bluuebunny/crossref_metadata_2025 huggingface dataset:
Nature's Catalyst: Investigating the Mechanisms behind Nitrogenase's N2rr Activity
Authors: Dheer Lakshay , Ablid-Pedersen Frank , Bajdich Michal
Published: August 2024

Electrochemical nitrogen reduction reaction (eNRR), one of the most studied problems in catalysis, has the potential to replace the century-old Haber-Bosch process for ammonia synthesis. However, a low-cost, highly selective and efficient catalyst for eNRR is yet to be discovered. Nitrogenase, a naturally occurring biocatalyst responsible for nitrogen conversion to ammonia under ambient conditions, is the most efficient catalyst for eNRR. The Iron-Molybdenum cofactor (FeMo-co) in the enzyme is identified as the catalytic part with bridging irons being active sites. Despite decades of work the exact mechanism of its operation and various intermediates along the pathway are still debated. We revisit eNRR on FeMo-co and decipher the key mechanisms at play.

Most studies on FeMo-co tend to ignore the magnetic nature of transition metals (TMs) in the cofactor. Proper treatment of these TMs (Fe and Mo) is necessary to pinpoint the intermediates and potential limiting step along the eNRR pathway. We start with an iterative optimization of the Hubbard U parameter to capture the correct magnetic structure of the cofactor. We also explore the effect of local chemical environment including, H-coverage and various ligands attached to the cofactor, on its activity and selectivity. The potential limiting step is found to be sensitive to the magnetic orientation of the TMs in the cofactor and it is thus imperative to provide the U correction to capture the true bottleneck of eNRR. The cofactor also shows an affinity towards a medium H-coverage under eNRR operating conditions. These findings provide a comprehensive and elaborate view of nitrogen reduction on FeMo-co and insights from this study paves the path towards designing heterogeneous counterparts to the catalyst.

Acknowledgments:

This work was supported by the U.S. Department of Energy, via Grant DE-FOA-0002676 to the SUNCAT Center for Interface Science and Catalysis.
(Invited) Analysis of Interfacial Species at Finite Bias - Calcium Borohydride in Tetrahydrofuran
Authors: Prendergast David , Matias Ana Sanz , Roncoroni Fabrice , Sundararaman Siddharth
Published: August 2024

To understand the operation of complex electrolytes we must determine which species are present and active at the interface with the electrode. We combine molecular dynamics sampling with continuum modeling to determine the speciation of Ca(BH4)2 in THF next to a model electrode (graphite). Mulitvalent ions in organic solvents with poor dielectric screening may exist in multiple coordinated states. We explore the free energy landscape associated with the interconversion of species in the bulk electrolyte using metadynamics simulations. We find that the chemical equilibrium between neutral and charged species is dominated by disproportionation following dimer formation - consistent with experimental findings. We also make use of clustering analysis to reveal distinct molecular conformations within constrained coordination states. To assess how the chemical equilibrium may be modified by the potential difference at the electrode, we develop a continuum model based on the modified Poisson-Boltzmann equation, with volume exclusion. This model also incorporates molecular-scale details through sampled free energy profiles of each relevant species within the solvent as a function of distance from the electrode. We find that a narrow (approximately 1 nm) region near the electrode, with highly variable speciation driven by potential difference, dominates the electrochemical activity of this electrolyte.
Pore-Scale Study of Diffusion and Adsorption Mechanisms during Capture of Atmospheric Carbon Dioxide
Authors: Goswami Navneet , Mukherjee Partha P. , Kang Qinjun
Published: August 2024

The surge in the global average temperatures has necessitated a decrease in the level of the released carbon dioxide (CO2) from different anthropogenic sources. In addition to curtailing the various emissions, there is a growing demand to remove the CO2 already existing in the atmosphere. As such, there is an impetus for synergistic experimental and modeling studies as it can propel the endeavor toward the development of durable and less energy-intensive CO2 capture systems. In this work, a physics-based numerical model employing the Lattice-Boltzmann Method (LBM) is formulated to simulate the coupled mass transfer and adsorption phenomena occurring during CO2 capture. A modeling workflow integrated with experiments will be presented which aids in the determination of the pertinent reaction order and adsorption rate constant based on a mixed-order kinetic model. The influence of Damköhler number, porosity, and microporosity content of the carbon fiber domain on key metrics such as the adsorption efficiencies and time constants will be further delineated.
Bubble Transport in Porous Media for Electrochemical Applications
Authors: Guo Jack , Lin Tiras Y , Seung Kansas , Davis Jonathan T.
Published: August 2024

Bubbles and their flow dynamics strongly impact the performance of gas-evolving electrochemical systems with porous electrode architectures. The presence of bubbles on the electrode surface reduces the number of active catalytic sites that are accessible for the liquid electrolyte, leading to limitations in mass transport and/or reaction kinetics. Additionally, bubbles can obstruct the flow of liquid electrolyte that is able to pass through the porous structure, leading to pressure buildup. Therefore, to mitigate bubble blockage, optimal electrolyzer performance requires understanding bubble dynamics within the porous electrode in the presence of an applied flow; an accurate and complete physical model of this setup is not yet available. Here, we present volume-of-fluid simulation results and a theoretical framework to describe the bubble/electrolyte/electrode interaction, i.e. the triple phase boundary, ultimately with an aim to predict whether the bubble does or does not break through the porous media. Informed by the numerical results, the constructed theory describes the interaction of buoyancy, surface tension, and pressure drop for the range of different porosities, bubble sizes, and electrolyte flow rates. Comparison of these results with experimental findings are discussed. This work serves as a first step in building the framework for the design and optimization of relevant porous media systems that aim towards the improved control of bubble dynamics.

