Journal Of Physical Chemistry Research Articles

Redox Behavior of Arsenic (III) and Copper (II) Mixtures on Ultraflat Au (111) Thin Film Electrodes

The electrochemical behavior of arsenic on gold (Au) electrodes surfaces is of great interest as As is well-recognized as a highly toxic and relatively ubiquitous ground water species. The United States Environmental Protection Agency (USEPA) and World Health Organization (WHO) drinking water standards for arsenic are 10 PPB, or 𝜇g L-1 [1]. These minute ion concentrations necessitate the use of analytical methods with high sensitivity and a low susceptibility to cross interferences. Electrochemical stripping voltammetry is a well-established electroanalytical method for arsenic ions [2]. Polycrystalline gold electrodes are often used due to their high redox stability and relatively low overpotential for hydrogen evolution. We recently explored the use of ultra-flat, thin film, Au(111) electrodes to replace polycrystalline Au for As stripping voltammetry. Previous studies on oriented single crystals showed relatively narrow stripping peaks with greatly improved peak to background ratios on the (111) surfaces [3]. We observed comparatively similar or better stripping behavior on the Au(111) thin film electrodes with correspondingly far less gold usage per electrode. Unfortunately, copper is a known interference for arsenic stripping electroanalysis, with a strong affinity for UPD deposition on gold. We therefore studied the deposition behavior of Cu on Au(111) thin film electrodes and the co- deposition of Cu and As on the Au(111) thin film electrodes to evaluate cross interference effects. Copper redox behavior in 0.5M H2SO4 was characterized by cyclic voltammetry, electro- deposition and linear stripping voltammetry (LSV) measurements. Strong Cu UPD behavior was observed on Au(111) thin films with sharper, better defined redox peaks than polycrystalline electrodes. Arsenic and Cu ions were also co-deposited over a wide range of Cu (II) and As (III) concentrations. Complex redox behavior was observed with strong indications of Cu-As alloy formation. This was confirmed via angle resolved, X-ray Photoemission Spectroscopy (XPS) measurements. Our results also indicate that the electrodeposition efficiency during LSV of As is increased by the co-deposition of Cu. The results of this study have important implications for understanding the nature of Cu (II) interference with electrochemical detection of trace As (III) in water.[1] USEPA. National Secondary Drinking Water Regulations. 2009. https://www.epa.gov/sdwa/drinking-water- regulations-and-contaminants (accessed.[2] USEPA. METHOD 7063: ARSENIC IN AQUEOUS SAMPLES AND EXTRACTSBY ANODIC STRIPPING VOLTAMMETRY (ASV). 1996.[3] Casuse-Driovínto, T. Q.; Rizo, R.; Benavidez, A.; Brearley, A. J.; Cerrato, J. M.; Garzon, F. H.; Herrero, E.; Feliu, J. M. Increased Sensitivity and Selectivity for As(III) Detection at the Au(111) Surface: Single Crystals and Ultraflat Thin Films Comparison. The Journal of Physical Chemistry C 2022, 126 (48), 20343-20353. DOI: 10.1021/acs.jpcc.2c05541.

Multiple Diffusion Processes in Lithium-Ion Battery Electrolytes

Numerical simulations are a powerful tool for the development and improvement of Li-ion batteries[1]. Modelling the mass transport of the involved electrolytic solutions requires precise determination of the corresponding electrolyte parameter. However, the determination methods are still controversially discussed.In this work, we attempt to measure the complete set of electrolyte parameter for a system of 0.5 M LiPF6 dissolved in a blend of ethylene carbonate and ethyl methyl carbonate (EC:EMC, 3:7 weight) at 20°C and 50°C. In order to determine the conductivity, the diffusion coefficient, the transference number and the thermodynamic factor we conduct a combination of concentration cell measurements, galvanostatic polarization experiments and electrochemical impedance spectroscopy[2].While the conductivity and concentration cell measurements show comparable results to the literature, we find the potential response in the polarization experiments deviating from theoretical expectations. Applying galvanostatic polarization experiments to symmetrical metal Li | electrolyte + separator | Li metal cells result in slower, impeded diffusion processes. This indicates the presence of additional, undesired porous structures on the Li electrodes, preventing a reliable evaluation of the electrolyte parameters[3]. To spectrally resolve the diffusive processes, we conduct very low frequency impedance spectroscopy in an attempt to identify the impedance for the sole diffusion through the separator[4].1. Max Schammer et al 2021 J. Electrochem. Soc. 168 0265112. Johannes Landesfeind and Hubert A. Gasteiger 2019 J. Electrochem. Soc. 166 A30793. Talian et al. The Journal of Physical Chemistry C 2019 123 (46), 27997-280074. F. Wohde et al 2016 J. Electrochem. Soc. 163 A714Figure 1: VLF-IS measurements with amplitudes of 60µA, 500µA and 10µA together wit the corresponding equivalent circuits, fits and Kramers-Kronig transformations at 20° C and 50°C respectively Figure 1

Accelerating Real-Time Analysis of Gas Diffusion Electrodes Using Different Coupled Mass Spectrometry Techniques

