Hossein Pourrahmani

- Pioneered the deployment of physics-informed AI surrogate models to replace slow, expensive traditional simulations and physical experiments. - Developed machine learning frameworks to characterize next-generation plasma-catalytic prototypes using selective experimental data. - Served as the lead mechanical designer for large-scale plasma systems, ensuring all designs were backed by deep physics and domain understanding. - Executed complex multiphysics modeling and engineering workflows across electromagnetic, electronic, mechanical, fluid flow, and structural domains. - Utilized SolidWorks (CAD + CAE) and advanced CFD/FEA tools (in addition to developing in-house codes) to architect and optimize the performance of next-generation hardware. - Analyzed and adjusted overall process flows to ensure the main prototype achieved optimal performance and efficiency. - Project-managed the scale-up and commercial transition of deep-tech prototypes from internal R&D to large-scale industrial systems. - Coordinated directly with international customers to oversee system integration and successful installation on their industrial sites. - Built and managed high-performance cloud computing workflows to accelerate data processing and handle heavy AI training models.

Summary: Led the end-to-end design, simulation, testing, and development of an advanced separation unit, from concept and multi-physics modeling to prototype iteration and GMP-ready product realization. Integrated CFD, adsorption modeling, and experimental validation to accelerate system performance and reduce development cycles. Key Achievements & Responsibilities: • Designed and engineered a novel adsorption-based separation unit, including structural design, flow-path architecture, and material selection for high-efficiency separation. • Developed and executed structural, leakage, and fluid-flow test protocols to validate mechanical integrity and optimize internal flow distribution. • Built multi-physics CFD models to analyze adsorption uniformity, pressure drop, and thermal effects, enabling data-driven design improvements. • Characterized adsorption kinetics using Gas Chromatography (GC) across multiple flow regimes, integrating data into AI-supported modeling workflows. • Created a digital twin of the separation process, combining CFD, experimental data, and model-based system engineering to accelerate performance optimization. • Led iterative prototype development, delivering a significantly improved final design through simulation-driven optimization and rapid testing loops. • Directed R&D responsibilities for GMP-aligned product development, ensuring manufacturability, reliability, and compliance with regulatory constraints. • Collaborated with industry and academic partners to validate technology pathways, support grant proposals, and expand innovation capabilities. • Contributed to strategic research on advanced separation materials, guiding decisions on sorbent selection, adsorption dynamics, and long-term performance.

Summary: Advanced molecular-scale understanding of CO₂ adsorption and developed AI-enhanced modeling frameworks to optimize carbon capture and sequestration (CCS) technologies. Combined molecular simulations, adsorption theory, and machine learning to accelerate material screening and system performance prediction. Key Achievements & Responsibilities: • Developed adsorption models using Classical Density Functional Theory (cDFT) and Molecular Dynamics (MD) to quantify CO₂ interactions with porous materials, mineral surfaces, and confined fluids. • Characterized adsorption isotherms, diffusion behavior, and free-energy landscapes, providing mechanistic insights critical for next-generation sequestration materials. • Built hybrid physics-informed + AI models to predict CO₂ adsorption capacity and kinetics across large material libraries, reducing the need for expensive simulations and experiments. • Implemented machine learning workflows (ANNs, surrogate models, regression, and optimization algorithms) to accelerate evaluation of sorbent performance under varying pressure-temperature conditions. • Integrated multi-scale modeling results into system-level CCS analysis, helping bridge molecular insights with field-scale sequestration strategies. • Collaborated with DOE-funded teams and cross-disciplinary experts, contributing to publications, grant milestones, and broader carbon management research initiatives. • Proposed AI-driven optimization frameworks for improving capture efficiency, adsorption selectivity, and operational conditions in industrial CCS processes.

Thesis title: Electrochemical devices and computer science: Water/thermal management of proton exchange membrane fuel cells and electrolyzers in different scales Led multi-scale R&D on PEM fuel cells and electrolyzers by integrating CFD, materials engineering, and AI-driven optimization. Work spanned component design, advanced microscopy, and system-level evaluation of hydrogen technologies. Key contributions: ✔ Fuel cells and electrolyzers • Developed an ultra-thin (28.9 μm) high-performance Gas Diffusion Layer (GDL) improving water/thermal management. • Proposed innovative bipolar plate designs optimized through multi-physics simulations. • Designed an IoT-based contamination detection sensor kit for electrolyzer/fuel cell diagnostics. • Evaluated hybrid battery-fuel cell architectures for aviation and maritime applications. • Applied AI/ML algorithms to optimize microstructural parameters of porous media (GDLs). ✔ Computational Fluid Dynamics (CFD) • Performed 3D multi-physics simulations of water, heat, and electrochemical reactions using Lattice Boltzmann Method (coded in Fortran) and Navier–Stokes CFD (ANSYS, COMSOL, OpenFOAM). • Designed novel fuel cell and heat exchanger geometries using simulation-driven optimization. ✔ Advanced Microscopy • Conducted high-resolution characterization of porous materials using SEM, EDX, FIB-SEM, and micro-CT. • Proposed and implemented 3D reconstruction of GDL microstructures from FIB-SEM/CT data to generate geometry-accurate CFD domains. • Performed comprehensive degradation and morphology studies to understand performance loss. ✔ Life Cycle Assessment (LCA) and Techno-Economic Analysis • Executed LCA studies for EV charging systems, electrolyzers, and integrated energy systems. • Led techno-economic evaluations connecting material-level performance to system- and grid-level impacts. • Developed frameworks combining environmental impact, cost modeling, and system optimization.