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL release number: LLNL-ABS-857509.
Towards Safer Li-Ion Batteries: A Study on Electrolyte Solvation and Dynamics with the Incorporation of Low Volatility Co-Solvents
Authors: Teeraburanapong Siriporn , Kasemchainan Jitti , Suttipong Manaswee
Published: August 2024

Molecular dynamics (MD) simulations were employed to investigate how the content and type of co-solvents influence the solvation structure and transport properties of lithium ions (Li+) in electrolytes. Our focus was on lithium hexafluorophosphate (LiPF6) at a concentration of 1.0 M in a carbonate-based solvent composed of ethylene carbonate (EC) and dimethyl carbonate (DMC) with a 1:1 mixing ratio. Low-volatility co-solvents, including tetramethylene sulfone (TMS), dimethyl sulfoxide (DMSO), fluoroethylene carbonate (FEC), and succinonitrile (SN), were introduced into the electrolytic matrix at concentrations of 0, 10, 25, 50, 75, and 100 wt.%. Li+ dynamics were notably influenced by these factors. The highest Li+ transference number was observed at a 25 wt.% concentration for each co-solvent, particularly with 25 wt.% DMSO, resulting in the highest ionic conductivity (14.13 mS/cm) and Li+ transference number (0.47). In this system, the PF6
- anion refrains from joining the initial solvation shell of Li+. This is attributed to the higher donor number of DMSO compared to TMS, FEC, and SN, leading to a weakening of electrostatic interactions. These findings advance our comprehension of electrochemical principles in bulk electrolytes, providing insights for designing safer and more efficient lithium-ion batteries.
Enhancing Microkinetic Modeling for CO2 Reduction Reaction: Integrating Electrolyte Effects
Authors: Cho Ara , Ablid-Pedersen Frank , Bajdich Michal
Published: August 2024

In the current landscape of escalating global environmental challenges, the development of sustainable energy solutions has become increasingly critical. A pivotal area in this endeavor is the carbon dioxide reduction reaction (CO2RR) technology, which holds the promise of converting CO2, a major greenhouse gas, into valuable chemicals and fuels. The intricate nature of CO2RR, characterized by complex reaction pathways and a plethora of intermediates, presents significant scientific and engineering challenges. Key to surmounting these challenges is the accurate and comprehensive modeling of CO2RR processes. However, traditional computational models often overlook a crucial aspect – the influence of electrolyte interactions with CO2RR intermediates. This omission leads to models that inadequately capture the true dynamics of the electrochemical environment, resulting in less accurate predictions. In this work, we introduce CatEnergy, a Python module that enhances our existing microkinetic modeling tool, CatMAP[1], focusing on CO2RR. CatEnergy specifically addresses the complexity of CO2RR by integrating electrolyte interaction data. This integration enables a more accurate representation of the electrochemical environment, improving the predictive power and efficacy of CO2RR models. By generating essential electrolyte interaction data for microkinetic modeling, it facilitates more effective catalyst design and optimization of reaction conditions. This development is key in advancing the accuracy of microkinetic modeling for CO2RR and underscores our commitment to sophisticated tool development in sustainable energy research. [1] Medford, A. J. et al. CatMAP: A Software Package for Descriptor-Based Microkinetic Mapping of Catalytic Trends. Catal. Lett.
145, 794–807 (2015).
Computational Modeling and Machine Learning Approaches for Accelerated Materials Design
Authors: Matanovic Ivana , Davis Megan Christina , Kort-Kamp Wilton , Holby Edward F. , Klein Jeffrey Michael , Leonard Daniel P , Kim Yu Seung , Zelenay Piotr
Published: August 2024

A substantial part of research in energy storage and conversion systems concerns the discovery and characterization of novel materials with improved performance, but most advancements are still generally attributed to costly and time-consuming trial-and-error experimentation. Computational chemistry methods combined with machine learning techniques offer paradigm shift in how materials are fundamentally understood and designed. Namely, high-throughput calculations combined with machine learning can help evaluate different properties of complex materials and efficiently screen millions of candidates to identify the ones with improved targeted properties, such as higher activity and selectivity and/or enhanced durability.

In this talk we will first illustrate the use of density functional theory (DFT) in the design of fuel cell and electrolyzer ionomers. More specifically, we will discuss how simple descriptors such as DFT-calculated adsorption energies and adsorption modes of polymer fragments can be used to guide the rational design of ionomers for anion exchange membrane fuel cells and alkaline membrane water electrolyzers. Our design principle has led to the synthesis of new polymers, e.g., poly(fluorene) and polynorbornene-based ionomers, with weak adsorption on the electrocatalyst surface and improved hydrogen oxidation reaction activity. We will further introduce the computational workflow that integrates high-throughput DFT calculations with machine learning with a goal of designing new amine-based CO2 adsorbents, as well as platinum group metal-free electrocatalysts for conversion of CO2 to value added products. In our workflow we use descriptors together with DFT-calculated binding energetics to train artificial neural networks for activity prediction. Our trained machine learning models are then used to screen millions of candidate chemistries and identify the ones with optimal activity. Descriptor importance evaluation provides additional design principles based on the structure to property relationships for the synthesis of targeted materials for CO2 capture and electro-conversion.
Automated Upscaling Via Symbolic Computing for Thermal Runaway Analysis in Li-Ion Battery Modules
Authors: Pietrzyk Kyle , Bucci Giovanna , Behandish Morad , Battiato Ilenia
Published: August 2024