Due to the rapid development of new catalysts, simple electrochemical screening methods are needed to evaluate the activity and stability of catalyst layers. Setups for these applications already exist: the so-called Scanning Flow Cells (SFCs) unify real-time electrochemical activity and dissolution stability analysis in a high-throughput fashion and find applications in a broad range of topics, such as battery research, 1 oxygen evolution reaction catalysts performance,2 and photo-electrochemistry.3 Yet, the low current densities reached in the system hinder the direct comparison of the results to real devices.4 Gas diffusion electrode (GDE) based setups present a promising alternative to Aqueous Model Systems (AMS) due to their ability to achieve higher current densities. Compared to two electrode full cells (fuel cell or water electrolyser), GDE half-cells are operated in a three-electrode configuration with liquid electrolyte. However, as in fuel cells, gasses reach the catalyst layer through a flow field, achieving relevant current densities up to 2 A cm-2. The GDE half- cell offers the advantage of studying the isolated reaction of the working electrode by applying controlled potentials with a reference electrode. While the GDE offers a simplified approach, the assembly process can be time-consuming, and the overall catalyst throughput analysis could be further optimised.5,6 In this context, we present a novel setup that enables the rapid examination of catalyst layers for fuel cells, providing more realistic conditions while simultaneously investigating degradation processes. The setup consists of an optimised SFC based on lower internal resistance and an additional flow field to purge the catalyst layer with different gasses. As the common SFC, the presented Scanning Gas Diffusion Electrode half cell (S-GDE) can be connected to an Inductively Coupled Plasma Mass Spectrometer (ICP-MS) to quantify the dissolution of metals in real-time. Furthermore, the gas-sensitive Mass Spectrometer can be connected to the gas stream of the cell, enabling the detection of volatile products via on-line electrochemical mass spectrometry (OLEMS). The simple replacement of catalyst layers in the S-GDE allows fast analysis of multiple catalysts consecutively. Still, as the aim is to facilitate high-throughput electrochemistry, developing the S-GDE is ongoing. Furthermore, the optimised cell can reach higher current densities than cells of a similar design, allowing accelerated stress tests (ASTs) and the performance of polarisation curves.The S-GDE will offer a new perspective on realistic catalyst layers, their performance, and catalyst/support degradation processes, e.g. Pt dissolution and carbon corrosion. The increasing demand for new catalyst materials highlights the need for their rapid evaluation under realistic conditions, taking into account not only their electrochemical performance but also their stability. Lüchtefeld J, Hemmelmann H, Wachs S, Mayrhofer KJ, Elm MT, Berkes BB. Effect of Water Contamination on the Transition Metal Dissolution in Water-Enriched Electrolyte: A Mechanistic Insight into a New Type of Dissolution. The Journal of Physical Chemistry C. 2022;126(40):17204–11.Zlatar M, Nater D, Escalera-López D, Joy RM, Pobedinskas P, Haenen K, et Evaluating the stability of Ir single atom and Ru atomic cluster oxygen evolution reaction electrocatalysts. Electrochimica Acta. 2023;444:141982.Jenewein KJ, Kormányos A, Knöppel J, Mayrhofer KJJ, Cherevko S. Accessing In Situ Photocorrosion under Realistic Light Conditions: Photoelectrochemical Scanning Flow Cell Coupled to Online ICP-MS. ACS Measurement Science Au. 2021;1(2):74–81.Ehelebe K, Escalera-López D, Cherevko S. Limitations of aqueous model systems in the stability assessment of electrocatalysts for oxygen reactions in fuel cell and Current Opinion in Electrochemistry. 2021;29:100832.Ehelebe K, Knöppel J, Bierling M, Mayerhöfer B, Böhm T, Kulyk N, et Platinum Dissolution in Realistic Fuel Cell Catalyst Layers. Angewandte Chemie (International ed in English). 2021;60(16):8882–8.Ehelebe K, Seeberger D, Paul MTY, Thiele S, Mayrhofer KJJ, Cherevko S. Evaluating Electrocatalysts at Relevant Currents in a Half-Cell: The Impact of Pt Loading on Oxygen Reduction Reaction. Journal of The Electrochemical Society. 2019;166(16):F1259-F68. Figure 1: The S-GDE unifies the real conditions approach of the GDE and the high throughput approach of the SFC and the connection to two mass spectrometer enables the real time detection of dissolved catalyst (ICP-MS) and volatile products (OLEMS). Figure 1

(Poster Award - Honorable Mention) Probing the Catalyst-Ionomer Interface in Catalyst Layers with Sulfo-Phenylated Polyphenylene Ionomers Using CO-Displacement and Stripping Techniques

Sulfo-phenylated polyphenylene ionomers (sPPP) are a class of hydrocarbon Ionomer being explored as a replacement for the perfluorinated sulfonic acid (PFSA) ionomer in fuel cell membranes and catalyst layers because they do not contain fluorinated compounds. Integration of sPPP ionomers into catalyst layers is challenging, as they have significantly different morphology compared to PFSA-based ionomers. Furthermore, little is known about the resulting ionomer-catalyst interface and whether characterization techniques developed for catalysts layers with PFSA-based ionomers will perform well for catalyst layers containing an sPPP ionomer. In this work, we examine the usefulness of CO displacement and stripping techniques to probe both the electrochemically active surface area (ECSA) of Pt/C in the catalyst layer and adsorbed species on the Pt catalyst sites. For catalyst layers containing PFSA, we measure a strong CO displacement reduction peak at potentials above potential of zero charge, when CO is introduced to the system, corresponding to sulfonic acid groups being displaced from active sites. The range of sulfonic acid groups adsorbed on the surface is 15- 25 % depending on the carbon support used. When the catalyst layers contain an sPPP ionomer instead of PFSA, the CO displacement peak is almost entirely suppressed, resulting in less than 10 % of sulfonic acid group adsorption. This is indicative that sPPP ionomer orientation near the Pt surface is very different compared to PFSA-based ionomer and that sulfonic acid groups do not “poison” Pt when in contact with the sPPP ionomer. However, mass activity increase is not observed for the sPPP ionomer-based catalyst layers, indicating there might be different “poisoning” mechanisms present, perhaps associated with the phenyl rings adsorption [1]. ECSA measurements for MEAs containing the non-fluorinated ionomer catalyst layers align with those measured for PFSA MEAs with the same catalysts type, loading, and comparable ionomer content, indicating that CO stripping is still a useful tool for assessing the ECSA for MEAs.[1] Zhai, Y., Baturina, O., Ramaker, D., Farquhar, E., St-Pierre, J., & Swider-Lyons, K. (2015). Chlorobenzene Poisoning and Recovery of Platinum-Based Cathodes in Proton Exchange Membrane Fuel Cells. Journal of Physical Chemistry C, 119(35), 20328–20338. https://doi.org/10.1021/acs.jpcc.5b06362

