ANTENNA - Advanced tools for predictive cleaning in a world of resource scarcity

ANTENNA - 在资源匮乏的世界中进行预测性清洁的先进工具

• 批准号: EP/V056891/1
• 负责人: Mark Wilson
• 金额: $ 278.92万
• 依托单位: Durham University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 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=EP%2FV056891%2F1
• 关键词: ANTENNA; Advanced; tools; predictive; cleaning

The ANTENNA programme aims to deliver new analysis and modelling tools to provide a step-change in formulation chemistry. These new tools will provide a transformation in the mechanisms, predictive models and experimental methods that will translate consumer cleaning tasks into tomorrow's formulations. Thereby providing a means of meeting the sustainability challenges of reduced water use, reduced energy use, fewer microfibres and the use of more sustainable chemistries.The Consumer Goods Cleaning Sector is facing four key sustainability challenges:1) Water: In many parts of the world water is becoming a scarce resource. Globally sustainable levels of water consumption (50 L/person/day, or ~1/3 of current UK usage) require a redesign of everyday cleaning tasks.2) Energy & Emissions: 80% of a washing machine's energy consumption arises from heating the water. The use phase of cleaning products, especially those that use hot water, provides an excellent opportunity to reduce domestic indirect Greenhouse Gas Emissions in homes.3) Garment lifespan: recent research shows that quick and cool wash cycles are key to reducing the number of microfibers released into the environment. Sensitive cleaning can extend garment lifespan and reduce clothes waste to landfill.4) Sustainable & efficient chemistry: reducing the environmental footprint of cleaning chemistries where today conventional materials are used in excess to compensate for water hardness, slow kinetics and non-selective modes of action. These sustainability challenges (relevant for the UK and beyond) are set to disrupt the industry and will require transformative solutions to redesign consumer cleaning tasks, based on a mechanistic understanding of the underpinning science and engineering. They cannot be developed incrementally from current products, even when augmented with High Throughput Experimentation & Machine Learning. These challenges require new formulations for cleaning products. However, to design these formulations is a formidable task. i) Unfavourable interactions between formulation components is a major problem in the development of new products (e.g., incompatibilities between bleach, enzymes and complex surfactant-polymer interactions). ii) The ability to deposit surface protection agents (e.g., soil release, anti-microbial) is often required in a wash environment that is usually optimised for cleaning and complete removal of soils from substrates. iii) The kinetics of favourable/unfavourable transformations must be understood to introduce novel sequenced chemistry solutions with minimum environmental footprint. The overall vision of this proposal is, therefore, to provide new "game-changing" experimental and theoretical tools to improve on the current formulation development process and tackle the sustainability challenges identified above. These tools will accelerate testing of cleaning actives, allow the effects of the chemistry to be quantified and separated from flow and mechanical agitation; and will vastly improve the speed of formulation development and screening.

天线计划旨在提供新的分析和建模工具，以提供配方化学方面的逐步变化。这些新工具将在机制，预测模型和实验方法中提供一个转换，这些方法将使消费者清洁任务转化为明天的表述。从而提供了一种应对减少用水量，减少能源使用，减少微侵权和使用更可持续的化学作用的可持续性挑战的方法。消费品清洁行业面临着四个关键的可持续性挑战：1）水：世界上许多地区的水都变得稀缺。全球可持续水平的用水量（50 l/persion/day或当前英国使用的〜1/3）需要重新设计日常清洁任务。2）能源和排放：洗衣机的80％的能源消耗来自加热水。清洁产品的使用阶段，尤其是那些使用热水的产品，为减少家庭中家庭间接温室气体排放提供了绝佳的机会。3）服装寿命：最近的研究表明，快速，凉爽的洗涤周期是减少释放到环境中的微纤维数量的关键。敏感的清洁可以延长服装的寿命并将衣服浪费减少到垃圾填埋场。4）可持续且有效的化学：减少清洁化学的环境足迹，如今，如今已过多地使用常规材料来补偿水硬度，缓慢的动力学和非选择性的行动方式。这些可持续性挑战（与英国及以后有关）将破坏该行业，并基于对基础科学和工程的机械理解，需要进行变革性的解决方案来重新设计消费者清洁任务。即使通过高通量实验和机器学习增强，它们也无法从当前产品逐渐开发。这些挑战需要清洁产品的新配方。但是，设计这些配方是一项艰巨的任务。 i）配方组件之间的不利相互作用是新产品开发的主要问题（例如，漂白剂，酶和复杂的表面活性剂 - 聚合物相互作用之间的不兼容）。 ii）在洗涤环境中通常需要将表面保护剂（例如，土壤释放，抗微生物）沉积的能力通常需要优化，以清洁和完全清除底物中的土壤。 iii）必须理解有利/不利转化的动力学，以引入具有最小环境足迹的新型测序化学解决方案。因此，该提案的总体愿景是提供新的“改变游戏规则的”实验和理论工具，以改善当前配方开发过程，并应对上述可持续性挑战。这些工具将加速清洁活性的测试，使化学的影响可以量化并与流动和机械搅动分开；并将大大提高配方开发和筛选的速度。

项目成果

Tunable Structural Color with Gradient and Multiaxial Polydimethylsiloxane Wrinkling

• DOI: 10.1002/adom.202200964
• 发表时间: 2022-06
• 期刊: Advanced Optical Materials
• 影响因子: 9
• 作者: Annabelle Tan;L. Pellegrino;Zain Ahmad;J. Cabral

Microfluidic in-line dynamic light scattering with a commercial fibre optic system

使用商用光纤系统进行微流体在线动态光散射

• DOI: 10.1039/d3lc00062a
• 发表时间: 2023
• 期刊: Lab on a Chip
• 影响因子: 6.1
• 作者: Torquato L

Light Responsiveness and Assembly of Arylazopyrazole-Based Surfactants in Neat and Mixed CTAB Micelles.

• DOI: 10.1021/jacsau.2c00453
• 发表时间: 2022-12-26
• 期刊: JACS AU
• 影响因子: 8
• 作者: Tyagi, Gunjan;Greenfield, Jake L;Jones, Beatrice E;Sharratt, William N;Khan, Kasim;Seddon, Dale;Malone, Lorna A;Cowieson, Nathan;Evans, Rachel C;Fuchter, Matthew J;Cabral, Joao T
• 通讯作者: Cabral, Joao T

A many-body dissipative particle dynamics parametrisation scheme to study behaviour at air-water interfaces.

• DOI: 10.1039/d3sm00276d
• 发表时间: 2023-05
• 期刊: Soft matter
• 影响因子: 3.4
• 作者: Rachel L Hendrikse;C. Amador;M. Wilson

Composition and temperature effects on the solution structure of SDS/octanol/brine by SANS, NMR and microscopy.

通过 SANS、NMR 和显微镜观察组成和温度对 SDS/辛醇/盐水溶液结构的影响。

• DOI: 10.1039/d3sm01098h
• 发表时间: 2023
• 期刊: Soft matter
• 影响因子: 3.4
• 作者: Donina L