A5045361793- Advanced Chemical Physics Studies
- Machine Learning in Materials Science
- Catalytic Processes in Materials Science
- Spectroscopy and Quantum Chemical Studies
- Physics of Superconductivity and Magnetism
- Semiconductor materials and devices
- Superconductivity in MgB2 and Alloys
- Chemical Thermodynamics and Molecular Structure
- Electronic and Structural Properties of Oxides
- Ga2O3 and related materials
- Thermal and Kinetic Analysis
- thermodynamics and calorimetric analyses
- Nanocluster Synthesis and Applications
- X-ray Diffraction in Crystallography
- Surface Chemistry and Catalysis
- Theoretical and Computational Physics
- Electrochemical Analysis and Applications
- Radiative Heat Transfer Studies
- Advanced Mathematical Modeling in Engineering
- Inorganic Fluorides and Related Compounds
- Advanced Neuroimaging Techniques and Applications
- Ammonia Synthesis and Nitrogen Reduction
- Membrane Separation and Gas Transport
- Fluid Dynamics and Turbulent Flows
- Catalysts for Methane Reforming
University of Cambridge
2022-2025
Thomas Young Centre
2025
University College London
2025
London Centre for Nanotechnology
2025
University of Naples Federico II
2025
University of Oxford
2023
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...
The adsorption energy of a molecule onto the surface material underpins wide array applications, spanning heterogeneous catalysis, gas storage, and many more. It is key quantity where experimental measurements theoretical calculations meet, with agreement being necessary for reliable predictions chemical reaction rates mechanisms. prototypical molecule–surface system CO adsorbed on MgO, but despite intense scrutiny from theory experiment, there still no consensus its energy. In particular,...
The O vacancy (Ov) formation energy, EOv, is an important property of a metal-oxide, governing its performance in applications such as fuel cells or heterogeneous catalysis. These defects are routinely studied with density functional theory (DFT). However, it well-recognized that standard DFT formulations (e.g., the generalized gradient approximation) insufficient for modeling Ov, requiring higher levels theory. embedded cluster method offers promising approach to compute EOv accurately,...
<a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:msub><a:mi>CO</a:mi><a:mn>2</a:mn></a:msub></a:math> capture using carbon-based materials, particularly graphene and graphene-like is a promising strategy to deal with <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"><b:msub><b:mi>CO</b:mi><b:mn>2</b:mn></b:msub></b:math> emissions. However, significant gaps remain in our understanding of the molecular-level interaction between <c:math...
The accurate treatment of noncovalent interactions is necessary to model a wide range applications, from molecular crystals surface catalysts aqueous solutions and many more. Quantum diffusion Monte Carlo (DMC) coupled cluster theory with single, double, perturbative triple excitations [CCSD(T)] are considered two widely trusted methods for treating interactions. However, while they have been well-validated small molecules, recent work has indicated that these can disagree by more than 7.5...
Basis set incompleteness error (BSIE) is a common source of in quantum chemistry calculations, but it has not been comprehensively studied fixed-node Diffusion Monte Carlo (FN-DMC) calculations. FN-DMC, being projection method, often considered minimally affected by basis biases. Here, we show that this assumption always valid. While the relative introduced small total FN-DMC energy minor, can become significant binding (Eb) evaluations weakly interacting systems. We systematically...
Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely-trusted many-body method for solving the Schr\"{o}dinger equation, known its reliable predictions of material and molecular properties. Furthermore, excellent scalability with system complexity near-perfect utilization computational power makes FN-DMC ideally positioned to leverage new advances in computing address increasingly complex scientific problems. Even though widely used as gold standard, reproducibility across numerous...
Calculating sublimation enthalpies of molecular crystal polymorphs is relevant to a wide range technological applications. However, predicting these quantities at first-principles accuracy -- even with the aid machine learning potentials challenge that requires sub-kJ/mol in potential energy surface and finite-temperature sampling. We present an accurate data-efficient protocol based on fine-tuning foundational MACE-MP-0 model showcase its capabilities physical properties ice polymorphs. Our...