Scaling a Gas Phase Residual Lithium Conversion Process on Ni-Rich NMC Cathode Materials in Commercial Fluidized Bed Reactors

‘Residual lithium’, the LiOH and Li2CO3 surface contamination that is ubiquitous to Ni-rich NMC manufacturing, is a significant obstacle in the large-scale production and handling of high-nickel layered oxides. These hydroxide and carbonate surface phases influence reproducibility and shelf stability of the NMC powder and cause gelation and particle aggregation during electrode casting. There is ample evidence in the literature that atomic layer deposition (ALD) possesses a two-fold solution to this problem.1-3 First, reactive organometallic species such as trimethylaluminum (TMA) can convert insulating residual lithium to a Li-rich LixAlyO conducting layer. Customizable ALD layers can then be added to inhibit the re-formation of the carbonate layer and to deter negative side reactions of the CAM surface with the liquid electrolyte. While highly impactful, these studies have mostly been relegated to small, lab-scale demonstrations of <50 g. As such, there remains a need to enable this ALD-assisted-technology for high-throughput commercial applications.In this talk, we will explore the progression of a residual lithium conversion process from lab (10 – 1000 mL) to industrial-scale (10 L – 100 L) fluidized bed equipment and how scale and material-dependent parameters can impact performance. Using a commercial NMC 811 cathode as a case study, we first applied aluminum phosphate ALD coatings on a lab-scale fluidized bed reactor to examine the interfacial and electrochemical changes of the CAM material under various process conditions. ICP-OES measurements confirmed linear and reproducible deposition versus ALD cycle number between 200- 300°C. XPS analysis showed the ALD coated NMC 811 powder had an 80% reduction in Li2CO3 versus the pristine material and that a reduction persisted even after 10 days of storage in atmospheric conditions. At standard (0.5C/1C) cycling to 4.4V, AlPO4 coatings increased cycle life by 44% versus the uncoated powder. Under optimized conditions, the process was scaled first to 1 kg and finally to 10 kg in a pilot-scale reactor. In-situ mass spectrometry indicated that residual lithium conversion byproducts such as CO2 could be used to monitor reaction progress and optimize chemical usage efficiency. Fluidization aids including vibration and mechanical stirring were used to inhibit and break up powder agglomerates. ICP-OES and electrochemical cycling data confirmed reproducible deposition and cycle life benefits versus the small scale runs and pristine materials, demonstrating a pathway for these ALD-enhanced materials to transition from lab-scale demonstration to viable product. We will discuss strategies for continuing the scaling process to 100 kg batches for commercial applications.[1] M. Young et al., The Journal of Physical Chemistry C 2019 123 (39), 23783-23790[2] P. Darapaneni et al., ACS Applied Energy Materials 2022, 5, 8, 9870–9876[3] J. Li et al., Coatings 2022, 12(1), 84

CO-Driven Au Recovery and Nanoparticle Synthesis By in-Situ CO2 Reduction on Gas-Diffusion Electrodes

Effective synthesis methods for gold nanoparticles (NPs) have been extensively researched due to their wide-ranging applications in biomedicine, bioanalytical processes, and electrochemistry. Chemical reduction is the most common technique for producing precious metals nanoparticles, with the synthesis method greatly influencing the morphology of the resulting product. In most instances, the formation of polydisperse nanoparticles (NPs) is obtained (Reverberi, Kuznetsov et al. 2016). CO is a known reducing agent for and , offering fast reduction rates (Pretzer, Nguyen et al. 2010) and easy removal, resulting in fewer purification steps.We recently reported a synthesis method called Gas-Diffusion Electrocrystallization (GDEx), which can be applied to the platinum group metals (PGMs). The precipitation of the water-soluble PGM precursors is accomplished by the in situ production of H2 and CO, issued from the electrochemical reduction of CO2 and water electrolysis, respectively. This is typically accomplished using gas diffusion electrodes (Martinez Mora, Pozo et al. 2023). H2 acts as a reducing agent and CO as a size-controlling agent. In this work, we propose the synthesis of Au0 NPs driven by the GDEx process fed by CO2 in aqueous media.Different current densities (i.e., 10 and 40 mA cm-2) and two gas-flow regimes were tested –flow-by (FB) and flow-through (FT). Under FB, excess gas was fed into the gas chamber of the electrochemical set-up (i.e., 200 mL min-1), while under FT, the gas chamber overpressure was increased to force the gas through the GDE in convective regime, (i.e., the outlet of the gas chamber was closed and the flow rate was set to 5 mL min-1).In the first instance, the CO-driven Au(III) reduction process was modeled, including the CO(g)-CO(l) mass transport and equilibrium. It was discovered that the CO mass transport is the bottleneck in the reduction rate.In the GDEx electrochemical set-up, lower current densities and FT conditions achieved smaller particle size (i.e., 46 nm at -10 mA cm-2 and FT, table 1) and higher current efficiencies for CO production (~19 %, where the competing reaction was H2 evolution, table 1). Conversely, higher current densities led to faster reduction kinetics, yet lower current efficiencies (see Fig. 1).The GDEx process enables Au recovery and nanoparticle synthesis from Au(III)-containing synthetic streams, and can be applied to industrial leachates from end-of-life products. Conditions favoring CO mass transport and availability in the electrolyte improved the reduction kinetics. Furthermore, GDEx allows controlled CO production, mitigating the risk associated with using pure CO.Table 1. Summary of CO yield, current efficiencies and NP size for the different operating conditions j / mA cm-2 FB/FT CO generation / mmol min-1 CECO / % CEAu / % NP Size / nm Crystallite size / nm -10 FB 0.0023 7.3 4.2 70 ± 32 29 ± 7 FT 0.0081 18.6 6.6 46 ± 17 29 ± 6 -40 FB 0.0046 3.3 2.0 91 ± 36 31 ± 6 FT 0.0081 5.5 2.1 72 ± 20 27 ± 6 This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 958302 (PEACOC project). Martinez Mora, O., G. Pozo, L. F. Leon-Fernandez, J. Fransaer and X. Dominguez-Benetton (2023). "Synthesis of platinum group metal nanoparticles assisted by CO2 reduction and H2 cogeneration at gas-diffusion electrodes." RSC Sustainability.Pretzer, L., Q. Nguyen and M. Wong (2010). "Controlled Growth of Sub-10 nm Gold Nanoparticles Using Carbon Monoxide Reductant." The Journal of Physical Chemistry C 114.Reverberi, A. P., N. T. Kuznetsov, V. P. Meshalkin, M. Salerno and B. Fabiano (2016). "Systematical analysis of chemical methods in metal nanoparticles synthesis." Theoretical Foundations of Chemical Engineering 50: 59-66. Figure 1

