### Novel Solvents for Point Source Capture Novel solvents, such as water-lean and multiphase solvents, which could offer lower-energy requirements, but it is difficult to predict the properties of the potential material at a molecular level. Quantum computing promises to enable more accurate modeling of molecular structure to design new, effective solvents for a range of CO2 sources ### Reinventing existing catalytic processes for capturing CO2 through using Quantum Computing to find cheaper & readily available substitutes *Use quantum computing to design new materials capable of capturing CO2 more efficiently* and accelerating the development of [[Carbon Capture Use & Storage (CCUS) MOC]] One of the **most important catalytic processes to crack** in order to reduce the greenhouse gases in the atmosphere is the **binding and transformation of carbon dioxide**_._ As a matter of fact, its infrared absorption properties make it a major factor in climate change [1]. Nonetheless, it should be, in principle, captured naturally by oceans and trees, but our production of this gas has exceeded these natural capture rates by several decades. [[Catalysis]] The *existing catalytic processes to capture CO₂* are currently based on **expensive precious metals** and so we would need a cheap and readily available substitute. We have an almost infinite plethora of possible molecules that could fulfil this task, but testing each one of them is almost impossible without the possibility to efficiently and quickly simulate the properties of these candidates. [[Metals]] The role of quantum computers could be crucial for these simulations in the medium term and investments in this direction already exist: for instance_,_ in 2020 the fuel company TotalEnergies announced a partnership with Cambridge Quantum Computing with the aim of improving materials for CO₂ capture [2, 3]. To improve the capture of CO2, Total is working on **nanoporous materials called adsorbents**, considered to be among the most promising solutions. These materials could eventually be used to trap the CO2 emitted by the Group's industrial operations or those of other players (cement, steel etc.). The CO2 recovered would then be concentrated and reused or stored permanently. These materials could also be used to capture CO2 directly from the air (Direct Air Capture or DAC). [[Sorbent Materials]] The quantum algorithms which will be developed in the collaboration between Total and CQC will **simulate all the physical and chemical mechanisms in these adsorbents as a function of their size, shape and chemical composition, and therefore make it possible to select the most efficient materials to develop.** Currently, such simulations are impossible to perform with a conventional supercomputer, which justifies the use of quantum calculations. > The use of quantum computing to model materials, as a part of the materials discovery process, for use in carbon capture and sequestration. They developed a quantum computing methodology describing the **binding of molecular carbon dioxide with a material being actively researched for carbon capture, called a [[Metal-Organic Frameworks - MOFs]]** This family of materials is of great scientific interest because they are capable of absorbing carbon dioxide with low energy requirements. These **synthetic materials are porous**, which gives them their ability to bind to carbon dioxide molecules. MOFs can be compared to “molecular LEGO”, as they can take many different configurations, which result in specific pore sizes and reactivity. **They can in principle be used to design materials with specific properties.** Using classical computers to model these systems often **yields imprecise solutions.** Using a novel quantum method, the team opens a door to potentially overcoming some of the limitations of classical approaches. Due to the **natural way in which many-body interactions can be treated, as well as the sheer size of the computational space,** quantum computing is a natural future alternative for modelling such systems. Modeling complex materials like MOFs is challenging. The breakthrough represented by this paper is the **use of fragmentation strategies to break down the computational task, providing a robust and versatile approach that combines quantum and classical computing methods.** The work revealed the way today’s **quantum computers modeling complex many-body interactions can increase our understanding of MOF-CO2 systems.** It potentially accelerates our ability to use quantum computers to solve challenges that could play an important role in tackling climate change. --- [1] [Quantum computing enhanced computational catalysis (aps.org)](https://journals.aps.org/prresearch/pdf/10.1103/PhysRevResearch.3.033055) [2] [Quantum computing for innovative climate change solutions | World Economic Forum (weforum.org)](https://www.weforum.org/agenda/2019/12/quantum-computing-applications-climate-change/) [3] [Total is exploring quantum algorithms to improve CO₂ capture | TotalEnergies.com](https://medium.com/r?url=https%3A%2F%2Ftotalenergies.com%2Fmedia%2Fnews%2Fnews%2Ftotal-exploring-quantum-algorithms-improve-co2-capture) [4] [Modelling Carbon Capture on Metal-Organic Frameworks with Quantum Computing](https://arxiv.org/abs/2203.15546) [Advancements in adsorption based carbon dioxide capture technologies- A comprehensive review](https://www.sciencedirect.com/science/article/pii/S240584402309549X) [Recent advances in direct air capture by adsorption](https://pubs.rsc.org/en/content/articlelanding/2022/cs/d1cs00970b) ![[Pasted image 20220710004645.png]] #quantum