2024 AIChE Annual Meeting

Session: Meet the Industry Candidates Poster Session: Computing And Systems Technology Division

An analog to the Meet the Faculty Candidate Poster Session, the Meet the Industry Candidates Poster Session and Reception will provide an excellent opportunity for graduate students to showcase their research to industrial attendees, talent scouts, and recruiters who regularly attend the AIChE Annual Meeting.

Co-Chairs

Baratsas, S., ExxonMobil
Zanfir, M., Linde

Presentations

(364a) Development of Fast-Charging Protocol Considering Cell-to-Cell Variability of Lithium-Ion Batteries
(364an) Process Mapping and Optimization through Adaptive Machine Learning for a Laser Powder Bed Fusion (L-PBF) Additive Manufacturing Process
(364ai) A Multiscale Modeling Framework for Sustainable Chemical Processes with Decision-Making Applications
(364aq) Energy Systems
(364v) Process Modeling and Techno-Economic Optimization for Producing Value-Added Products from Lignocellulosic Biomass
(364b) Simplest Mechanism Builder Algorithm (SIMBA)
(364m) Hyper-Sample-Efficient Optimization of Expensive Simulation-Based Models for Process Design Under Uncertainty
(364r) Synergistic Design of Catalysts: Integrating Density Functional Theory and Machine Learning
(364n) Decarbonization of Processing Systems and Value Chains through Optimal Resource Integration
(364c) Design and Optimization of Integrated Energy Systems with Market Interactions
(364ae) Innovative Approaches to Medical Challenges Using Computational Chemical Engineering Principles
(364w) Modeling Affinity Maturation to Recapitulate Germinal Center Dynamics
(364d) Mathematical Modeling of Lipid Metabolism Using Cybernetic Framework (Kinetic Modeling Technique) and Novel Information-Theoretic Approaches
(364e) Kinetic Modeling of Eicosanoid Metabolism Using Cybernetic Framework and Novel Information-Theoretic Approaches
(364k) Machine Learning-Enhanced Tools for Bioprocess Modelling
(364s) Dynamic Modeling and Estimation for Condition Monitoring of Energy Systems
(364o) Polarizable Force Field Development and Molecular Dynamics Simulation for High Ionic Concentration Systems
(364af) Integrating Data-Driven and Knowledge-Based Methodologies: Designing a Framework for Chemical Process Modeling
(364x) Modeling and Solution Strategies for the Optimization of Multi-Timescale Process Systems
(364p) Machine Learning Aided Tools for Separation Processes
(364f) Dynamic Risk-Based Operability and Control Strategies for Smart and Sustainable Process Operations
(364y) Data-Driven and Physics-Informed Machine Learning Applications in Real-Time Decision Making and Predictive Control
(364q) Revealing Molecular Mechanisms in Polymeric Membranes through Molecular Simulation and Modeling
(364z) Development of Algebraic and Topological-Based Structured Packing Model for Rapid Development of Designs
(364al) Systematic Exploration of the Structural Design Space of Metal–Organic Frameworks for Ultrahigh Capacity Hydrogen Storage Using Molecular Simulation and Machine Learning
(364aa) Identifying Cost Saving Opportunities through Coordinating Deliveries to Vendor-Managed Inventory Customers
(364t) Computation-Led Design of Bimetallic Catalysts for Renewable Fuel Production
(364l) Integrated Modeling and Experimental Design for the Digital Design of Pharmaceutical Manufacturing Processes
(364ab) Low-Field Magnetic Resonance Relaxation: Signals, Mechanisms, and Applications in Porous Media
(364ag) Exploring Gas Diffusion in the Codh/ACS Enzyme Complex Using Molecular Simulations.
(364ac) Sustainable Aviation Fuels (SAF) from Ethanol: An Integrated Systems Modeling Approach
(364aj) Stiction Detection in Valve Using He’s Model By Simulation of Equal Percentage Valve Characteristic Transfer Function
(364ad) Theoretical View on Alternative Oxygen Evolution Reactions for Heterogeneous Catalysis
(364h) Development of All-Atomistic Force Fields to Model the Polarization Interactions of Liquids with Hexagonal Boron Nitride and Boron Nitride Nanotubes
(364i) Bridging Physics-Based Simulations and AI-Driven Methods to Accelerate the Design of the Next-Generation Polymers
(364am) Addressing the water-energy nexus with reverse electrodialysis and disjunctive optimization
(364ak) Integrated Machine Learning Prediction of Cardiac Fibrosis and Heart Failure Patients.
(364ao) The Design and Operation of Carbon Capture, Utilization, and Storage (CCUS) Supply Chain Networks Under Uncertainty
(364ap) System Dynamics Modeling for the Sustainable Urban Development in the City of Cape Town: A Water-Energy-Food Nexus Approach
(364j) Assessing Accuracy and Improving Prediction of Chemical Reaction Barriers Using Density Functional Theory and Machine Learning Approaches
(364u) Exploring Gas Diffusion Pathways in the Carbon Monoxide Dehydrogenase/Acetyl-CoA Synthase (CODH/ACS) Enzyme Complex Using Molecular Simulations.