Exploring the Efficiency of Lithium Stripping/Plating in Solid Polymer Anode-Free Lithium Cells

Traditional Li-ion batteries (LIBs) are widely used in various electronic devices due to their advantages in energy storage applications. However, finding ways to push the energy densities even higher would be highly desirable for the further rapid development of electric vehicles and electromobility. Li metal batteries and anode-free batteries (AFBs) – where the Li metal is plated in situ from Li+ ions taken from the cathode – have received extensive attention and research due to their very high specific capacity.[1] However, Li ions are unevenly deposited on the surface of anodes to form Li dendrite during the charging and discharging process, which severely deteriorates their electrochemical performance and battery safety.[2] To solve this problem, many researchers choose solid polymer electrolytes (SPEs) instead of liquid electrolytes in the batteries, because of the stability of SPEs towards Li metal.Long-term cycling of AFBs requires high-efficiency Li metal stripping and plating, which in a solid polymer cell is highly dependent on the polymer electrolyte system used, so finding appropriate host materials and salts to for the SPEs is very necessary. Poly(ethylene oxide) (PEO)-based SPEs are one of the most popular host materials for SPEs, due to their excellent chemical stability. Poly(ε-caprolactone) (PCL)-based SPEs have higher ionic conductivity and can be cycled at room temperature.[3] Poly(trimethylene carbonate) (PTMC)-based SPEs have high lithium transference number and better mechanical properties.[4] Lithium bis(trifluoromethanesulphonyl)imide (LiTFSI) is one of the most popular salts used for SPEs. Recently, lithium difluoro(oxalate)borate (LiDFOB) and lithium bis(oxalato)borate (LiBOB) have been considered a promising alternative as electrolyte because they can passivate electrode surfaces and protect electrode materials.[5] Combinations of these materials are all potentially relvant for application in AFBs.In this work, three different polymer host materials, PEO, PTMC, and PCL, were explored as polymer electrolytes together with LiTFSI salt for their performance in anode-less cell setups, testing the plating/striping coulombic efficiency (CE) in Cu || Li cells. The results reveal clear issues for the CE of cycling in the PEO:LiTFSI system, while low-concentration PTMC:LiTFSI instead shows much more promising results. Changing the LiTFSI salt for LiBOB or LiDFOB also improves the CE of the cells.[1] Beyene, T. T., Jote, B. A., Wondimkun, Z. T., Olbassa, B. W., Huang, C. J., Thirumalraj, B., Wang C. H., Su W. N., Dai H., Hwang B. J., Effects of concentrated salt and resting protocol on solid electrolyte interface formation for improved cycle stability of anode-free lithium metal batteries, ACS applied materials & interfaces, 2019, 11(35), 31962.[2] Huang W. Z., Zhao C. Z., Wu P., Yuan H., Feng W. E., Liu Z. Y., Lu Y., Sun S., Fu Z. H., Hu J. K., Yang S. J., Anode‐Free Solid‐State Lithium Batteries: A Review, Advanced Energy Materials, 2022, 12(26), 2201044.[3] Chiu, C. Y., Chen, H. W., Kuo, S. W., Huang, C. F., Chang, F. C., Investigating the effect of miscibility on the ionic conductivity of LiClO4/PEO/PCL ternary blends. Macromolecules, 2004, 37(22), 8424.[4] Li Z., Mogensen R., Mindemark J., Bowden T., Brandell D., Tominaga Y., Ion‐conductive and thermal properties of a synergistic poly (ethylene carbonate)/poly (trimethylene carbonate) blend electrolyte. Macromolecular rapid communications, 2018, 39(14):1800146.[5] Shkrob, I. A., Zhu, Y., Marin, T. W., Abraham, D. P., Mechanistic Insight into the Protective Action of Bis (oxalato) borate and Difluoro (oxalate) borate Anions in Li-Ion Batteries, The Journal of Physical Chemistry C, 2013, 117(45), 23750.

