Transport Processes
Transport Processes
Mass Transport Implications on RDE Applications
Mass Transport Implications on RDE Applications
Description:
Description:
In my first semester, one of my most notable presentations was when assigned to make a poster presentation summarising two recently published research articles relating to mass transport. I chose to look into mass transport effects in the context of Rotating Disc Electrodes (RDEs). RDEs are hydrodynamic electrodes that make use of curvilinear angular fluid motion to ensure a continuous flux of analyte reaches the electrode. It's application ranges from corrosion studies to fuel cell research. The papers I discussed used a combination of theoretical principles (Fick's laws and momentum conservations) and computational techniques (PDE solver - Freefem+, CFD software - StarCCM+ ) to explore and analyze the mass transport effects that end up affecting RDE perfomances in different uses and conditions.
In my first semester, one of my most notable presentations was when assigned to make a poster presentation summarising two recently published research articles relating to mass transport. I chose to look into mass transport effects in the context of Rotating Disc Electrodes (RDEs). RDEs are hydrodynamic electrodes that make use of curvilinear angular fluid motion to ensure a continuous flux of analyte reaches the electrode. It's application ranges from corrosion studies to fuel cell research. The papers I discussed used a combination of theoretical principles (Fick's laws and momentum conservations) and computational techniques (PDE solver - Freefem+, CFD software - StarCCM+ ) to explore and analyze the mass transport effects that end up affecting RDE perfomances in different uses and conditions.
Nature of Project :
Nature of Project :
-Individual Project
-Individual Project
-Transport Phenomena
-Transport Phenomena
-Electrochemistry
-Electrochemistry
-Research Summary
-Research Summary
Concepts Utilised:
Concepts Utilised:
-Mass Transport Processes
-Mass Transport Processes
-Fick's Laws
-Fick's Laws
-Convective-Diffusion Relations
-Convective-Diffusion Relations
-Rotating Disc Electrodes
-Rotating Disc Electrodes
-Electrochemical Engineering
-Electrochemical Engineering
Final Poster*:
Final Poster*:
Final poster.pdf
Statistical Mechanics and Molecular Simulations
Statistical Mechanics and Molecular Simulations
Monte Carlo NPT and NVT ensemble analysis
Monte Carlo NPT and NVT ensemble analysis
Description:
Description:
Monte Carlo is a popular computational technique used to predict the trajectory of atomic particles by systematically invoking random particle perturbations. Its fundamental algorithm is intrinsically formulated for the NVT (canonical) system, however through slight algorithmic modifications, Monte Carlo can be made to work for various other ensembles and systems. A noteable report I generated in my second semester was in the study of the popular NVT (Canonical) and NPT (Isothermal-Isobaric) ensembles/systems. In it, I developed relevant simulations through custom Monte Carlo algorithms and analysed the resulting system properties, energy distributions as well as their errors.
Monte Carlo is a popular computational technique used to predict the trajectory of atomic particles by systematically invoking random particle perturbations. Its fundamental algorithm is intrinsically formulated for the NVT (canonical) system, however through slight algorithmic modifications, Monte Carlo can be made to work for various other ensembles and systems. A noteable report I generated in my second semester was in the study of the popular NVT (Canonical) and NPT (Isothermal-Isobaric) ensembles/systems. In it, I developed relevant simulations through custom Monte Carlo algorithms and analysed the resulting system properties, energy distributions as well as their errors.