Despite the availability of advanced numerical capabilities and computational power, complex multi-physical, multiscale systems continue to challenge modeling efforts due to their elusive behaviors and nontrivial couplings. High-fidelity simulations have paved the way for simulating such systems, but the associated computational costs prohibit such tools from being used in iterative routines for engineering design and optimization. While numerical strategies for accelerating complex at-scale multi-physical simulations exist, they often concede predictive accuracy and lack rigorous justification. Alternatively, methods for developing rigorous multiscale models (e.g., upscaling techniques) offer a priori modeling error guarantees, but are primarily used in academic settings due to their requirements in time and specialized expertise for handling analytically intractable derivations. In our previous work, we developed an automated upscaling engine, Symbolica, that uses symbolic computation to avoid these overheads and rapidly develop multiscale models via rigorous homogenization theory. In this work, we extend Symbolica’s model development capabilities to accommodate multi-domain structures and demonstrate Symbolica’s generality in model development by applying it to a real-world problem; namely, to analyze thermal runaway in Li-ion battery modules. We obtain homogenized models that capture the sharp spatiotemporal gradients associated with thermal runaway to within the guaranteed modeling error. Upon numerically validating the models, we demonstrate how Symbolica can be used to reduce the level of effort in rigorous multiscale modeling and model implementation for real-world applications.

Figure 1
(Invited) First Principles and Thermodynamics Modeling of Battery Materials and Electrocatalysts in Aqueous Settings: The Search for Sustainable and Functional Nanomaterials
Authors: Mason Sara Elizabeth
Published: August 2024

Electrochemical modeling of processes at the solid-aqueous solution interface poses inherent challenges owing to structural complexity, heterogeneity, and redox chemistry. The first-principles methods that can reliably predict materials properties are not compatible with the macroscopic electrochemical driving forces of concentration, pH, and applied potential. The ability to partition overall reactions into elementary steps enables a modeling strategy that uses electronic structure calculations combined with information from thermodynamics, statistical mechanics, and electrochemical principles. The "DFT + Thermodynamics" approach is discussed and demonstrated for electrochemical systems. First, we discuss a body of work comprised of modeling, synthesis, characterization, analytical measurements, and biological studies of the Li(NixMnyCo1-x-y)O2 ("NMC") family of materials. NMC is a technologically relevant complex metal oxide used in rechargeable Li-ion battery technology, with projected increased use and demand. A lagging consequence of the growing demand of NMC is the (slower growing yet increasing) amount of end-of-life battery materials entering permanent waste disposal. Environmental exposure results in leaching of toxic metals, in particular nickel and cobalt. It was shown experimentally that equistoichiometric NMC undergoes incongruent metal release in water, resulting in Mn-enriched materials after long periods of exposure. DFT + Thermodynamics modeling captures the incongruent trend, and provides an interpretation based on the interplay of metal oxidation states, coordination environment, and thermodynamically preferred aqueous speciation. The results are extended to Mn- and Ni-rich variations of NMC in compositional tuning studies. In subsequent work, it is shown that variations in the aqueous media can go on to further govern metal release, again with strong correlation between theory and experiment. In separate work, we model transition metal phosphides as promising electrocatalysts for HER. Here, the ability of DFT + Thermodynamics to predict how the surface structure evolves as a function of pH and U is essential to understanding the reactive sites and HER mechanisms.
Shape Optimization for Lithium-Ion Battery with Porous Electrodes
Authors: Li Hanyu , Barrera Jorge-Luis , Roy Thomas
Published: August 2024

In this presentation, we introduce a gradient-based shape optimization framework to design porous electrodes for maximum energy storage. Lithium-ion batteries are becoming an increasingly important energy source and storage device. Large surface area that advocates high reaction rates often leads to small porosities that deteriorate electrochemical transport, which significantly restricts ion penetration depth, limiting the material utilization in planar electrodes. Consequently, architected electrodes are required to optimize performance.

We consider a model with two materials, namely porous electrode and pure electrolyte. Density-based topology optimization with continuous material volume fraction has previously been implemented on lithium-ion battery system for both half-cell and full-cell model to maximizes its energy storage. Despite the capability of producing complex interdigitated structures, an appropriate penalization scheme for intermediate materials is required for the optimizer to provide near binary designs. Setting up such a penalization is often time-consuming due to the large number of design-dependent variables that affect the forward model differently. Alternatively, the shape optimization approach used in this work produces binary designs naturally by morphing conformal meshes, circumventing inaccuracies associated with fuzzy interfaces. Shape sensitivities are computed via the adjoint method and leveraging automatic differentiation. The optimization problem is solved using a nonlinear programming technique.