Modeling the Environment-Dependent Kinetics of Oxygen Reduction Reaction – a Continuum Model for Electric Double Layer

For proton-exchange-membrane fuel cells (PEMFCs) to achieve broad commercialization, improved energy-conversion efficiency with minimal Pt-based electrocatalyst is required [1]. Because the sluggish rate of oxygen reduction reaction (ORR) limits the efficiency of PEMFCs [2], the efficiency improvement requires a better understanding of ORR kinetics and mechanism to design better catalyst. To understand the ORR mechanism, theoretical and experimental analyses have been conducted. While previous studies reasonably explained the catalyst-dependent activity on single crystal catalysts in 0.1 M perchloric acid solution [3, 4], the explicit effect of electrolyte and related microenvironments [5, 6] is not thoroughly understood. The change in the electrolyte alters the electric-double-layer (EDL) structure and thus the local microenvironment at the electrode/electrolyte interface. Thus, the structure of the EDL should be carefully analyzed to uncover the electrolyte-dependent reaction kinetics. In this talk, we propose a multiscale continuum model to predict the EDL structure and examine the effect of perchloric acid concentration on ORR activity on Pt (111). The model includes Density Potential Functional Theory (DPFT) for electron density and Modified Poisson Boltzmann equation for species’ density and electric potential [7]. Also, the interaction between adsorbents and electric field is taken into account by minimizing the grand potential. After model validation with experimentally measured double-layer capacity data as a function of applied potential and concentration, the effect of the perchloric acid concentration (0.02 M – 0.2 M) on ORR activity is analyzed and discussed. It is shown that the model reproduces the specific activity obtained in the experiments when assuming the oxygen adsorption is limiting the rate, which can be attributed to the large energetic barrier for solvent reorganization [8]. Then, extension of the model to PEMFC ionomer electrolytes will be introduced. Overall, the model framework and findings provide insights into the ORR mechanism and guidance on how to tailor catalyst materials for increased PEMFC performance. Acknowledgements: This work was partially supported by the Hydrogen and Fuel Cell Technologies Office (HFTO), Office of Energy Efficiency and Renewable Energy, U.S. Department of Energy (DOE) through the Million Mile Fuel Cell Truck (M2FCT) consortia, technology managers G. Kleen and D. Papageorgopoulos, under contract number DE-AC02- 05CH11231, as well as by a CRADA with Toyota Central R&D Labs., Inc.. Reference [1] D. A. Cullen, K. C. Neyerlin, R. K. Ahluwalia, R. Mukundan, K. L. More, R. L. Borup, A. Z. Weber, D. J. Myers and A. Kusoglu, Nature Energy, 6, 462 (2021).[2] I. E. L. Stephens, A. S. Bondarenko, U. Grønbjerg, J. Rossmeisl and I. Chorkendorff, Energy & Environmental Science, 5 (2012).[3] M. Shibata, M. Inaba, K. Shinozaki, K. Kodama and R. Jinnouchi, Journal of The Electrochemical Society, 169 (2022).[4] H. A. Hansen, V. Viswanathan and J. K. Nørskov, The Journal of Physical Chemistry C, 118, 6706 (2014).[5] K. Kodama, K. Motobayashi, A. Shinohara, N. Hasegawa, K. Kudo, R. Jinnouchi, M. Osawa and Y. Morimoto, ACS Catalysis, 8, 694 (2017).[6] M. Luo and M. T. M. Koper, Nature Catalysis, 5, 615 (2022).[7] J. Huang, J Chem Theory Comput, 19, 1003 (2023).[8] D. T. Limmer, A. P. Willard, P. Madden and D. Chandler, Proceedings of the National Academy of Sciences, 110, 4200 (2013).

Electrodeposition of 3D Au1-XAgx Nanowire Networks – Influence of Ag on the Electrochemical Properties

We present the synthesis of free-standing Au1-xAgx alloy nanowire networks with controlled geometry and atomic composition, by ion track nanotechnology and electrodeposition, and their electrochemical characterization.Polycarbonate polymer templates with interconnected nanochannels are fabricated by sequential irradiation from four directions with 1-2 GeV Au ions at the UNILAC accelerator of GSI, followed by selective chemical etching of the ion tracks. [1] Au1-xAgx alloy nanowires are subsequently synthesized by potentiostatic electrodeposition inside the channels. Nanowire growth rate and atomic composition are tuned by varying the deposition potential and the electrolyte composition. The technique provides precise control of the nanowire size, interconnectivity, and composition. [2,3,4] By dissolving the polymer template, free standing nanowire networks are obtained showing good mechanical stability. Geometry, crystallinity, and composition of the alloy Au1-xAgx nanowires were analysed by TEM, EDX, and XPS. The results demonstrate that the Ag molar fraction can be precisely adjusted between 10% and 90%.The electrochemically active surface area was determined by measuring the double layer capacitance of the nanowire network surface, and is in good agreement with the calculated theoretical surface area. The 3D network exhibit surface areas up to 200 times larger than their planar counterpart, which makes them highly interesting for catalytic processes. Their electrochemical activity in alkaline solution is investigated by cyclic voltammetry in 0.1 M KOH electrolyte, and will be discussed in this presentation.[1] M.E. Toimil-Molares, Beilstein Journal of Nanotechnology, 3.1, 860-883 (2012).[2] M. Rauber, I. Alber, S. Müller et al. Nano Letters, 11.6, 2304-2310 (2011).[3] L. Burr, I. Schubert, W. Sigle et al. The Journal of Physical Chemistry C, 119.36, 20949-20956 (2015).[4] M. Li, N. Ulrich, I. Schubert et al. RSC Advances, 13, 4721-4728 (2023).

