Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert t... more Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert the chemical energy stored in fuel into electrical energy with a practical conversion efficiency as high as 65%. In the past years, significant progress has been made in PEM fuel cell commercialization. By 2019, there were over 19,000 fuel cell electric vehicles (FCEV) and 340 hydrogen refueling stations (HRF) in the U.S. (~8,000 and 44, respectively), Japan (~3,600 and 112, respectively), South Korea (~5,000 and 34, respectively), Europe (~2,500 and 140, respectively), and China (~110 and 12, respectively). Japan, South Korea, and China plan to build approximately 3,000 HRF stations by 2030. In 2019, Hyundai Nexo and Toyota Mirai accounted for approximately 63% and 32% of the total sales, with a driving range of 380 and 312 miles and a mile per gallon (MPGe) of 65 and 67, respectively. Fundamentals of PEM fuel cells play a crucial role in the technological advancement to improve fuel cell performance/durability and reduce cost. Several key aspects for fuel cell design, operational control, and material development, such as durability, electrocatalyst materials, water and thermal management, dynamic operation, and cold start, are briefly explained in this work. Machine learning and artificial intelligence (AI) have received increasing attention in material/energy development. This review also discusses their applications and potential in the development of fundamental knowledge and correlations, material selection and improvement, cell design and optimization, system control, power management, and monitoring of operation health for PEM fuel cells, along with main physics in PEM fuel cells for physics-informed machine learning. The objective of this review is three fold: (1) to present the most recent status of PEM fuel cell applications in the portable, stationary, and transportation sectors; (2) to describe the important fundamentals for the further advancement of fuel cell technology in terms of design and control optimization, cost reduction, and durability improvement; and (3) to explain machine learning, physics-informed deep learning, and AI methods and describe their significant potentials in PEM fuel cell research and development (R&D).
The presence of atmospheric brown carbon (BrC) has been the focus of many recent studies. These p... more The presence of atmospheric brown carbon (BrC) has been the focus of many recent studies. These particles, predominantly emitted from smoldering biomass burning, absorb light in the near-ultraviolet and short visible wavelengths and offset the radiative cooling effects associated with organic aerosols. Particle density dictates their transport properties and is an important parameter in climate models and aerosol instrumentation algorithms, but our knowledge of this particle property is limited, especially as functions of combustion temperature and fuel type. We measured the effective density (ρ) and optical properties of primary BrC aerosol emitted from smoldering combustion of Boreal peatlands. Energy transfer into the fuel was controlled by selectively altering the combustion ignition temperature, and we find that the particle ρ ranged from 0.85 to 1.19 g cm corresponding to ignition temperatures from 180 to 360 °C. BrC particles exhibited spherical morphology and a constant 3.0 ...
In this study, we investigate the spatial variations of discharge precipitate and cathode reactio... more In this study, we investigate the spatial variations of discharge precipitate and cathode reaction rate in lithium (Li)-air battery both theoretically and experimentally: (1) the reaction variation of local oxygen reduction reaction (ORR) rate is theoretically analyzed, with analytical solutions as a function of the Damköhler (Da) number; (2) a novel experimental method is proposed to probe local ORR rate by designing a multi-layer cathode which consists of three identical Toray® carbon clothes that have a porosity of 0.8 and a thickness of about 0.4 mm. The morphology of insoluble Li compounds at different thickness locations is uncovered by SEM images. An overall very small volume fraction of precipitates was observed in the air cathode. It is found that the local ORR rate decreases from the air side of cathode to the separator side in the case of study, which is consistent with our model predictions for two orders of the cathode reaction. The theoretical analysis and experimental...
Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert t... more Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert the chemical energy stored in fuel into electrical energy with a practical conversion efficiency as high as 65%. In the past years, significant progress has been made in PEM fuel cell commercialization. By 2019, there were over 19,000 fuel cell electric vehicles (FCEV) and 340 hydrogen refueling stations (HRF) in the U.S. (~8,000 and 44, respectively), Japan (~3,600 and 112, respectively), South Korea (~5,000 and 34, respectively), Europe (~2,500 and 140, respectively), and China (~110 and 12, respectively). Japan, South Korea, and China plan to build approximately 3,000 HRF stations by 2030. In 2019, Hyundai Nexo and Toyota Mirai accounted for approximately 63% and 32% of the total sales, with a driving range of 380 and 312 miles and a mile per gallon (MPGe) of 65 and 67, respectively. Fundamentals of PEM fuel cells play a crucial role in the technological advancement to improve fuel cell performance/durability and reduce cost. Several key aspects for fuel cell design, operational control, and material development, such as durability, electrocatalyst materials, water and thermal management, dynamic operation, and cold start, are briefly explained in this work. Machine learning and artificial intelligence (AI) have received increasing attention in material/energy development. This review also discusses their applications and potential in the development of fundamental knowledge and correlations, material selection and improvement, cell design and optimization, system control, power management, and monitoring of operation health for PEM fuel cells, along with main physics in PEM fuel cells for physics-informed machine learning. The objective of this review is three fold: (1) to present the most recent status of PEM fuel cell applications in the portable, stationary, and transportation sectors; (2) to describe the important fundamentals for the further advancement of fuel cell technology in terms of design and control optimization, cost reduction, and durability improvement; and (3) to explain machine learning, physics-informed deep learning, and AI methods and describe their significant potentials in PEM fuel cell research and development (R&D).
The presence of atmospheric brown carbon (BrC) has been the focus of many recent studies. These p... more The presence of atmospheric brown carbon (BrC) has been the focus of many recent studies. These particles, predominantly emitted from smoldering biomass burning, absorb light in the near-ultraviolet and short visible wavelengths and offset the radiative cooling effects associated with organic aerosols. Particle density dictates their transport properties and is an important parameter in climate models and aerosol instrumentation algorithms, but our knowledge of this particle property is limited, especially as functions of combustion temperature and fuel type. We measured the effective density (ρ) and optical properties of primary BrC aerosol emitted from smoldering combustion of Boreal peatlands. Energy transfer into the fuel was controlled by selectively altering the combustion ignition temperature, and we find that the particle ρ ranged from 0.85 to 1.19 g cm corresponding to ignition temperatures from 180 to 360 °C. BrC particles exhibited spherical morphology and a constant 3.0 ...
In this study, we investigate the spatial variations of discharge precipitate and cathode reactio... more In this study, we investigate the spatial variations of discharge precipitate and cathode reaction rate in lithium (Li)-air battery both theoretically and experimentally: (1) the reaction variation of local oxygen reduction reaction (ORR) rate is theoretically analyzed, with analytical solutions as a function of the Damköhler (Da) number; (2) a novel experimental method is proposed to probe local ORR rate by designing a multi-layer cathode which consists of three identical Toray® carbon clothes that have a porosity of 0.8 and a thickness of about 0.4 mm. The morphology of insoluble Li compounds at different thickness locations is uncovered by SEM images. An overall very small volume fraction of precipitates was observed in the air cathode. It is found that the local ORR rate decreases from the air side of cathode to the separator side in the case of study, which is consistent with our model predictions for two orders of the cathode reaction. The theoretical analysis and experimental...
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Papers by Bongjin Seo