Nature of Project :
Nature of Project :
-Individual Project
-Individual Project
-Atomistic Simulations
-Atomistic Simulations
-Statistical Thermodynamics
-Statistical Thermodynamics
-Ensemble/System Comparisons
-Ensemble/System Comparisons
-Computational Modelling
-Computational Modelling
Concepts Utilised:
Concepts Utilised:
-1st and 2nd laws of Thermodynamics
-1st and 2nd laws of Thermodynamics
-Metropolis criterion
-Metropolis criterion
-Log Volume Scaling
-Log Volume Scaling
-Maxwell Relations
-Maxwell Relations
-Ensemble Average - Property relations
-Ensemble Average - Property relations
Final Report*:
Final Report*:
Molecular_Simulations_Final Project Report_KennethKusima.pdf
SAMSUNG AI CAPSTONE PROJECT
SAMSUNG AI CAPSTONE PROJECT
Ground State Energy Prediction
Ground State Energy Prediction
Samsung Innovation Campus
November 2021 – May 2022
Description:
Description:
From agricultural products to cosmetics, the function behind any product is governed by its molecular properties. Currently, molecular property prediction is primarily based on density-functional theory which produces accurate yet computationally expensive simulations. We strive to drive down computing time by modeling molecular features based upon the spatial structure and type of atoms within a molecule. Ground state energy is the lowest possible energy of a molecule and is useful in determining thermodynamic properties of the molecule. Given DFT-obtained ground state energy information from PubChem on over 250,000 nonmetallic molecules made up of H,C,N,O,F,Si,P,S,Cl,Br,andI elements, we defined relevant molecular property features. These features were used to predict the molecular property - namely, the ground state energy. The resulting predictive ability could in turn help in informing chemical synthesis mechanisms and provide the possibility of a quicker route to discovering new useful materials and products.
From agricultural products to cosmetics, the function behind any product is governed by its molecular properties. Currently, molecular property prediction is primarily based on density-functional theory which produces accurate yet computationally expensive simulations. We strive to drive down computing time by modeling molecular features based upon the spatial structure and type of atoms within a molecule. Ground state energy is the lowest possible energy of a molecule and is useful in determining thermodynamic properties of the molecule. Given DFT-obtained ground state energy information from PubChem on over 250,000 nonmetallic molecules made up of H,C,N,O,F,Si,P,S,Cl,Br,andI elements, we defined relevant molecular property features. These features were used to predict the molecular property - namely, the ground state energy. The resulting predictive ability could in turn help in informing chemical synthesis mechanisms and provide the possibility of a quicker route to discovering new useful materials and products.
Nature of Project :
Nature of Project :
-Group Project
-Group Project
-Artificial Intelligence
-Artificial Intelligence
-Report Generation
-Report Generation
-Research
-Research
Concepts Utilised:
Concepts Utilised:
-Machine Learning
-Machine Learning
-First Principle Calculations
-First Principle Calculations
-Quantum Mechanics
-Quantum Mechanics
-Ground State Energies
-Ground State Energies
Final Report*:
Final Report*:
SIC Project.pdf
DFT for Catalysis Summer School Workshop
DFT for Catalysis Summer School Workshop
Institute for Computational Molecular Science Education | Dave C. Swalm School of Chemical Engineering Bagley College of Engineering Mississippi State University
June 13 – 17, 2022
Dynamic microkinetic modelling using DFT
Dynamic microkinetic modelling using DFT
Description:
Description:
I attended a workshop regarding the use of DFT (Density Functional Theory) in catalysis. In addition to learning the theory behind DFT, and getting hands on practice on using CP2K ( a popular open-source DFT software), I had the opportunity to present a poster on my proposed efforts to use DFT to obtain the relevant parameters needed to perform my intended dynamic microkinetic modelling.
I attended a workshop regarding the use of DFT (Density Functional Theory) in catalysis. In addition to learning the theory behind DFT, and getting hands on practice on using CP2K ( a popular open-source DFT software), I had the opportunity to present a poster on my proposed efforts to use DFT to obtain the relevant parameters needed to perform my intended dynamic microkinetic modelling.
Nature of Project :
Nature of Project :
-Individual Presentation
-Individual Presentation
-Computational Kinetic Modelling
-Computational Kinetic Modelling
-Statistical Thermodynamics
-Statistical Thermodynamics
-Poster Presentation
-Poster Presentation
Concepts Utilised:
Concepts Utilised:
-Mean Field Microkinetics
-Mean Field Microkinetics
-Harmonic Transition State Theory
-Harmonic Transition State Theory
-Bragg-Williams approximation
-Bragg-Williams approximation
-Density Functional Theory
-Density Functional Theory
Final Poster*:
Final Poster*:
Final_Poster_Kenneth_DFT workshop_2022.pdf