Reevaluation of the reaction rates of H+O2

The rate coefficients of H+O2=O+OH (R1) were reevaluated using the reported shock tube experimental data from Ryu et al. (1995), Yuan et al. (1991), Masten et al. (1991) and Hong et al. (2011) based on our latest kinetic mechanism [Xueliang Yang et al., Journal of Physical Chemistry A, 2021, 125, 10223–10234]. The statistical analysis using weighted average and weighted least-square regression was performed by applying the updates on specific rates and corresponding uncertainties. The chain-termination reaction of H+O2(+M)=HO2(+M) (R2) was reevaluated as well. New rate formulae of R1 and R2 were derived and incorporated back into the mechanism. The validation demonstrates the updated mechanism has good performance against the measurements such as mass burning rate and ignition delay time at broad range of initial conditions.

(First Place Poster Award) Probing Charge Transport Mechanisms in 2D Metal Organic Frameworks

Metal Organic Frameworks (MOFs) are a class of highly porous crystalline materials that are constructed from zero- or one-dimensional inorganic chains in combination with multitopic organic ligands.1 They have received great attention recently due to their large surface area, tunable porosity, and easy preparation, which lead to their versatile applications including gas storage2 and separation3, sensing4, catalysis5 and drug delivery6. The versatility of MOFs is further entrenched in the vast available design space offered by the enormous number of metal-linker combinations7, 8. However, majority of MOFs are insulators with very few of them showing appreciable electrical conductivity. The insulating nature of MOFs can be traced back to the starting materials used in constructing these hybrid materials9. Although conductive MOFs have been reported, very little information about the mechanism of charge transport is available.10-12 There are mainly two types of charge transport mechanism reported in such materials, hopping and band transport.13 Hopping mechanism is dominated by movement of charges from donor to acceptor moieties due to charge localization which exists at specific sites within the MOF.13 Band transport relies on delocalization of carriers throughout the valence and conduction bands.14 These mechanisms require low energy pathways for charge transport which are not present in MOFs. Recently, researchers have focused on two synthetic approaches from a chemical perspective to achieve such low energy pathways; through bond approach and through space approach.13 Ideally, both pathways can either lead to band or hopping transport. The through space mechanism utilizes non-covalent interactions like π-π stacking between organic linkers, which creates an extended pathway for charge delocalization usually pronounced in 2D MOFs.15, 16 Recent studies which have successfully quantified and identified charge carrier types in MOFs17 show that conductivity increases mainly with chemical oxidation signifying hole formation18, but mobility and directional charge transfer is still limited by geometry.19 Although the field of electrically conductive MOFs has experienced tremendous expansion in the last decade and yielded a variety of MOFs with high mobility and conductivity, majority of these works focus on material design principle and conductivity measurement, leaving the fundamental understanding of CT mechanism underexplored; yet the latter is essential for the further development of this class of materials to be exploited in optoelectronics, solar cells, and photocatalysis. I will present my progress in exploring CT mechanisms in 2D MOFs using advanced spectroscopic techniques.ReferencesC. Janiak and J. K. Vieth, New J. Chem., 2010, 34, 2366-2388.M. Latroche, S. Surble, C. Serre, C. Mellot-Draznieks, P. L. Llewellyn, J. H. Lee, J. S. Chang, S. H. Jhung and G. Ferey, Angewandte Chemie-International Edition, 2006, 45, 8227-8231.Z. J. Zhang, Y. G. Zhao, Q. H. Gong, Z. Li and J. Li, Chem. Commun., 2013, 49, 653-661.E. A. Dolgopolova, A. M. Rice, C. R. Martin and N. B. Shustova, Chem. Soc. Rev., 2018, 47, 4710-4728.Y. X. Zhou, W. H. Hu, S. Z. Yang, Y. B. Zhang, J. Nyakuchena, K. Duisenova, S. Lee, D. H. Fan and J. Huang, Journal of Physical Chemistry C, 2020, 124, 1405-1412.I. A. Lazaro and R. S. Forgan, Coord. Chem. Rev., 2019, 380, 230-259.C. Muschielok and H. Oberhofer, J. Chem. Phys., 2019, 151.L. Sun, M. G. Campbell and M. Dinca, Angewandte Chemie-International Edition, 2016, 55, 3566-3579.P. F. Li and B. Wang, Isr. J. Chem., 2018, 58, 1010-1018.K. W. Nam, S. S. Park, R. dos Reis, V. P. Dravid, H. Kim, C. A. Mirkin and J. F. Stoddart, Nature Communications, 2019, 10, 10.T. Chen, J.-H. Dou, L. Yang, C. Sun, N. J. Libretto, G. Skorupskii, J. T. Miller and M. Dincă, J. Am. Chem. Soc., 2020, 142, 12367-12373.S. S. Park, E. R. Hontz, L. Sun, C. H. Hendon, A. Walsh, T. Van Voorhis and M. Dincă, J. Am. Chem. Soc., 2015, 137, 1774-1777.M. Ko, L. Mendecki and K. A. Mirica, Chem. Commun., 2018, 54, 7873-7891.R. Dong, P. Han, H. Arora, M. Ballabio, M. Karakus, Z. Zhang, C. Shekhar, P. Adler, P. St Petkov, A. Erbe, S. C. B. Mannsfeld, C. Felser, T. Heine, M. Bonn, X. L. Feng and E. Canovas, Nature Materials, 2018, 17, 1027-+.L. Y. Qu, H. Iguchi, S. Takaishi, F. Habib, C. F. Leong, D. M. D'Alessandro, T. Yoshida, H. Abe, E. Nishibori and M. Yamashita, J. Am. Chem. Soc., 2019, 141, 6802-6806.L. S. Xie, E. V. Alexandrov, G. Skorupskii, D. M. Proserpio and M. Dinca, Chemical Science, 2019, 10, 8558-8565.A.C. Hinckley, J. Park, J. Gomes, E. Carlson and Z. Bao, J. Am. Chem. Soc., 2020, 142, 11123-11130. S.

