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Binding Energy Determination of CO₂ Adsorption in MOF-74 with Diffusion Monte Carlo

This record is embargoed.

• Embargo End Date: 2027-05-19

Date: 2022-01-01

Creator: Yucheng Hua

Access: Embargoed

Assessing the Accuracy of Quantum Monte Carlo Pseudopotentials for CO2 Capture in Metal Organic Frameworks

Date: 2021-01-01

Creator: Chloe Renfro

Access: Open access

As global emissions of CO2 and other greenhouse gases rises, global warming persists as an imminent threat to the environment and every day lives. To reduce greenhouse gas emissions in the atmosphere, there is a need to design materials to separate and capture the different gasses. Current gas capturing technologies lack efficiency and have extensive energy costs. A class of materials for CO2 capture is Molecular Organic Frameworks (MOFs). In order for a MOF to be efficient for this type of separation, the MOF needs to be able to selectively bind to the gas, while also not suffering a high energy cost to remove the gas and reuse the material. Computationally calculated binding energies are used to determine the usefulness of a MOF at capture and separation of a certain gas. Each computational method has its advantages and limitations. In this work, diffusion quantum Monte Carlo is being explored. This paper focuses on the accuracy of recently developed pseudopotentials for DMC use. These pseudopotentials have been tested on smaller molecules but have not been systematically tested for systems such as MOFs. Results from a DMC calculation of Zn-MOF-74 show a binding energy of -18.02 kJ/mol with an error bound of 16.74 kJ/mol. In order to assess the accuracy of the DMC results for binding energies of this magnitude the uncertainty need to be reduced, a subject of ongoing work.

Benchmarking Ab Initio Computational Methods for the Quantitative Prediction of Sunlight-Driven Pollutant Degradation in Aquatic Environments

Date: 2016-05-01

Creator: Kasidet Trerayapiwat

Access: Open access

Understanding the changes in molecular electronic structure following the absorption of light is a fundamental challenge for the goal of predicting photochemical rates and mechanisms. Proposed here is a systematic benchmarking method to evaluate accuracy of a model to quantitatively predict photo-degradation of small organic molecules in aquatic environments. An overview of underlying com- putational theories relevant to understanding sunlight-driven electronic processes in organic pollutants is presented. To evaluate the optimum size of solvent sphere, molecular Dynamics and Time Dependent Density Functional Theory (MD-TD-DFT) calculations of an aniline molecule in di↵erent numbers of water molecules using CAM-B3LYP functional yielded excited state energy and oscillator strength values, which were compared with data from experimental absorption spectra. For the first time, a statistical method of comparing experimental and theoretical data is proposed. Underlying Gaussian functions of absorption spectra were deconvoluted and integrated to calculate experimental oscillator strengths. A Matlab code written by Soren Eustis was utilized to decluster MD-TD-DFT results. The model with 256 water molecules was decided to give the most accurate results with optimized com- putational cost and accuracy. MD-TD-DFT calculations were then performed on aniline, 3-F-aniline, 4-F-aniline, 3-Cl-aniline, 4-MeOacetophenone, and (1,3)-dimethoxybenzophenone with CAM-B3LYP, PBE0, M06-2X, LCBLYP, and BP86 functionals. BP86 functional was determined to be the best functional. Github repository: https://github.com/eustislab/MD_Scripts