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Engineering topics

Zelenay, Piotr

Publications and source records attributed to Zelenay, Piotr.

Machine learning-guided design of direct methanol fuel cells with a platinum group metal-free cathode

Direct methanol fuel cells (DMFCs) offer a promising solution for clean electricity generation, particularly in small electronics and remote auxiliary power units. However, optimizing their efficiency and performance is challenging due to the complex interactions between various factors. Here, we present a novel approach that integrates experiments with machine learning to model and predict the performance of these fuel cells using atomically dispersed platinum group metal (PGM)-free catalysts at the cathode. Further, our machine learning models, trained on diverse input parameters, allow for the comprehensive optimization of DMFC performance prior to fabrication and testing. Through extensive experimental validation, we demonstrate that this data-driven approach accurately predicts key performance metrics, such as maximum power output and polarization curves. By combining our models with interpretable game-theory methods, we provide deep insights into the factors governing fuel cell performance, ultimately paving the way for the design of scalable and efficient DMFC technologies.

25 ENERGY STORAGE↗

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling oxygen reduction activity loss mechanisms in atomically dispersed Fe–N–C electrocatalysts

Materials degradation is a major factor that limits the wider adoption of renewable and clean energy technologies. This is particularly true for the Pt group metal-free (PGM-free) atomically dispersed metal-nitrogen-carbon (M-N-C) catalysts. Here, while many experimental studies have investigated and reported the phenomenological aspects of M-N-C degradation, only a few modeling studies have considered degradation mechanisms at the atomic level. Understanding the mechanisms responsible for activity loss occurring in atomically dispersed M-N-C’s is crucial towards rationally designing active, durable, and less expensive Earth-abundant catalysts. Towards this end, we have surveyed recent literature concerning the modeling of corrosion mechanisms that impact M-N-C catalysts (Fe–N–C, in particular) and offer our own perspectives on the future direction of this field.

36 MATERIALS SCIENCE↗

Aerogel-derived nickel-iron oxide catalysts for oxygen evolution reaction in alkaline media

Anion exchange membrane water electrolyzers (AEMWEs) can generate hydrogen with a pure water feed using noble metal-free catalysts. Here, the development of highly active and stable catalysts for oxygen evolution reaction (OER) is required for improving performance of AEMWEs systems. Ni-Fe (oxy)hydroxides show high OER catalytic activity in alkaline media, but typically have low surface area. In this work, we investigate a series of Ni-Fe oxides with high surface area and disordered morphology, obtained using an aerogel synthesis method. We evaluate the impact of different synthesis variables on the OER activity and demonstrate that heat treatment at high temperatures generates more ordered structure, resulting in a decrease in OER activity. Advanced characterization reveals that maintaining highly disordered and porous structure of the aerogel is essential to achieving high OER activity, as it enables the formation of highly OER-active lamellar structures of the catalyst.

36 MATERIALS SCIENCE↗

Atomic-scale modeling of C/N kinetic stability descriptors for PGM-free electrocatalysts at finite temperatures

The durability of platinum group metal-free (PGM-free) electrocatalysts is a major barrier to their usage in polymer electrolyte fuel cell cathodes. C and N removal from active sites may play an important role in the catalyst’s ability to maintain high activity. While C degradation mechanisms are kinetically controlled, previous studies have focused on thermodynamic descriptors. In this work, we develop a temperature-dependent kinetic descriptor of C and N stability using an electron beam-damage model. Our approach considers the electron beam energy threshold (EBET) describing the knock-on displacement of C and N atoms as a stability descriptor for atomic structures. The stability of different sites is calculated to be different showing this approach can discriminate between similar sites with varied configurations. Additionally, we provide important insight regarding TEM beam damage of proposed active sites. We calculate 60 keV electrons can damage some proposed active site structures even at room temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Iron redox behavior and oxygen reduction activity of Fe-N-C electrocatalysts in different electrolytes

