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Motivated by the current demand of clinical governance, surgical simulation is now a well-established modality for basic skills training and assessment. The practical deployment of the technique is a multi-disciplinary venture encompassing…

Simulation studies are computer experiments that involve creating data by pseudorandom sampling. The key strength of simulation studies is the ability to understand the behaviour of statistical methods because some 'truth' (usually some…

We describe a framework for interactive molecular dynamics in a multiuser virtual reality environment, combining rigorous cloud-mounted physical atomistic simulation with commodity virtual reality hardware, which we have made accessible to…

The transmission electron microscope (TEM) has become an essential tool for innovation in nanoscience, material science, and biology. Despite these instruments being widely used across both industry and academia, academics may hesitate to…

This article reports prototype web apps that use commodity, open-source technologies for augmented and virtual reality to provide immersive, interactive human-computer interfaces for chemistry, structural biology and related disciplines.…

Discovery of the molecular candidates for applications in drug targets, biomolecular systems, catalysts, photovoltaics, organic electronics, and batteries, necessitates development of machine learning algorithms capable of rapid exploration…

Scientific computing applications have benefited greatly from high performance computing infrastructure such as supercomputers. However, we are seeing a paradigm shift in the computational structure, design, and requirements of these…

Computation, the use of a computer to solve, simulate, or visualize a physical problem, has revolutionized how physics research is done. Computation is used widely to model systems, to simulate experiments, and to analyze data. Yet, in most…

Machine-learning (ML) techniques have revolutionized a host of research fields of chemical and materials science with accelerated, high-efficiency discoveries in design, synthesis, manufacturing, characterization and application of novel…

This article addresses the logistics of implementing projects in an undergraduate mathematics class and is intended both for new instructors and for instructors who have had negative experiences implementing projects in the past. Project…

While climate models provide insights for climate decision-making, their use is constrained by significant computational and technical demands. Although machine learning (ML) emulators offer a way to bypass the high computational costs,…

In case of inquiry-based education, the priority is the pupil's activity, developing his/her practical and research skills. We can use the knowledge and skills obtained by the pupil from other subjects. Applied informatics into physics…

The current tendency of human learning and teaching is targeted to development and integration of digital technologies (like cloud solutions, mobile technology, learning analytics, big data, augmented reality, natural interaction…

Machine learning encompasses a set of tools and algorithms which are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting…

Workflow support typically focuses on single simulation experiments. This is also the case for simulation based on finite element methods. If entire simulation studies shall be supported, flexible means for intertwining revising the model,…

Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this…

Machine learning potentials offer a revolutionary, unifying framework for molecular simulations across scales, from quantum chemistry to coarse-grained models. Here, I explore their potential to dramatically improve accuracy and scalability…

While the uptake of data-driven approaches for materials science and chemistry is at an exciting, early stage, to realise the true potential of machine learning models for successful scientific discovery, they must have qualities beyond…

The ability to perform ab initio molecular dynamics simulations using potential energies calculated on quantum computers would allow virtually exact dynamics for chemical and biochemical systems, with substantial impacts on the fields of…

Quantum simulators are a promising technology on the spectrum of quantum devices from specialized quantum experiments to universal quantum computers. These quantum devices utilize entanglement and many-particle behaviors to explore and…