2023 AIChE Annual Meeting

Session: Undergraduate Student Poster Session: Computing and Process Control

Presentations

10:00 AM

Diffusion and Sedimentation in Suspensions of Shape-Anisotropic Nanoparticles
Interfacial Competition between Surfactant and Polymer Excipients on a Drug Nanocrystal Surface
Sequence Patterning, Morphology, and Dispersity in Single-Chain Nanoparticles: Insights from Simulation and Machine Learning
Enabling the Structure-Property Predictions of New Organic Photovoltaic Chemistries with Quantum Chemical Parameterizations
Magma: A Robust, User-Friendly Kinetic Modeling Platform for Simulating and Optimizing Algal Bioprocesses
Cooking with Chem-E: Analysis of Sensitivities of Assumptions in Multilayered Beef Wellington Comsol Model
Development of Automated Active Learning Loop for the Prediction of Zeolite-OSDA Binding Energies
Designing Automated Systems to Monitor the Effect of Humidity on Membrane Permeability
Zero-Point Energies from Bond Orders and Populations Relationship
Mathematically Modeling Chemokine Ligand-Receptor Kinetics in the Context of Pancreatic Cancer
A Machine-Learning Approach to Simulate Confined Liquid Lithium Polysulfides for Battery Applications
Computer-Verified BET Analysis Using the Lean Theorem Prover.
Machine Learning for Predicting Cradle-to-Gate Life Cycle Inventory (LCI) Data
Eco-COMP: Towards Responsible Computing in Materials Science
A Computational Tool for Taxadiene Synthase Mutation Site Screening
Molecular Dynamics Discovers Ligand Binding Regions on Molybdate Transport Protein, Moda
CFD Analysis of Mixing in the Transition Regime: User-Defined Functions and Viscosity Variations
CFD Analysis of Repaired Coarctation of the Aorta
Modeling Blood Flow in Repaired and Healthy Aortic Arches Using Computational Fluid Dynamics
Development and Optimization of Robotic Nanodroplet Dispenser with Hydrophobic Needles and Computer Vision
Predicting Vapor-Liquid Equilibria Using Physic-Inspired Machine Learning Models
Autonomous Image Segmentation for Single Nanoparticle Tracking in Liquid Phase Transmission Electron Microscopy
Leveraging Large Language Models for Molecular Property Prediction in Scientific Research
Automating Self-Driving Laboratory Growth ASSAY Protocol to Efficiently Measure Cell Antibiotic Resistance
Melting Point Predictions of Thermally Stable Ionic Liquids Using a Machine Learning Approach.
Development of Machine-Learning Models for the Prediction of Membrane Active Peptides with Cell-Penetrating Capabilities Based on Amino Acid Periodicities
Characterizing Dialysis Efficacy, Kidney Failure, and Renal Recovery Using Blood Urea Nitrogen (BUN) Modeling
Exploring Machine Learning Models for Predicting Vapor Pressure
Enhancing Sabatier Reaction Efficiency with Membrane Reactors
Group Theory and Artificial Intelligence
Deciphering the Unfolding Pathway of Bovine Serum Albumin Under Varying External Stressors: Insights from Molecular Dynamics Simulation