A5040056496- Machine Learning in Materials Science
- Spectroscopy and Quantum Chemical Studies
- COVID-19 and healthcare impacts
- COVID-19 Clinical Research Studies
- Orthopedic Surgery and Rehabilitation
- Geriatric Care and Nursing Homes
- Electrochemical Analysis and Applications
- SARS-CoV-2 and COVID-19 Research
- Advanced Physical and Chemical Molecular Interactions
- Long-Term Effects of COVID-19
- Surgical site infection prevention
- Scientific Computing and Data Management
- Ion-surface interactions and analysis
- Multiple and Secondary Primary Cancers
- Health, Nursing, Elderly Care
- Interprofessional Education and Collaboration
- Public Health in Brazil
- Chemical and Physical Properties in Aqueous Solutions
- Venous Thromboembolism Diagnosis and Management
- Electrostatics and Colloid Interactions
- Economic and Financial Impacts of Cancer
- Solid-state spectroscopy and crystallography
- Nanopore and Nanochannel Transport Studies
- Mass Spectrometry Techniques and Applications
- Diversity and Career in Medicine
Family Carers Ireland
2024
University of Cambridge
2024
Cancer Institute of New South Wales
2022
Queen Mary University of London
2020
University of Southampton
2020
Barts Health NHS Trust
2020
Royal London Hospital
2020
Southend Hospital
2020
St George's, University of London
2020
Imperial College London
2020
Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations ab initio quality on unprecedented time and length scales. However, they are currently limited by: (i) significant computational human effort that must go into development validation potentials for each particular system interest; (ii) a general lack transferability from one chemical to next. Here, using state-of-the-art MACE architecture we introduce single general-purpose ML model,...
The nature of ion–ion interactions in electrolytes confined to nanoscale pores has important implications for energy storage and separation technologies. However, the physical effects dictating structure nanoconfined remain debated. Here we employ machine-learning-based molecular dynamics simulations investigate with density functional theory level accuracy a prototypical electrolyte, aqueous NaCl within graphene slit pores. We find that free ion pairing highly deviates substantially from...
The extent of ion pairing in solution is an important phenomenon to rationalize transport and thermodynamic properties electrolytes. A fundamental measure this the potential mean force (PMF) between solvated ions. relative stabilities paired solvent shared states PMF barrier them are highly sensitive underlying energy surface. However, direct application accurate electronic structure methods challenging, since long simulations required. We develop wave function based machine learning...
Machine-learned atomistic simulations reveal that NaCl dissolves via a crumbling mechanism.
The nature of ion-ion interactions in electrolytes confined to nanoscale pores has important implications for energy storage and separations technologies. However, the physical effects dictating structure nanoconfined remain debated. Here we employ machine learning-based molecular dynamics simulations investigate with density functional theory-level accuracy a prototypical electrolyte, aqueous NaCl within graphene slit pores. We find that free ion pairing highly deviates substantially from...
Life on Earth depends upon the dissolution of ionic salts in water, particularly NaCl. However, an atomistic scale understanding process remains elusive. Simulations lend themselves conveniently to studying since they provide spatio-temporal resolution that can be difficult obtain experimentally. Nevertheless, complexity various inter- and intra-molecular interactions require careful treatment long time simulations, both which are typically hindered by computational expense. Here, we use...
The extent of ion pairing in solution is an important phenomenon to rationalise transport and thermodynamic properties electrolytes. A fundamental measure this the potential mean force (PMF) between solvated ions. relative stabilities paired solvent shared states PMF barrier them are highly sensitive underlying energy surface. However direct application accurate electronic structure methods challenging, since long simulations required. We develop wavefunction based machine learning...
e13518 Background: Anticancer drug dosing recommendations in kidney dysfunction are often empirical, based on non-standardised creatinine assays calculated via the Cockcroft-Gault equation, and lack applicability to globally accepted classifications. ADDIKD aims provide a standardised approach assessing function cancer patients, apply evidence consensus-based anticancer dysfunction. Methods: An expert international multidisciplinary working group was established develop recommendations. The...
Machine learning potentials have revolutionised the field of atomistic simulations in recent years and are becoming a mainstay toolbox computational scientists. This paper aims to provide an overview introduction into machine their practical application scientific problems. We systematic guide for developing potentials, reviewing chemical descriptors, regression models, data generation validation approaches. begin with emphasis on earlier such as high-dimensional neural network (HD-NNPs)...
Abstract Background Older adults and particularly older with frailty are high users of acute hospital care which results in overall higher costs reduced functional independence. Early supported discharge (ESD) was found to have a statistically significant impact reducing length stay admitted for medical reasons. This poster outlines the rehabilitation pathway developed by an ICPOP team provide early frail inpatients SMART rehab goals. Methods Suitable patients identified assessed prior from...
Abstract Background Detention orders are the inherent jurisdiction of high court. Only mechanism to support treatment in those lacking capacity and refusing care. Considered a last resort. Integrated care for older persons teams (ICPOP) often engage with complex cases who require this intervention. I aim review detention enacted on ICPOP patients within 1 year. Methods Retrospective notes all required order transfer from March 2023- 2024. Assessing patient’s primary diagnosis, expressed...