Investigation on Reaction Mechanism in an SOFC Composite Cathode by Using Patterned Thin Film Electrodes

Introduction For the further commercial use of solid oxide fuel cells (SOFCs), operating at intermediate temperatures is demanded. When reducing the operating temperature, the degradation of cathodic activity occupies the largest part of degradation of cell performance. Therefore, to improve the performance of SOFCs at intermediate temperature, the activity of cathodic reaction has to be improved.The cathodic reaction of SOFCs proceeds not only at triple phase boundaries (TPBs) of electrode, electrolyte and gas but also at double phase boundaries (DPBs) of electrode and gas, when a mixed ionic and electronic conductor (MIEC) is used. Thus, increasing the DPB area is considered as the best way to improve the cathodic performance. However, it was reported that composite cathodes of MIEC and electrolyte particles showed better performance than simple MIEC cathodes, despite the DPB area decreased [1]. Possible reasons for such performance enhancement can be considered as (i) promotion of oxide ion diffusion and/or (ii) the increase of TPB concentration. However, the reason for the performance enhancement by making a composite cathode are not-well understood so far.In this study, we aimed to understand the cathodic reaction in a composite cathode of MIEC and electrolyte. For this purpose, we proposed new types of original model electrodes to simulate the reaction in actual porous composite electrodes. From electrochemical and the operando X-ray absorption spectroscopic measurements of the model electrodes, we tried to separately evaluate the contribution of ion diffusion and TPB reactions on the performance improvement of composite cathode. Methods When using a porous electrode, it is difficult to investigate the reaction mechanism because of its complicated microstructures. Our research group proposed so-called “patterned thin film model electrode” like Figure 1(a) as a model electrode to reproduce the reaction in a porous electrode while removing the influence of microstructure [2]. In this model electrode, the contact area of electrode and electrolyte was limited by partially inserting an insulating layer, and thus the reaction distribution was formed in the electrode as a function of the distance from the electrode/electrolyte interface.In this study, we proposed two new types of model electrodes as Figure 1(b) and 1(c) to simulate the porous composite electrode. In the patterned composite electrode (b), an electrolyte layer was inserted between the electrode and insulator. On the other hand, in the patterned composite electrode (c), a part of electrode was removed to introduce TPBs. From the difference between the model electrodes (a) and (b), the contribution of oxide ion diffusion in composite electrode was estimated. From the difference between the model electrodes (b) and (c) the contribution of the TPB reaction was estimated. In this study, we selected La0.6Sr0.4CoO3-δ (LSC64) as an MIEC cathode and Gd0.1Ce0.9O2-δ (GDC10) as an electrolyte material. Operando micro X-ray absorption spectroscopy (μ-XAS) measurement was conducted with the model electrodes to investigate the effective reaction area of the model electrode. In this measurement, a change in the oxygen chemical potential can be detected as a change of X-ray absorbance at the fixed energy near the Co K-edge accompanying a change of the oxidation state of Co in the LSC64 [3]. Thus, the reaction distribution could be evaluated by measuring the change of the X-ray absorbance due to the polarization as a function of the distance from the electrode/electrolyte interface. Results and Discussion Figure 2 shows the results of μ-XAS measurement at 973 K under 1 bar O2 with cathodic polarization. The area where the ratio of absorbance is larger than 1 corresponds to the area where the oxygen chemical potential is changed due to the polarization, i.e. the effective reaction area. The reaction area of the model electrode (b) was longer than that of the model electrode (a). This suggested oxide ion diffusion was improved by inserting the GDC layer. On the other hand, the reaction area of the model electrode (c) was longer than that of the model electrode (b). Generally, the reaction on the mixed conducting LSC64 electrode is supposed to proceed DPB reaction mainly. However, the longer reaction area of model electrode (c) indicated that the contribution of TPB reaction was also significant in the LSC64 composite electrode. As a conclusion, both promotion of oxide diffusion and the increase of TPB effective for the enhancement of the cathodic reaction in MIEC composite electrode.[1] Y. T. Kim, et al., Solid State Ionics, 309, 77-85 (2017).[2] K. Amezawa, et al., ECS transactions, 62(2), 129-135 (2015).[3] Y. Orikasa, et al., Journal of Physical Chemistry C, 115, 16433–16438 (2011). Figure 1

Preferential Coordination As a Means to Investigate Ca2+ Speciation and SEI Formation