In this presentation, we perform shape optimization on a half-cell model to maximize its energy storage when a fixed charging current is applied. We study multiple arrangements of physical parameters and compare their performance against a monolithic electrode. Both 2D and 3D results are presented.
Quantifying Electrolyte Variation through Coupled Molecular Dynamics and Porous Electrode Modeling of Lithium-Ion Battery Cells
Authors: Dix Sean T. , Lowe Jeffrey , Rashvand Avei Mehdi , Garrick Taylor R.
Published: August 2024

Lithium-ion battery cell modeling using physics-based approaches such as porous electrode theory is a powerful tool for battery design and performance analysis both at the beginning and end of life[1]. Cell metrics such as resistance and thermal performance[2-6] can be quickly calculated in a pseudo-two-dimensional (P2D) framework. For engineering of electric vehicle batteries, speed and fidelity of electrochemical models is paramount in a competitive landscape. Physics-based models[7, 8] allow for high fidelity but require detailed knowledge of the cell component material properties. Acquiring these material characteristics typically requires time-consuming and expensive experiments limiting the ability to quickly screen through cell designs. One approach to circumvent costly experiments is to use molecular dynamics[9, 10] to calculate electrolyte transport properties. We demonstrate how cell modeling using simulated transport properties enables predictions of cell level metrics, allowing for experiment-free component screening. We also show how the variation in transport property predictions from molecular dynamics affects the final cell level performance predictions.

References

1. U. Janakiraman, T. R. Garrick and M. E. Fortier, J Electrochem Soc, 167, 160552 (2020).

2. Y. Hu, S.-Y. Choe and T. R. Garrick, Electrochim Acta, 362, 137124 (2020).

3. M. Song, Y. Hu, S.-Y. Choe and T. R. Garrick, J Electrochem Soc, 167, 120503 (2020).

4. Y. Hu, S.-Y. Choe and T. R. Garrick, Applied Thermal Engineering, 189, 116709 (2021).

5. Y. Hu, S.-Y. Choe and T. R. Garrick, J Power Sources, 532, 231350 (2022).

6. M. Song, Y. Hu, S.-Y. Choe and T. R. Garrick, J Electrochem Soc, 169, 070502 (2022).

7. T. R. Garrick, J. Gao, X. Yang and B. J. Koch, J Electrochem Soc, 168, 010530 (2021).

8. J. S. Lopata, T. R. Garrick, F. Wang, H. Zhang, Y. Zeng and S. Shimpalee, J.
Electrochem. Soc., 170 (1) 020530 (2023)

9. S. T. Dix, J. S. Lowe, M. R. Avei and T. R. Garrick, J Electrochem Soc, 170, 083503 (2023).

10. T. R. Garrick, Y. Zeng, J. B. Siegel, and V. R. Subramanian, J. Electrochem. Soc., 170 113502 (2023)
Effect of Metal Work Function on Electron Transfer Kinetics in Electrochemical Reactions
Authors: Buckley D. Noel , Leddy Johna
Published: August 2024

The longstanding problem of explaining the observed dependence of the kinetic rates of electrochemical reactions on the work function of the electrode material (metal) is revisited, based on a recent paper.1 It was proposed that this dependence could be explained in terms of the effect of the work function of the metal on the free energies of activation of the forward and backward electron transfer reactions. In this presentation, we will explore details of the proposed mechanism.

In essence, the mechanism is based on the effect of work function on the Galvani potential of the metal at any given applied potential. Even though the total electron energy (Fermi level) of an electron in the electrode must be the same, regardless of the metal, when it is at equilibrium with a given electrolyte, the manner in which that energy is partitioned between the effect of work function and the effect of potential is significantly different for different electrode materials. A higher work function leads to more stabilization of an electron in the metal (lower free energy) and, since the total free energy must remain the same, this lower free energy due to work function must be compensated by a more negative Galvani potential.

The classical analysis of the effect of a more negative potential is based on the theory that a change in potential has a greater effect on the initial (reactant) free energy than it does on the free energy of the transition state. Consequently, the activation energy of the forward (cathodic) reaction is decreased by some fraction α of the corresponding increase in electron energy in the metal. This type of analysis is generally used to quantify the effect of changes in applied voltage and derive current-voltage relationships. In this paper we extend the analysis to take account of changes in the (Galvani) potential ϕm of the metal due to changes in work function Φm.

It is reasonable to assume that a change in ϕm will have a similar effect whether it occurs due to a change in applied voltage or due to a change in the work function of the metal. This implies that an increase in work function with a corresponding negative shift in Galvani potential can lead to a lowering of activation energy and so to faster kinetics. However, we must also consider a possible change in activation energy arising from the decreased electron energy (increased stabilization) due to higher work function. If this caused a change in activation energy it would be expected to be in the opposite direction to the change due to Galvani potential, since it would be expected to lower the initial free energy by a greater amount than that of the transition state.

The presentation will consider in detail the interplay of these effects and the consequent implications for modelling electrode kinetics.

