ORCID Profile
0000-0001-9105-2858
Current Organisation
University of Oxford
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Publisher: Springer Science and Business Media LLC
Date: 30-09-2021
Publisher: Frontiers Media SA
Date: 10-05-2017
Publisher: Elsevier BV
Date: 06-2021
Publisher: Frontiers Media SA
Date: 12-07-2022
Abstract: Materials on plant leaf surfaces that attract water impact penetration of foliar-applied agrochemicals, foliar water uptake, gas exchange, and stomatal density. Few studies are available on the nature of these substances, and we quantify the hygroscopicity of these materials. Water vapor sorption experiments on twelve leaf washes of s le leaves were conducted and analyzed with inductively coupled plasma-optical emission spectroscopy (ICP-OES) and X-ray diffraction. All leaf surface materials studied were hygroscopic. Oils were found on the surface of the Eucalyptus studied. For mangroves that excrete salt to the leaf surfaces, significant sorption occurred at high humidity of a total of 316 mg (~0.3 ml) over 6–10 leaves and fitted a Guggenheim, Anderson, and de Böer sorption isotherm. Materials on the plant leaf surface can deliquesce and form an aqueous solution in a variety of environments where plants grow, including glasshouses and by the ocean, which is an important factor when considering plant-atmosphere relations.
Publisher: MDPI AG
Date: 02-07-2019
Abstract: The global agricultural industry requires improved efficacy of sprays being applied to weeds and crops to increase financial returns and reduce environmental impact. Enhancing foliar penetration is one way to improve efficacy. Within the plant leaf, the cuticle is the most significant barrier to agrochemical diffusion. It has been noted that a comprehensive set of mechanisms for ionic active ingredient (AI) penetration through plant leaves with surfactants is not well defined, and oils that enhance penetration have been given little attention. The importance of a mechanistic mathematical model has been noted previously in the literature. Two mechanistic mathematical models have been previously developed by the authors, focusing on plant cuticle penetration of calcium chloride through tomato fruit cuticles. The models included ion binding and evaporation with hygroscopic water absorption, along with the ability to vary the AI concentration and type, relative humidity, and plant species. Here, we further develop these models to include lipophilic adjuvant effects, as well as the adsorption and desorption, of compounds on the cuticle surface with a novel Adaptive Competitive Langmuir model. These modifications to a penetration model provide a novel addition to the literature. We validate our theoretical model results against appropriate experimental data, discuss key sensitivities, and relate theoretical predictions to physical mechanisms. The results indicate the addition of the desorption mechanism may be one way to predict increased penetration at late times, and the sensitivity of model parameters compares well to those present in the literature.
Publisher: Springer Science and Business Media LLC
Date: 19-08-2021
DOI: 10.1038/S41467-021-25225-Y
Abstract: Food production must increase significantly to sustain a growing global population. Reducing plant water loss may help achieve this goal and is especially relevant in a time of climate change. The plant cuticle defends leaves against drought, and so understanding water movement through the cuticle could help future proof our crops and better understand native ecology. Here, via mathematical modelling, we identify mechanistic properties of water movement in cuticles. We model water sorption in astomatous isolated cuticles, utilising three separate pathways of cellulose, aqueous pores and lipophilic. The model compares well to data both over time and humidity gradients. Sensitivity analysis shows that the grouping of parameters influencing plant species variations has the largest effect on sorption, those influencing cellulose are very influential, and aqueous pores less so but still relevant. Cellulose plays a significant role in diffusion and adsorption in the cuticle and the cuticle surfaces.
Publisher: Cold Spring Harbor Laboratory
Date: 22-11-2021
DOI: 10.1101/2021.11.22.469518
Abstract: Materials on plant leaf surfaces that attract water impact penetration of foliar-applied agrochemicals, foliar water uptake, gas exchange and stomatal density. Few studies are available on the nature of these substances, and we quantify the hygroscopicity of these materials. Water vapor sorption experiments on twelve leaf washes of s le leaves were conducted and analyzed with inductively coupled plasma-optical emission spectroscopy and X-ray diffraction. All leaf surface materials studied were hygroscopic. Oils were found on the surface of the Eucalyptus studied. For mangroves that excrete salt to the leaf surfaces, significant sorption occurred at high humidity of a total of 316 mg (∼ 0.3 mL) over 6–10 leaves, and fitted a Guggenheim, Anderson, and de Böer sorption isotherm. Materials on the plant leaf surface can deliquesce and form an aqueous solution in a variety of environments where plants grow, including glasshouses and by the ocean, which is an important factor when considering plant-atmosphere relations.
Publisher: Research Square Platform LLC
Date: 06-06-2023
DOI: 10.21203/RS.3.RS-2959700/V1
Abstract: One of the main issues affecting the uptake of battery packs are safety concerns, particularly with respect to the fires caused by cell faults. Managing the risks from faults requires advances in battery management systems and an understanding of the dynamics of large packs. To address this issue, a machine learning classifier based upon a support vector machine was developed to detect cell faults within large packs using a limited number of current sensors. To train the classifier, a modelling framework for parallel connected packs was introduced and shown to generalise to Doyle-Fuller-Newman electrochemical models. The fault classification performance was found to be satisfactory, with an accuracy of 83% using current information from only 27% of the cells. These results highlight the potential of combining mathematical modelling and machine learning to improve battery management systems and deal with the complexities of large packs.
Publisher: Queensland University of Technology
Date: 2019
Publisher: IOP Publishing
Date: 10-2022
Abstract: Growth in the Li-ion battery market continues to accelerate, driven primarily by the increasing need for economic energy storage for electric vehicles. Electrode manufacture by slurry casting is the first main step in cell production but much of the manufacturing optimisation is based on trial and error, know-how and in idual expertise. Advancing manufacturing science that underpins Li-ion battery electrode production is critical to adding to the electrode manufacturing value chain. Overcoming the current barriers in electrode manufacturing requires advances in materials, manufacturing technology, in-line process metrology and data analytics, and can enable improvements in cell performance, quality, safety and process sustainability. In this roadmap we explore the research opportunities to improve each stage of the electrode manufacturing process, from materials synthesis through to electrode calendering. We highlight the role of new process technology, such as dry processing, and advanced electrode design supported through electrode level, physics-based modelling. Progress in data driven models of electrode manufacturing processes is also considered. We conclude there is a growing need for innovations in process metrology to aid fundamental understanding and to enable feedback control, an opportunity for electrode design to reduce trial and error, and an urgent imperative to improve the sustainability of manufacture.
Publisher: Frontiers Media SA
Date: 20-12-2018
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Eloise Tredenick.