The structure of oxide-supported metal nanoclusters plays an essential role in their sharply enhanced catalytic activity over that bulk metals. Simulations provide the atomic-scale resolution needed to understand these systems. However, sensitive mix metal–metal and metal–support interactions, which govern structure, puts stringent requirements on method used, requiring calculations beyond standard density functional theory (DFT). choice is coupled cluster [specifically CCSD(T)], but its...
Structure factors obtained from diffraction experiments are one of the most important quantities for characterizing electronic and structural properties materials. Methods calculating this quantity plane-wave density functional theory (DFT) codes typically prohibitively expensive to perform, requiring electron be constructed evaluated on dense real-space grids. Making use projector functions found in both Vanderbilt ultrasoft pseudopotential augmented wave methods, we implement an approach...
We present an accurate and data-efficient protocol for fine-tuning the MACE-MP-0 foundational model a given system. Our achieves kJ/mol in predicting sublimation enthalpies below 1% error density of ice polymorphs.
The accurate treatment of non-covalent interactions is necessary to model a wide range applications, from molecular crystals surface catalysts aqueous solutions and many more. Quantum diffusion Monte Carlo (DMC) coupled cluster theory with single, double perturbative triple excitations [CCSD(T)] are considered two widely-trusted methods for treating interactions. However, while they have been well-validated small molecules, recent work has indicated that these can disagree by more than...
The adsorption energy of a molecule onto the surface material underpins wide array applications, spanning heterogeneous catalysis, gas storage and many more. It is key quantity where experimental measurements theoretical calculations meet, with agreement being necessary for reliable predictions reaction rates mechanisms. prototypical molecule-surface system CO adsorbed on MgO, but despite intense scrutiny from theory experiment, there still no consensus its energy. In particular, large cost...
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...
Recent work has suggested that nanoconfined water may exhibit superionic proton transport at lower temperatures and pressures than bulk water. Using first-principles-level simulations, we study the role of nuclear quantum effects in inducing this superionicity We show increase ionic conductivity hexatic water, leading to behaviour previously thought possible. Our suggests be accessible graphene nanocapillary experiments.
Basis set incompleteness error (BSIE) is a common source of in quantum chemistry (QC) calculations, but it has not been comprehensively studied fixed-node Diffusion Monte Carlo (FN-DMC) calculations. FN-DMC, being projection method, often considered minimally affected by basis biases. Here, we show that this assumption always valid. While the relative introduced small total FN-DMC energy minor, can become significant binding ($E_{\rm b}$) evaluations weakly interacting systems. We...
Quantum-mechanical simulations can offer atomic-level insights into chemical processes on surfaces. This understanding is crucial for the rational design of new solid catalysts as well materials to store energy and mitigate greenhouse gases. However, achieving accuracy needed reliable predictions has proven challenging. Density functional theory (DFT), workhorse quantum-mechanical method, often lead inconsistent predictions, necessitating accurate methods from correlated wave-function...
The adsorption energy of a molecule onto the surface material underpins wide array applications, spanning heterogeneous catalysis, gas storage and many more. It is key quantity where experimental measurements theoretical calculations meet, with agreement being necessary for reliable predictions reaction rates mechanisms. prototypical molecule-surface system CO adsorbed on MgO, but despite intense scrutiny from theory experiment, there still no consensus its energy. In particular, large cost...
Metal nanoclusters supported on oxide surfaces are widely-used catalysts that boasts sharply enhanced activity over their bulk, especially for the coinage metals: Au, Ag and Cu. These properties depend sensitively nanocluster structure, which challenging to model with density functional theory (DFT) -- workhorse modelling technique. Leveraging recently developed SKZCAM protocol, we perform first ever benchmark study of metal structures MgO surface coupled cluster [CCSD(T)] gold-standard We...
Structure factors obtained from diffraction experiments are one of the most important quantities for characterizing electronic and structural properties materials. Methods calculating this quantity plane-wave density functional theory (DFT) codes typically prohibitively expensive to perform, requiring electron be constructed evaluated on dense real-space grids. Making use projector functions found in both Vanderbilt ultrasoft pseudopotential augmented wave methods, we implement an approach...