K. S. R. Dadallagei, D. L. Parr IV, J. R. Coduto, A. Lazicki, S. DeBie, C. D. Haas, and J. Leddy, J. Electrochem.
Soc.
170, 086508 (2023)
Origin of Stability and Activity Enhancements in Pt-Based Oxygen Reduction Reaction Catalysts Via Defect-Mediated Dopant Adsorption
Authors: Sawant Kaustubh NMI , Zeng Zhenhua , Greeley Jeffrey
Published: August 2024

Platinum alloys are highly efficient electrocatalysts for the oxygen reduction reaction (ORR) in acidic conditions. However, these alloys are susceptible to metal loss through leaching and degradation, leading to reduced catalyst stability and activity. Recently, it has been shown that doping with oxophilic elements can significantly alleviate these problems, with a prominent example being Mo-doped Pt alloys. Here, to achieve atomic scale understanding of the exceptional activity and stability of these alloys, we present a detailed density functional theory description of the dopants’ structures and impact on electrocatalyst properties. Beginning with the Mo/Pt system, we demonstrate that Mo can be stabilized in the form of low-dimensional oxyhydroxide moieties on Pt defects. The resulting structures enhance stability and activity via distinct physical processes, with the Mo moieties both directly inhibiting Pt dissolution at defects and indirectly enhancing ORR activity by generation of strain fields on surrounding Pt terraces. We then generalize these analyses to other metal dopant elements, and we demonstrate that similar low-dimensional oxyhydroxide structures control the electrocatalytic properties through an intricate interplay of the structures’ acid stability, intrinsic activity for the ORR, and ability to induce ORR-promoting strain fields on Pt.

Reference:

Sawant, K., Zeng, Z. & Greeley, J., Angew. Chem., Int. Ed., 10.1002/anie.202312747
The Impact of Carbon Corrosion Towards Oxygen Reduction Reaction Activity on Atomically Dispersed M-N-C Catalysts
Authors: Li Sirui , Kort-Kamp Wilton , Holby Edward F. , Zelenay Piotr
Published: August 2024

Atomically dispersed Pt group metal free (PGM free) M-N-C catalysts offer a promising pathway towards a clean energy future.1 This class of materials has proven to be a viable substitute for commercial Pt/C to catalyze oxygen reduction reaction (ORR) with similar activity at only a fraction of the raw material cost.2 To gain a wider market adoption, however, M-N-C catalysts need to significantly improve its durability compared to Pt and its alloys in a real-world operating condition. Towards this end, substantial efforts have focused on making more durable M-N-C catalysts while simultaneously maintaining and improving its ORR activity.3,4 As part of the effort to understand the fundamental aspects that control M-N-C catalysts’ durability during ORR condition, we employ a combined approach using first principles density functional theory (DFT) and density functional tight binding theory (DFTB) to identify the impact of carbon corrosion occurring on M-N-C catalyst towards ORR activity. Our starting atomic representation of the ORR active site is the “C10” type local structure composed of FeN4C10 local defect5 embedded in a monolayer graphene support of varying cell size. As carbon corrosion occurs and consequently creating local carbon vacancies surrounding the active site, we then obtain a family of FeN4C11 and FeN4C12 type of local structures. Our DFT calculations of OH binding energy on these corrosion derived structures suggest that the presence of C vacancies and the subsequent H passivation on dangling C introduces elastic structural deformation to various degree that decreases the theoretical ORR limiting potential. This decrease in DFT calculated ORR limiting potential across a family of FeN4C10, FeN4C11, and FeN4C12 local structures can be attributed to a mechanical energy arising from the surface reconstructions.

Reference

D. A. Cullen et al., Nat Energy, 6, 462–474 (2021).

G. Wu, K. L. More, C. M. Johnston, and P. Zelenay, Science, 332, 443–447 (2011).

E. F. Holby, G. Wang, and P. Zelenay, ACS Catal., 10, 14527–14539 (2020).

T. Patniboon and H. A. Hansen, ACS Catal., 11, 13102–13118 (2021).

H. T. Chung et al., Science, 357, 479–484 (2017).
Modeling of Fluidized Bed Molten Carbonate Direct Carbon Fuel Cell: Effect of Reverse Boudouard Reaction
Authors: Suarez Errol John Elizondo , Ortenero Joseph Rempillo
Published: August 2024

Direct carbon fuel cells (DCFCs) are an alternative technology to coal-fired power plants for converting the chemical energy of abundant carbon-rich fuel into electrical energy. DCFCs have higher electrical efficiency and lower greenhouse emissions, which are easier to separate and capture. In the transition to renewable sources of energy, efficient and low-emission technologies need to be explored. Since DCFC technologies are in their early stages of development, modeling and simulation studies are needed to reduce costs and aid in experimental design. In this study, an electrochemical and transport model for a fluidized bed molten carbonate DCFC (FBMCDCFC) is developed. The performance of the fuel cell is evaluated through the polarization losses. This study expounds on recent developments in DCFCs by considering the effect of the reverse Boudouard reaction and the 2-electron oxidation of CO alongside the 4-electron oxidation of carbon at higher temperatures. The electrolyte used is a 62 : 38 mol % Li2CO3/K2CO3 eutectic mixture, while the fuel is activated carbon impregnated by HNO3. The results show that the greatest polarization losses for the FBMCDCFC are from anode activation overpotential and ohmic overpotential. The cathode activation and concentration overpotentials are relatively small. Increasing the reaction temperature results in a greater decrease in anode activation overpotential than ohmic overpotential, despite the increase in CO formation from the reverse Boudouard reaction. The peak power density of the FBMCDCFC is 434.437 W m-2 when operated at 923 K and a gas flow rate of 30 mL min-1. The peak power density of the FBMCDCFC is greater with higher temperatures, where the peak increases to 584.802 W m-2 when operated at 1023 K. The peak power density is greater with lower gas flow rates, where the peak increases to 458.175 W m-2 at a gas flow rate of 25 mL min-1. The mathematical model can aid in optimizing the performance of FBMCDCFCs, such as how increasing the operating temperature favorably increases anode reaction kinetics and reduces ohmic resistances in the cell. Future work will focus on improving the model correlations to close the gap between the results of modeling and actual experiments.

