What is Computational Science?

The electrostatic potential of isopropanolamine mapped onto its electron density. Blue areas are electron poor; red areas are electron rich.

Chemistry modeling, engineering simulation, and data analytics – or more broadly, computational science – is a general purpose, alternative way to better understand and solve practical chemical problems in a structured and detailed manner. Like the experimental chemist, who uses the laboratory to verify a chemical hypothesis, the computational chemist uses models to gain insight into the chemistry of a particular process.

Computational science applies theoretical models and runs computer software to provide technical information based on quantum chemistry, transport phenomena, and statistics. It can accurately predict the physical, material, and performance properties of both established and new materials and processes. As computers and information tools grow more connected, the ability to exploit quantitative computational methods becomes an essential competitive tool for rapid problem resolution.

Benefits of Computational Science

The energy diagram for the reaction X + Y → Z, with and without a catalyst, showing reactant, product, transition state, activation, and reaction energies.

Judicious application of modeling, simulation, and data analytics allows materials scientists, chemists, and engineers to predict and understand the relationships of a material’s elemental structure with its properties and behavior. This additional technical knowledge permits the reliable engineering of new, better-performing, and more cost-effective materials of all types, such as pharmaceuticals, catalysts, polymers and composites, metal alloys, and batteries and fuel cells.

Modeling and simulation results significantly hasten the understanding of a chemical concern more efficiently than only testing and experimentation. This acceleration is a byproduct of the more robust experimental and computational scientific data set. Correlated with known phenomena and analyzed for trends or anomalies, that data set can be confidently mined to identify gaps or opportunities for improvement. These discoveries feed into better statistical design of new experiments or calculations which, in turn, provide more data that make it easier to improve product quality, control costs, decrease waste, enhance safety, etc. The tools of computational science translate the principles of science and engineering into dependable and practical actions.

Computational Science Projects

A material’s X-ray diffraction pattern inspires a computational model of the catalytic surface to study reaction chemistry.

With over 25 years of industry experience, Environmental Standards, Inc.’s computational science professionals provide technical advice, trusted guidance, purposeful application, and dependable support for computer-aided advanced modeling and simulation. Our expertise delivers the opportunity to improve or innovate your products or processes faster. Our goal is to help you think about your problem from a different perspective and deliver accurate, actionable solutions.

Fundamental Capabilities

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One of the greatest strengths of computational science methods is that one can study any molecule or chemical process. In fact, computational experiments are limited only by the imagination of the scientist and, of course, the computer resources that are available. This ability profoundly impacts the acquisition of detailed and pertinent chemical information on compounds that have not been experimentally characterized or even synthesized.