arXiv subjects

Jonathan R. Owens

Publications and source records attributed to Jonathan R. Owens.

3 recordsLinked to original sources

arXiv2026

The Future of Computing for Materials Science Challenges

Materials discovery increasingly relies on the coordinated use of theory, computation, experiment, data-driven methods, and emerging quantum technologies, yet the full potential of these tools is realised only when they operate within workflows that reflect the complexity of real systems. This perspective summarises current capabilities, limitations, and opportunities across these domains, drawing on contributions from academia, industry, and national laboratories to identify the scientific and structural requirements for more reliable and efficient discovery. Classical simulations provide broad coverage across design spaces, while experimental measurements reveal degradation, heterogeneity, and kinetic processes that determine performance under realistic conditions. Machine learning accelerates exploration when supported by well-curated datasets with clear provenance and uncertainty quantification, and quantum computing offers promising routes into correlated electronic behaviour when aligned with properties that influence engineering decisions. Collectively, these insights highlight the need for reproducible workflows, shared data standards, realistic benchmarks, and a research culture that prepares scientists to work across paradigms. By integrating these methodological and organisational elements, the community can move toward discovery processes that deliver robust predictions, support confident decision making, and shorten the path from conceptual design to deployable materials.

cond-mat.mtrl-sci↗

arXiv2025

Quantum simulation of CO$_2$ chemisorption in an amine-functionalized metal-organic framework

We perform a series of calculations using simulated QPUs, accelerated by the NVIDIA CUDA-Q platform, focusing on a molecular analog of an amine-functionalized metal-organic framework (MOF), a promising class of materials for CO$_2$ capture. The variational quantum eigensolver (VQE) technique is employed, utilizing both the unitary coupled-cluster method with singles and doubles (UCCSD) and adaptive ansätze within active spaces extracted from the larger material system. We explore active spaces of (6e,6o), (8e,8o), and (10e,10o), corresponding to 12, 16, and 20 qubits, respectively, and simulate them using CUDA-Q's GPU-accelerated state-vector simulator. Gate fusion is shown to decrease circuit evaluation time by 2-3$\times$, while parameter shift decreases the number of epochs required for variational convergence. The ADAPT-VQE method decreases both the number of epochs required for convergence and reduces the number of circuit parameters across all active spaces, at the cost of an increased number of circuit evaluations. Combining ADAPT-VQE with the 1- and 2-electron integrals from a CASSCF calculation recovers more correlation energy, at the cost of increased computational time. The CO$_2$ binding energy is computed, and we observe and discuss how increasing the active space size can lead to uneven recovery of correlation energy, making the predicted binding energies variable, even positive (\textit{i.e.}, energetically unfavorable) in some instances. This can be partially remedied by using an alternative approach to computing the binding energy that more evenly spreads the active space. This work explores the application of VQE to a novel material system using simulated QPUs and provides some insight into various consideration when performing these types of calculations, ultimately highlighting the challenges of studying chemisorption on near-term quantum machines.

physics.chem-ph↗

arXiv2025

A combined statistical mechanical and ab initio approach to understanding H2O/CO2 co-adsorption in mmen-Mg2(dobpdc)

We study the effects of H2O on CO2 adsorption in an amine-appended variant of the metal-organic framework Mg2(dobpdc), which is known to exhibit chaining behavior that presents in a step-shaped adsorption isotherm. We first show how the presence of different levels of local H2O affects this chaining behavior and the energetics of CO2 adsorption, based on a series of ab initio calculations, giving insight into the atomic-scale environment. In particular, we predict a novel adsorbed configuration, in which H2O and CO2 intertwine to make a braided chain down the MOF pore. We then show how an existing lattice model can be adapted to incorporate the effect of water, and predict the CO2 isotherms for the various water levels, observing a sharp shift the uptake at low partial pressures. The manifestation of this braided chain in the lattice model points to the potential emergence of a shift from cooperative capture to that of a phase transition. In addition to the physical insights, this work may serve as a launching off point for further work on this and related materials.

cond-mat.mtrl-sci↗