Figure 1. a) Power curves at different temperatures, 823 K to 1323 K (30 mL min-1 flow rate, 1 atm total pressure); b) Power curves at different gas (O2 and CO2) flow rates (923 K, 1 atm total pressure)

Figure 1
Finite Difference Model of Substrate Channeling in TCA Cycle Enzymes
Authors: Wark Christina , Xie Yan , Calabrese Barton Scott
Published: August 2024

The Tricarboxylic Acid (TCA) cycle is a highly optimized metabolic pathway. Of particular interest in the TCA cycle is the malate dehydrogenase—citrate synthase (MDH-CS) complex, which accomplishes citrate production from malate with an oxaloacetate intermediate. This complex was studied experimentally by Bulutoglu et al, who showed that mutation of positively-charged residues on the complex surface effected the dynamic response of citrate production as measured by lag time experiments.1 More recently, we have created a Markov State model that was used to predict the transfer efficiency of each complex and determine the reaction pathways on the surface.2

Utilizing the kinetic parameters of both the recombinant and mutant complexes determined experimentally1and Markov state transition matrix produced by previous modeling2, we report a finite difference model to calculate time trajectories of the surface and bulk occupancies by OAA. Solution of a system of differential mass balance equations, based on the transient matrix, provide the occupancy probability at each node in the network. The lag time of MDH-CS was determined computationally to be comparable to experiment for both the recombinant and mutant complex with lag times of 0.44 and 2.1 seconds, respectively.1 Using the model, the dynamics of each of the four possible reaction pathways between the the two source (MDH) active sites and the two sink (CS) sites could be studied independently. This analysis provides a dynamic model for intermediate transport in an electrostatically channeled system, and can be used as a predictive tool to provide mechanistic insight into pathway dominance. We gratefully acknowledge support from the Army Research Oﬃce MURI (#W911NF1410263) via The University of Utah.

References

B. Bulutoglu, K. E. Garcia, F. Wu, S. D. Minteer, and S. Banta, ACS Chemical Biology,
11, 2847–53 (2016). doi:10.1021/acschembio.6b00523

Y. Xie, S. D. Minteer, S. Banta, and S. Calabrese Barton, ACS Nanoscience Au, 2, 414-421 (2022). doi:10.1021/acsnanoscienceau.2c00011

Figure 1
(Invited) Operando Nanoimaging of Phase Transformations in Energy Storage Materials
Authors: Singer Andrej
Published: August 2024

We applied operando Bragg Coherent Diffractive Imaging (BCDI) to study the discontinuous phase transformation in LixNi0.5Mn1.5O4 embedded in a fully operational battery. During Li-intercalation, we observed nucleation and growth of the Li-rich phase in a 500 nm particle embedded in the multicomponent positive electrode. The data captures the evolution from a curved coherent to planar semi-coherent interface, driven by dislocation dynamics. These dislocations travel with the interface and are expelled upon the completion of the phase transformation, resulting in a crystal devoid of defects. We hypothesize that these defects move via glissile motion without diffusion of host ions. Our data indicate the absence of significant kinetic limitations affecting the transformation kinetics, even under rapid discharge within 2 hours. This study underscores the capability of BCDI as a powerful tool for operando analysis of nanoscale phase transformations, offering guidance for the design and optimization of electrochemical materials.
Novel Fast-X-Ray Reflectivity Setup for Studying Electrochemical Interfaces
Authors: Corts Wieland , Ge Xiaokun , Matar Toka , Steinruck Hans-Georg , Frücht Sebastian , Bertram Florian , Lippmann Milena
Published: August 2024

A fundamental understanding of atomic scale processes occurring at electrochemical interfaces is crucial for advancing the development of energy-related electrochemical systems such as ion batteries or fuel cells. For this purpose, operando experiments are imperative. X-ray reflectivity (XRR) is a non-destructive technique that enables operando analysis of buried structures with atomic resolution [1,2]. However, the time-resolution of typical XRR setups of minutes per XRR scan is limited by diffractometer motor motion and detector read-out times; this resolution is in many cases too slow to observe interfacial electrochemical phenomena [1,2].

To overcome these limitations, we developed a novel fast-XRR setup, which employs a fast quasi-continuous rotation stage in combination with a stationary, high frame rate area detector. With this setup, the sample can be rotated with a frequency of up to 10 Hz, yielding sub-second time resolution for an individual XRR scan. In contrast to complementary fast-XRR setups [3,4], the presented setup can easily be combined with complex sample environments, as typically required for the investigation of electrochemical interfaces.

We present first fast-XRR results obtained at PETRA III beamline P08 at DESY using 18 keV and a Dectris Eiger1M detector. We reached a time resolution below one second for an incident angular range between 0° – 6° (≙ 0 – 2 Å-1, i.e., covering the Fresnel XRR range). We measured several multilayer samples (e.g., 2 nm Ti / 20 nm Au coating on a Si substrate) and benchmarked the results to “standard” XRR measurements, where the measurements took several minutes. We find good agreement and conclude, that our novel setup provides significant XRR data within less than one second, demonstrating its usability for operando XRR measurements.