The iron redox behavior and oxygen reduction reaction (ORR) activity of Fe-N-C ORR electrocatalysts synthesized by a variety of techniques were investigated as a function of the identity of the electrolyte anion (bisulfate/sulfate or perchlorate) at a constant pH. In situ X-ray absorption spectroscopy data support the assignment of the redox peaks in the voltammograms to the Fe 3+ /Fe 2+ redox couple. It was found that for a given Fe-N-C catalyst, there is a correlation between the Fe redox couple peak potential and the ORR activity in perchloric acid electrolyte, but not in sulfuric acid electrolyte. While a higher Fe redox couple potential (≥ 110 mV higher) was observed in perchloric acid electrolyte, a higher ORR activity was obtained in sulfuric acid electrolyte. Here, the higher ORR activity observed in sulfuric acid than perchloric acid was correlated with the higher peak current and larger faradaic charge for the Fe redox couple. A study of the Fe redox behavior using a cavity microelectrode, eliminating the impact of ionomer, showed that the interaction of H 2 SO 4 with Fe-N-C is stronger than that of HClO 4 and that Fe redox in both electrolytes is a reversible surface electrochemical reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗

La–Sr–Co oxide catalysts for oxygen evolution reaction in anion exchange membrane water electrolyzer: The role of electrode fabrication on performance and durability

Anion exchange membrane water electrolysis is an attractive technology for low-cost generation of “green” hydrogen by combining the use of noble metal-free catalysts with pure water feed. By thus addressing main drawbacks of the liquid alkaline electrolysis and proton exchange membrane water electrolysis, anion exchange membrane water electrolysis stands an excellent chance of replacing the two technologies. The development of active and stable platinum group metal (PGM)-free catalysts for oxygen evolution reaction (OER) is crucial for making anion exchange membrane water electrolyzers (AEMWEs) practical. For this work, we synthesized, characterized and tested two La–Sr–Co oxide-based OER catalysts. First, we characterized the catalysts by XRD, SEM, and N 2 physisorption and assessed their OER activity in a three-electrode cell. Next, we focused on electrode fabrication, demonstrating the importance of catalyst-ink application to the porous transport layers (PTLs) and a key role of adding a binder to the catalyst ink to prevent the catalyst detachment from the PTL in pure water. We tested three membrane electrode assemblies prepared using different formulations of the anode catalyst ink. The results show that the optimum ink formulation is essential for the performance on pure-water feed by maximizing OH - conductivity of the catalyst layer and catalyst-membrane interface.

47 OTHER INSTRUMENTATION↗

Standardized protocols for evaluating platinum group metal-free oxygen reduction reaction electrocatalysts in polymer electrolyte fuel cells

Platinum group metal (PGM)-free electrocatalysts for the oxygen reduction reaction at the polymer electrolyte fuel cell cathode have shown substantial improvements in activity—especially those derived from transition metals, nitrogen and carbon. However, their stability and durability remain insufficient. A key to enabling future improvements and performance comparisons lies in the development of test protocols that are relevant to the operating conditions of the fuel cell cathode, can be completed within a reasonable time and are ubiquitously adopted. Here we propose and validate such protocols, designed with special attention to typical catalyst degradation mechanisms of PGM-free catalysts. The results of the cross-laboratory validation study using two different catalysts attest to the strength and feasibility of the proposed approach. We hope that the information provided here can serve as a broad and effective platform for assessing the performance and durability of PGM-free catalysts for polymer electrolyte fuel cells.

25 ENERGY STORAGE↗

Quantifying the electrochemical active site density of precious metal-free catalysts in situ in fuel cells

We report advances in the development of precious-group metal-free (PGM-free) catalysts for the oxygen reduction reaction (ORR) in fuel cell cathodes have produced active catalysts that reduce the performance gap to the incumbent Pt-based materials. However, utilization of state-of-the-art PGM-free catalysts for commercial applications is currently impeded by their relatively low durability. Methods designed to study catalyst degradation in the operation of fuel cells are therefore critical for understanding durability issues and, ultimately, their solutions. Here we report the use of Fourier-transform alternating current voltammetry as an electrochemical method for accurate quantification of the electrochemically active site density of PGM-free cathode catalysts, and to follow their degradation in situ during the operation of polymer electrolyte fuel cells. Using this method, we were able to quantify the electrochemical active site density, which will enable the elucidation of degradation mechanisms of PGM-free ORR catalysts in situ in fuel cells.

