Read our articles about computational chemistry


Computational development of metal-organic frameworks for sustainability

Metal-organic frameworks (MOFs) are a fascinating class of hybrid porous solids made from the self-assembly of inorganic centres and organic linkers. Due to their reticular nature, MOFs offer a wide range of possibilities for the design of new materials with tailored chemistries and properties. These materials have already demonstrated a versatile potential for applications including gas sorption and separation, catalysis, drug delivery, and water harvesting. Nowadays, as databases of hundreds of thousands of synthesized and [...]

In silico evaluation of asphaltene inhibitor performances

A predominant challenge for the oil and gas industry is the deposition of asphaltene, a class of compounds defined as the fraction of crude oil that is soluble in toluene but not in n-heptane. Asphaltene, known as the “cholesterol” of crude oil, is among the heaviest and most polar components of petroleum fluids and can precipitate in the reservoir and plug production and transportation flowlines, risking economic loss due to flow interruption and environmental [...]

Surfactants for Flow Assurance: Adsorption study via Molecular Modeling

Under appropriate pressure and temperature conditions, the self-assembly of water molecules can result in the formation of gas hydrates, a solid, ice-like material that is composed of molecules of appropriate size (typically small hydrocarbon species) enclathrated in three-dimensional water cages. Due to the favorable conditions, gas hydrates can form spontaneously during oil and gas production and threaten the safety and economic viability of the operation processes. Indeed, as oilfields mature, they produce increasing quantities [...]

Data-driven discovery of new chemicals

Data-driven approaches have experienced an impressive growth over the last few years, thanks to the availability of large resources (i.e., databases) and the development of off-the-shelf machine learning (ML) methods. The combination of big data and ML is sparking the “fourth industrial revolution” and a new paradigm of science. In this context, it can add a new dimension to chemical discovery and allow to accelerate the chemicals value chain from discovery to deployment. Many flavours [...]

Lubricant additives: Friction modifiers

Tribology is the science that studies friction, wear and lubrication of surfaces in relative motion, such as any kind of engines. With the transport and industry sectors accounting for more than 60% of the global energy consumption, tribology is key to achieve energy efficiency and has a huge economic impact. Different machine elements operate under different conditions and thus experience different levels of friction and lubrication. A well-established model that describes the different lubrication [...]

Lubricant additives: Adsorption

Modern engine lubricants are a complex blend of a base oil and a package of dissolved additive molecules (5-20%) that impart new properties or improve existing ones. This additive technology has been indispensable for lubrication since it was born in the early petroleum age. Considering their function, lubricant additives can be classified into detergents, dispersants, viscosity-modifiers, anti-wears, corrosion inhibitors or friction modifiers. The performance of friction modifiers and anti-wears depends on their ability to [...]

Molecular modeling of anti-agglomerants for Oil & Gas applications

Surfactants (short for surface active agent) are molecules used to alter interfacial properties by adsorbing at the boundary between two immiscible phases, and play an important role in many industrial applications. A particular situation where surfactants are vital to effective operation is flow assurance in oil and gas extraction, where gas hydrates (inclusion compounds that consist of water and small hydrocarbon molecules) can form spontaneously under common operation conditions, causing pipeline and equipment blockages [...]

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