superoxide is one of the most aggressive, indiscriminately toxic species with the capacity to cause significant alterations in molecular and cellular function through multiple attack pathways and oxidative modifications of membranes, proteins and DNA. We aim to use the powerful combination of robotic aided synthetic chemistry, machine-guided learning and materials design to accelerate the development of these novel antimicrobial coatings on a timescale not possible using classical approaches to chemistry.Globally, institutions have rapidly reacted to ramp-up vaccine-based research in Manhattan-esque projects. In parallel to vaccine development, it is crucial we develop strategies to reduce the role of environmental contamination in the spread of infectious agents. Studies have so far shown that microbes and viruses, including SARS-CoV-2, can survive on various surfaces for up to a week. Our approach goes beyond just Covid-19 in that it is shows potential in tackling the growing threat of nosocomial infections caused by fungi, bacteria and viruses, such as candida, MRSA and C. difficile. The contamination of surfaces is significant to the spread of disease and research in this field can help be part of our arsenal to limit or even halt the progression of future pandemics and tackle the increasing existential threat of antimicrobial resistance.

抗菌素耐药性(AMR)和感染传播是全球严重关切的领域，需要紧急关注。我们正处于COVID19之中，但我们如何阻止它的发展，并为下一次大流行做好准备，甚至预防？受污染表面的感染是疾病传播的关键。我们的多学科团队正在开发一种全新的塑料电子材料应用，以产生活性氧物种(ROS)并将其开发成抗菌表面。我们问了以下问题：我们的光激活抗菌表面是否提供了一种可行的感染控制机制？在这个项目中，我们希望利用机器人合成化学和机器学习的方法来开发下一代LAMS(LightActiated Antim微生物Surface)，以杀灭表面上的微生物并限制感染的传播。我们利用基于太阳能研究中通常使用的可溶液处理的有机/无机半导体的光吸收薄膜作为平台来开发新型抗菌涂层。当这些涂层暴露在环境、可见光和氧气中时，会产生ROS，包括超氧化物，从而能够杀灭细菌和病毒。超氧化物是一种最具侵略性的、不分青红皂白的有毒物种，它能够通过多种攻击途径以及对膜、蛋白质和DNA的氧化修饰，导致分子和细胞功能的显著变化。我们的目标是利用机器人辅助合成化学、机器引导学习和材料设计的强大组合，在时间尺度上加快这些新型抗菌涂层的开发，这是使用经典化学方法所不可能的。在全球范围内，机构对曼哈顿式项目中基于疫苗的研究做出了迅速反应。在疫苗开发的同时，我们制定战略，减少环境污染在传染病传播中的作用，这一点至关重要。到目前为止，研究表明，包括SARS-CoV-2在内的微生物和病毒可以在各种表面上存活长达一周。我们的方法超越了新冠肺炎，因为它在应对由真菌、细菌和病毒(如念珠菌、耐甲氧西林金黄色葡萄球菌和艰难梭菌)引起的医院感染的日益增长的威胁方面显示出潜力。表面的污染对疾病的传播具有重要意义，这一领域的研究可以帮助我们限制甚至阻止未来大流行的发展，并应对日益增长的抗菌素耐药性生存威胁。