25 ENERGY STORAGE↗

Electrocatalysis in Alkaline Media and Alkaline Membrane-Based Energy Technologies

Hydrogen energy-based electrochemical energy conversion technologies offer the promise of enabling a transition of the global energy landscape from fossil fuels to renewable energy. Here, we present a comprehensive review of the fundamentals of electrocatalysis in alkaline media and applications in alkaline-based energy technologies, particularly alkaline fuel cells and water electrolyzers. Anion exchange (alkaline) membrane fuel cells (AEMFCs) enable the use of nonprecious electrocatalysts for the sluggish oxygen reduction reaction (ORR), relative to proton exchange membrane fuel cells (PEMFCs), which require Pt-based electrocatalysts. However, the hydrogen oxidation reaction (HOR) kinetics is significantly slower in alkaline media than in acidic media. Understanding these phenomena requires applying theoretical and experimental methods to unravel molecular-level thermodynamics and kinetics of hydrogen and oxygen electrocatalysis and, particularly, the proton-coupled electron transfer (PCET) process that takes place in a proton-deficient alkaline media. Extensive electrochemical and spectroscopic studies, on single-crystal Pt and metal oxides, have contributed to the development of activity descriptors, as well as the identification of the nature of active sites, and the rate-determining steps of the HOR and ORR. Among these, the structure and reactivity of interfacial water serve as key potential and pH-dependent kinetic factors that are helping elucidate the origins of the HOR and ORR activity differences in acids and bases. Additionally, deliberately modulating and controlling catalyst-support interactions have provided valuable insights for enhancing catalyst accessibility and durability during operation. The design and synthesis of highly conductive and durable alkaline membranes/ionomers have enabled AEMFCs to reach initial performance metrics equal to or higher than those of PEMFCs. We emphasize the importance of using membrane electrode assemblies (MEAs) to integrate the often separately pursued/optimized electrocatalyst/support and membranes/ionomer components. Operando/in situ methods, at multiscales, and ab initio simulations provide a mechanistic understanding of electron, ion, and mass transport at catalyst/ionomer/membrane interfaces and the necessary guidance to achieve fuel cell operation in air over thousands of hours. We hope that this Review will serve as a roadmap for advancing the scientific understanding of the fundamental factors governing electrochemical energy conversion in alkaline media with the ultimate goal of achieving ultralow Pt or precious-metal-free high-performance and durable alkaline fuel cells and related technologies.

30 DIRECT ENERGY CONVERSION↗

w19_OMEC Scientific Highlight [Slides]

Used DFT to identify likely experimental limitations for realizing high HER activity for DPA-based organic molecular electrocatalysts (OMEC) systems, directly guiding future experiments

08 HYDROGEN↗

Porphyrin Aerogel Catalysts for Oxygen Reduction Reaction in Anion-Exchange Membrane Fuel Cells

Platinum group metal (PGM)-free catalysts for oxygen reduction reaction have shown high oxygen reduction reaction activity in alkaline media. In order to further increase the power density of anion-exchange membrane fuel cells (AEMFCs), PGM-free catalysts need to have a high site density to reach high current densities. In this work, synthesis, characterization, and utilization of heat-treated iron porphyrin aerogels are reported as cathode catalysts in AEMFCs. The heat treatment effect is thoroughly studied and characterized using several techniques, and the best performing aerogel is studied in AEMFC, showing excellent performance, reaching a peak power density of 580 mW cm –2 and a limiting current density of as high as 2.0 A cm –2 , which can be considered the state-of-the-art for PGM-free based AEMFCs.

25 ENERGY STORAGE↗

Detection Technologies for Reactive Oxygen Species: Fluorescence and Electrochemical Methods and Their Applications

Reactive oxygen species (ROS) have been found in plants, mammals, and natural environmental processes. The presence of ROS in mammals has been linked to the development of severe diseases, such as diabetes, cancer, tumors, and several neurodegenerative conditions. The most common ROS involved in human health are superoxide (O 2 •-), hydrogen peroxide (H 2 O 2 ), and hydroxyl radicals (•OH). Organic and inorganic molecules have been integrated with various methods to detect and monitor ROS for understanding the effect of their presence and concentration on diseases caused by oxidative stress. Among several techniques, fluorescence and electrochemical methods have been recently developed and employed for the detection of ROS. This literature review intends to critically discuss the development of these techniques to date, as well as their application for in vitro and in vivo ROS detection regarding free-radical-related diseases. Moreover, important insights into and further steps for using fluorescence and electrochemical methods in the detection of ROS are presented.

59 BASIC BIOLOGICAL SCIENCES↗