Handson Gisubizo
From molecular insight to better process design.
I work at the intersection of simulation and experiment. I use first-principles methods to predict mechanisms, energetics, and material behavior, then validate them in the lab. My goal is closing the loop between molecular-scale understanding and real process decisions. My toolkit includes ORCA for DFT, LAMMPS for molecular dynamics, and Python for analysis and machine-learned force fields.
Toolkit · what I use
Selected Work · 12 projects
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01
NEB Transition State: Methanol + Chloride
Located and characterized the transition state of the methanol and chloride substitution using Nudged Elastic Band with ORCA.
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02
NaCl Solvation: XTB Analysis
Studied ion and water interactions and solvation shell structure of NaCl using semi-empirical XTB simulations.
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03
15-Water Cluster: Geometry & IR Spectra
Optimized cluster geometries and computed vibrational IR spectra to probe hydrogen-bond network structure.
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04
Partial Charge Analysis of Water Clusters
Computed and compared partial charges across cluster sizes to map electronic redistribution under H-bonding.
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05
Temperature-Dependent Thermodynamics of (H₂O)₁₅
Calculated internal energy, enthalpy, and Gibbs free energy of a 15-water cluster across a temperature range.
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06
Butane Conformer Analysis
Mapped the torsional energy surface of butane and quantified relative conformer stability via DFT.
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07
HOH Bond Angle Study
Probed the energy dependence of water's HOH bond angle around equilibrium and quantified the stiffness of the bend.
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08
Water Dimer: O-O Interaction Analysis
Scanned the O-O distance of the water dimer to characterize the hydrogen bond's well depth and equilibrium length.
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09
Water Dimer Hydrogen Bond Analysis
Quantified hydrogen-bond geometry and interaction energy in the water dimer at the DFT level.
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10
Full DFT Project Report PDF
Consolidated documentation: methods, inputs, results, and discussion across all ORCA-based studies above.
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11
Water Cluster Cooling: LAMMPS MD In Progress
Modeling thermal relaxation and structural reorganization of water clusters using classical molecular dynamics in LAMMPS.
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12
ORCA-DFT Machine-Learned Force Field for Water In Progress
Training an equivariant neural-network potential (NequIP) on DFT-computed energies and forces to bridge quantum accuracy and MD speed.