TA for different courses of Renewable energy, Engines and Fuel cells, Thermal power cycles and heat pump systems, Modeling and optimization of energy systems, Thermodynamics.

Developed a novel ultra-thin Gas Diffusion Layer (28.9 μm) for PEM fuel cells, far thinner than commercial 90-200 μm products, while overcoming the major manufacturing challenges of cracking, delamination, and structural instability. This work demonstrated how material design, multi-scale modeling, and AI can be combined to create next-generation electrochemical components with higher performance, lower cost, and reduced usage of scarce materials. Key Responsibilities & Achievements: • Designed and synthesized an ultra-thin GDL using advanced carbon materials and precision skiving techniques, maintaining mechanical stability at extremely low thicknesses. • Performed FIB-SEM and micro-CT imaging, followed by full 3D reconstruction and segmentation to characterize pore structure, degradation behavior, and transport pathways. • Conducted CFD and FEA simulations directly on the reconstructed microstructures to analyze water transport, thermal behavior, mechanical robustness, and gas diffusion efficiency. • Built AI/ML models to estimate hidden experimental conditions, predict performance metrics, and guide material formulation strategies. • Applied multi-objective optimization using metaheuristic algorithms on the AI models to determine optimal synthesis ratios and microstructural configurations. • Integrated materials science, computational modeling, and AI to develop a GDL with improved performance, enhanced stability, and reduced cost compared to conventional products. • Demonstrated a reproducible manufacturing workflow for ultra-thin GDLs, enabling potential scalability in fuel-cell applications.

TA for different courses such as Computational Fluid Dynamics (CFD), Advanced thermodynamics, and Fluid mechanics

Gas Turbine Design & Overhaul Engineering (Rolls-Royce 50 kW Turbine Project) Worked on the CAD redesign and overhaul engineering of a 50 kW Rolls-Royce gas turbine, contributing directly to component improvement, reverse engineering, and manufacturing support. This role gave hands-on exposure to turbomachinery, precision design, and simulation-driven validation. Key Responsibilities & Achievements: • Performed reverse engineering of aged turbine components to restore geometry, improve performance, and support overhaul operations. • Prepared components for 3D imaging using matte powder coating (TiO₂) to enhance surface capture accuracy. • Reconstructed worn or damaged geometries using the Digitized Shape Editor and Surface Reconstructor modules. • Redesigned multiple turbine parts, ensuring manufacturability, improved fit, and enhanced aerodynamic/structural behavior. • Conducted CFD simulations to evaluate flow distribution, combustion characteristics, cooling effectiveness, and pressure losses. • Performed FEA analyses to assess stresses, thermal expansion, fatigue risks, and material integrity under high-temperature conditions. • Collaborated with manufacturing teams to translate digital designs into production-ready components, supporting machining and quality checks. • Contributed to extending turbine life and improving performance through simulation-guided redesign and precise surface reconstruction.

Hot Test Development for Internal Combustion Engines – EF7 (1.6L) Program Led the development of an optimized hot test protocol for a newly designed inline 4-cylinder, 1.6 L naturally aspirated engine (Engine Code: EF7). The goal was to create a standardized, calibrated, and GMP-compliant procedure to evaluate performance, reliability, and operational consistency before vehicle integration. Key Responsibilities & Achievements: • Designed a comprehensive hot test protocol aligned with organizational standards and manufacturing requirements. • Analyzed engine behavior (thermal response, vibration, fuel-air dynamics, pressure profiles) to define critical test parameters and acceptance criteria. • Collaborated with manufacturing teams to ensure GMP compliance, repeatability, and operational safety in the testing workflow. • Calibrated sensors, instrumentation, and test bench equipment to ensure accuracy and reproducibility of measured data. • Validated the protocol through iterative test cycles, data analysis, and cross-functional reviews. • Successfully delivered a fully operational test protocol adopted for production-line testing of the EF7 engine, in collaboration with supervisor Mr. Reza Fallahmorad. • Contributed to quality assurance and reliability improvements for one of the company’s most widely used passenger car engines.

Thesis title: Electrochemical devices and computer science: water/thermal management of proton exchange membrane fuel cells and electrolyzers in different scales In addition to the developed projects as a research assistant, there was special focus on Artificial Neural Network (ANN) Modelling and Optimization. I am glad that I could innovatively integrate Energy Studies and Computer Science to develop methodologies for energy system optimization. I'm also proficient in using Artificial Neural Network (ANN) modeling for non-linear system optimization, enabling precise and efficient solutions for complex energy challenges. My research during this period is also internationally recognized in enhancing the water/thermal management of Gas Diffusion Layer (GDL) in PEM fuel cells. In this field, I could successfully develop and test novel GDLs, contribute to improved fuel cell performance during contamination and aging. My research is also known to propose novel designs for bipolar plates.

1) Economic Analyses Proficient in performing Exergoeconomic and Thermoeconomic analyses for renewable energy systems. Specialized in conducting detailed cost analyses for fuel cells and batteries, particularly in the maritime and aviation sectors. Adept at identifying cost-effective solutions while considering long-term sustainability and performance. 2) System Integration and Multi-generation Systems Engineering Recognized for expertise in analyzing multi-generation systems from Energy, Exergy, Economic, and Environmental (4E) perspectives. Successfully developed novel system designs aimed at optimizing costs, minimizing environmental impact, and maximizing energy and exergy efficiencies. Proven ability to integrate diverse energy sources into cohesive, sustainable systems.