Bayesian optimisation is a statistical method that efficiently models and optimises expensive
“black-box” functions. This review considers the application of Bayesian optimisation to …

One of the main challenges in materials discovery is efficiently exploring the vast search
space for targeted properties as approaches that rely on trial-and-error are impractical. We …

Abstract Design of Experiments (DOE) is statistical tool deployed in various types of system,
process and product design, development and optimization. It is multipurpose tool that can …

Statistical models can be used as surrogates of detailed simulation models. Their key
advantage is that they are evaluated at low computational cost which can remove …

The ability to accurately model and simulate chemical processes has been paramount to the
growing success and efficiency in process design and operation. These improvements …

Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …

High-fidelity computer-aided experimentation is becoming more accessible with the
development of computing power and artificial intelligence tools. The advancement of …

The ability to integrate resources and share knowledge across organisations empowers
scientists to expedite the scientific discovery process. This is especially crucial in addressing …

In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …

We perform an ensemble of N-body simulations with 2048 3 particles for 101 flat wCDM
cosmological models sampled based on a maximin distance sliced Latin hypercube design …