Literature:

[1] C. Cao, H.-G. Steinrück, Encyclopedia of Solid-Liquid Interfaces, 391–416, Elsevier, 2024.

[2] C. Cao, H.-G. Steinrück et al., Nano Letters, 16, 12, 7394–7401, 2016.

[3] M. Lippmann et al. Review of Scientific Instruments, 87, 113904, 2016.

[4] H. Jorres et al., Applied Physics Letters, 114, 081904, 2019.
Investigation of 40 Ah Prismatic Batteries Operating Under Fast-Charge Conditions Using Operando Synchrotron XRD Technique
Authors: Alrifai Bouthayna , Vincent Remi , Mirolo Marta , Jacquet Quentin , Charbonnel Juliette , Genies Sylvie , Daniel Lise
Published: August 2024

The pressing challenges posed by the energy crisis and the impact of climate change have forced a gradual replacement of traditional internal combustion engine (ICE) automobile powertrains with electrochemical energy storage devices. However, a boost of the electric vehicles (EVs) market, by significant battery performance enhancements are consistently required, primarily due to numerous persistent concerns. One of the key features targeted by battery and EVs industries is the rapid charging capability, making EVs more competitive with the quick refueling of traditional gasoline vehicles. Notably, despite the clear benefits of fast charging technology, the accelerated battery degradation after fast and extreme fast charging raises on top of the drawbacks of this technology. Therefore, understanding of heterogeneity and structural transformations within battery systems is of high interest.

In this regard, we attempt to investigate the structural properties of a LiNi1/3Mn1/3Co1/3O2 (NMC111) /graphite fresh industrial prismatic cell using synchrotron XRD under fast charge conditions. The investigated battery is a PHEV cell with an experimental capacity of 40 Ah. It was taken from a range rover vehicle pack after being disassembled. The evolution of the composite anode and cathode structures was followed by operando wide-angle X-ray scattering (WAXS). Using this approach, we were able to measure and quantify the different phases of graphite and NMC111 lithiation/delithiation at various potentials by analyzing the corresponding Bragg peaks. By that, we were able to detect some heterogeneities in the degree of lithiation/delithiation within the cell upon charge. In addition, a comparison between a fresh cell and another aged cell, with a state of health (SOH) of 88%, was made in order to investigate the effect of aging under fast charging conditions on the performance of the industrial LIBs.
Operando X-Ray Scattering for Electrocatalysis and Beyond
Authors: Ennaji Meryem , Gasmi Amir , Amigues Simon , Jones Deborah J. , Jaouen Frederic , Drnec Jakub , Chattot Raphael
Published: August 2024

The energy transition stands as one of the greatest challenges of today’s society. In this context, electrocatalyst materials at the heart of electrochemical energy conversion devices such as fuel cells and water electrolyzers are expected to play an increasing crucial role in the near future. The urgent bottleneck to be overcome in electrocatalyst materials development to allow the widespread deployment of electrochemical systems is thus reaching combined high activity and long-term stability at low cost. Despite the diversity in electrocatalyst materials, the latter being largely imposed by the various types of electrochemical systems (noble vs. non-noble metals in acidic vs. alkaline media for example) and the prerequisites of the different electrochemical processes (oxidation or reduction reactions of various species at different electrode potential ranges), most activity and stability properties of electrocatalysts directly derive from their (surface) chemistry and structure [1]. Such properties (and their temporal evolution) can thus be directly investigated by means of in situ or operando high energy X-ray scattering (XRD) technique [2].

In this presentation, the versatility of in situ and operando XRD technique in addressing key bottlenecks in electrocatalyst materials development, notably by probing adsorption and oxidation trends [3], will be showcased. After an overview of previous contributions from the literature, the talk will focus on our ongoing works which encompass the study of Pt-based nanocatalysts for the oxygen reduction reaction (ORR) at proton-exchange membrane fuel cells (PEMFCs) anode, carbon-capped Ni@C catalyst for the hydrogen oxidation reaction (HOR) at anion-exchange membrane fuel cells (AEMFCs) anode and IrCu unsupported aerogel catalyst for the oxygen evolution reaction (OER) at proton-exchange membrane water electrolyzers (PEMWEs) anode.

Finally, the ability of operando XRD to provide device-relevant insights at the macroscale (such as ionomer hydration in PEMFCs or water distribution in AEMFCs) beyond electrocatalysts microstructural properties will be presented. References

[1] Z. W. Seh, J. Kibsgaard, C. F. Dickens, I. Chorkendorff, J. K. Nørskov, and T. F. Jaramillo. Combining theory and experiment in electrocatalysis: Insights into materials design. Science, 355(6321): eaad4998, 2017.

[2] Magnussen, O. M., Qiu, C., Drnec, J., Martens, I., Jared Huang, J., Chattot, R., & Singer, A. (2023). In situ and operando X-ray scattering methods in electrochemistry and electrocatalysis. Chemical Reviews, Accepted.

[3] Chattot, R., Martens, I., Mirolo, M., Ronovsky, M., Russello, F., Isern, H., Braesch, G., Hornberge, E., Strasser, P., Sibert, E., Chatenet, M., Honkimäki, V., Drnec, J. (2021). Journal of the American Chemical Society, 1, 17068-17078.
Operando X-Ray Absorption Spectroscopy Characterization of Ir Catalyst Dynamics in a Realistic Proton Exchange Membrane Water Electrolyzer
Authors: Hannagan Ryan T. , Hersbach Thomas J. P. , Weker Johanna Nelson , Nielander Adam C. , Stevens Michaela Burke , Sokaras Dimosthenis , Jaramillo Thomas F.
Published: August 2024

Water electrolysis powered by renewable energy is a promising technology which can produce green H2 with no direct CO2 emissions. The US Department of Energy has set an ambitious target to bring down the cost of green H2 to $1 per kg within the next decade. To drive the innovation required to meet this target, it is essential we understand catalyst behavior in realistic zero gap membrane based electrolyzers operating at industrially relevant current densities. Towards this goal, we have developed methodologies for conducting high-resolution X-ray absorption spectroscopy at current densities of 2 A cm-2 in a synchrotron-compatible electrolyzer. This innovation enabled us to track dynamic changes in Ir oxidation during sustained operation of a realistic proton exchange membrane water electrolyzer (PEMWE). The hardware and techniques developed are also widely applicable to other types of electrolyzers and fuel cells.
Approaching the Multiphase Interface of Ir-Based PEM Electrolyzers Using Operando ‘Tender’ X-Ray AP-XPS
Authors: Hamlyn Rebecca , Crumlin Ethan J.
Published: August 2024

Electrochemical water splitting is a promising pathway for the renewable production of hydrogen as an alternative fuel and chemical feedstock. Yet, the process is plagued by slow kinetics of the essential oxygen evolution reaction at the anode. Further, large-scale hydrogen production from such devices will require reduced platinum group metal (PGM) loadings (often iridium-based anodes) and/or new materials due to factors such as PGM scarcity, cost and loss during operation. In the hopes of enabling progress of rational design for OER catalysts, effective characterization of the electrode-liquid interface is crucial. Synchrotron-based X-ray Photoelectron Spectroscopy (XPS) offers a versatile way to obtain surface chemical and elemental characterization of these materials. The use of X-rays in the ‘tender’ regime (~2-6 keV) allows for deeper probing than the conventional ‘soft’ x-ray (< 2000 eV) set up that is common at synchrotrons and lab-based sources. The photoelectrons generated from tender x-rays have enough energy to penetrate tens of nanometers through low density components such as a layer of liquid or polymeric electrolyte. This opens the door to access the chemistry at the interface of liquid and ionomer electrolyte-electrocatalyst materials. With the use of a fully operational two-electrode system, we are able to study these membrane electrode assemblies under active water splitting conditions.

My talk will explain our specific approach, which is often crucial for successful collection of accurate data, highlighting elements of cell design and experimental setup that are helpful for this process. I will also show recent AP-XPS results on iridium-based polymer electrolyte membranes for water splitting. With application of elevated potential, we can correlate the iridium valency and surface species with the appearance of product traces in a mass spectrum.

Figure 1
(Invited) In Situ x-Ray Diffraction Studies of the Atomic Structure and Charge Distribution at the Electrochemical Interface
Authors: Grunder Yvonne , Lucas Christopher A , Joly Yves , Soldo-Olivier Yvonne
Published: August 2024

The presence of specifically adsorbed anions can significantly affect the electrochemical reactivity of a metal electrode which is of major interest for galvanic deposition, etching, corrosion and electrocatalysis. In-situ surface x-ray diffraction has enabled an atomic/molecular-level understanding of the interface under reactive conditions, including its potential and time dependence, to be developed. While information about the atomic structure of the electrode surface in electrochemical in-situ cells has been widely investigated, insight into the charge distribution and the structure of the electrolyte at the interface is still lacking. Advances in these directions offer possibilities in elucidating atomic scale models of the electrochemical interface and thus will help to establish structure-stability-reactivity relationships.

A fundamental understanding of the nature of the charge transfer, especially the influence of the applied potential and the screening by the electrolyte, is a major goal in electrochemistry to better understand electrochemical processes and charge transfer during adsorption and deposition. [1]

Thus, combining x-ray spectroscopy and x-ray diffraction to gain site specific information about the charge distribution at buried interfaces is a promising tool. [2,3]

Examples of how the use of surface x-ray scattering techniques can help to characterize electrochemical interfaces in-situ in order to link, structure, reactivity and stability will be presented. [4-5] Advances in these directions offer possibilities in elucidating atomic scale models of the electrochemical interface and thus will help to establish structure-stability-reactivity relationships and to understand growth kinetics and electrochemical phase formation.

References:

[1] Y. Gründer and C. A. Lucas, Nano Energy 29, 378 (2016).

[2] Y. Gründer, P. Thompson, A. Brownrigg, M. Darlington, and C. A. Lucas, Journal of Physical Chemistry C 116, 6283 (2012).

[3] Y. Joly et al., Journal of Chemical Theory and Computation 14, 973 (2018).

[4] Y. Grunder et al., Charge Reorganization at the Adsorbate Covered Electrode Surface Probed through in Situ Resonant X-ray Diffraction Combined with ab Initio Modeling; Phys. Chem. C 2022, 126, 9, 4612–4619

[5] Yvonne Soldo-Olivier et al., Unraveling the Charge Distribution at the Metal-Electrolyte Interface Coupling in Situ Surface Resonant X-Ray Diffraction with Ab Initio Calculations, ACS Catal. 2022, 12, 4, 2375–2380