Given concerns about the low earth abundance of Li in Li-ion batteries, there is growing interest in developing a beyond-Li materials basis for rechargeable batteries. Divalent batteries based on calcium (Ca) have received attention due to their ~2000-fold higher concentration in the earth’s crust along with attractive theoretical metrics if Ca is used as the metallic anode. When most common battery electrolytes come into contact with Ca, however, a passivating solid electrolyte interphase (SEI) forms that prevents Ca2+ transport.1 At present, only a small number of nonaqueous electrolytes have been identified that form sufficiently Ca2+-conductive SEIs for Ca electrodeposition, limiting the design space for Ca battery development. Thus, learning how to tailor Ca SEI formation is of central importance to identify handles for next-generation battery design. Several methods of modifying SEI to improve Ca2+ transport have been reported, including synthesizing an ex situ artificial layer,2 or the introduction of boron-containing electrolyte additives that form beneficial SEI compounds.3 Ca electrolyte modification faces a unique challenge, however, as the large size and divalent nature of Ca2+ leads to large coordination environments (up to 7 solvating molecules) in solution.4 Recent studies have begun to identify that co-reduction of these coordinating molecules has a significant impact on Ca electrochemistry. For example, strong coordination between Ca2+ and the anion TFSI- has been demonstrated to deactivate Ca plating behavior via TFSI- decomposition.5,6 However, competition between coordinating molecules can be exploited to favor specific Ca2+ speciation (i.e. BH4 - displaces bidentate TFSI---Ca2+ in favor of BH4 ---Ca2+ interactions) and unlock Ca plating behavior.6 Further mechanistic understanding is needed to identify the specific connections between Ca2+ coordination, SEI formation, and anode performance (beyond just a binary toggling of plating behavior). To address this, we have systematically introduced chelating glyme-based solvents into a baseline electrolyte, investigating the subsequent changes in SEI composition and electrochemical behavior.This study investigates the preferential coordination of Ca2+ by glymes in the baseline electrolyte 1 M Ca(BH4)2 in tetrahydrofuran (THF). THF is systematically replaced by 1,2-dimethoxyethane (G1) or bis(2-methoxyethyl) ether (G2) over a range of Gx/Ca2+ molar ratios. Microcalorimetry measurements demonstrate that the introduction of both G1 and G2 to the electrolyte is enthalpically favorable, as each glyme displaces THF from the Ca2+ coordination sphere and modulates Ca2+--BH4 - speciation, as indicated by NMR and Raman spectroscopy. Addition of a small amount of each glyme (1:1 Gx/Ca2+) increases electrolyte ionic conductivity by nearly half; however, glyme addition systematically increases the overpotentials of both Ca plating and stripping while decreasing Coulombic efficiency. The presence of glymes increases the amount of carbon present in both chemically- and electrochemically-formed SEI as indicated through XPS. We further find increased evidence of fragmentation of strongly Ca2+-coordinating molecules (G2, BH4 -) within the SEI formed during Ca deposition as compared to formed chemically. Calcium-based olefins as well as ionic phases (CaCO3, CaC2) are detected in electrochemically-formed SEI through titration gas chromatography. This work reveals factors that modulate both Ca2+ coordination and subsequent SEI formation, highlighting preferential coordination as a novel approach for Ca-based electrolyte design.1 Aurbach, D., Skaletsky, R. & Gofer, Y. The Electrochemical Behavior of Calcium Electrodes in a Few Organic Electrolytes. Journal of The Electrochemical Society 138, 3536-3545 (1991).2 Hou, Z., Zhou, R., Min, Z., Lu, Z. & Zhang, B. Realizing Wide-Temperature Reversible Ca Metal Anodes through a Ca2+-Conducting Artificial Layer. ACS Energy Letters, 274-279 (2022).3 Bodin, C. et al. Boron-Based Functional Additives Enable Solid Electrolyte Interphase Engineering in Calcium Metal Battery. Batteries & Supercaps n/a, e202200433 (2022).4 Tchitchekova, D. S. et al. On the Reliability of Half-Cell Tests for Monovalent (Li+, Na+) and Divalent (Mg2+, Ca2+) Cation Based Batteries. Journal of The Electrochemical Society 164, A1384-A1392 (2017).5 Hahn, N. T. et al. Influence of Ether Solvent and Anion Coordination on Electrochemical Behavior in Calcium Battery Electrolytes. ACS Applied Energy Materials 3, 8437-8447 (2020).6 Melemed, A. M., Skiba, D. A. & Gallant, B. M. Toggling Calcium Plating Activity and Reversibility through Modulation of Ca2+ Speciation in Borohydride-Based Electrolytes. The Journal of Physical Chemistry C 126, 892-902 (2022).

(Invited) In Situ Spectroscopy of Electrocatalytic and Photocatalytic Interfaces

We report various aspects of electrochemistry and photoelectrochemistry using in situ spectroscopy of electrode (metal) and photoelectrode (semiconductor) interfaces in situ under electrochemical working conditions. These spectroscopies include sum frequency generation (SFG), transient reflectance/absorption spectroscopy (TAS/TRS), and surface enhanced Raman spectroscopy (SERS). Using surface enhanced Raman scattering (SERS) spectroscopy, we monitor local electric fields using Stark-shifts of nitrile-functionalized silicon photoelectrodes.6 Using Graphene-enhanced Raman spectroscopy (GERS)-based Stark-shifts, we measure local electric fields and local charge densities at monolayer graphene electrode surfaces.1 We also measured the stacking dependence and Resonant interlayer excitation of monolayer WSe2/MoSe2 heterostructures for photocatalytic energy conversion.2 Using sum frequency generation (SFG) spectroscopy, we measure the voltage dependence of the orientation of D2O molecules at a graphene electrode surface, which is related back to the “stiffness of the ensemble”.3 In particular, we measured the “free OD” feature in the spectra, which corresponds to the topmost water molecule that is rotated up out of the bulk water solution and is, therefore, not hydrogen bonded. Using transient absorption spectroscopy (TAS), we measure the lifetime of hot electrons photoexcited in plasmon resonant nanostructures.5 Using transient reflectance spectroscopy (TRS), we measure the photoexcited carrier dynamics in a GaP/TiO2 photoelectrode, as well as the electrostatic field dynamics at this semiconductor-liquid interfaces in situ under various electrochemical potentials.4 Here, the electrostatic fields at the surface of the semiconductor are measured via Franz−Keldysh oscillations (FKO). These spectra reveal that the nanoscale TiO2 protection layer enhances the built-in field and charge separation performance of GaP photoelectrodes. Shi, H.T., B.F. Zhao, J. Ma, M.J. Bronson, Z. Cai, J.H. Chen, Y. Wang, M. Cronin, L. Jensen and S.B. Cronin, Measuring Local Electric Fields and Local Charge Densities at Electrode Surfaces Using Graphene-Enhanced Raman Spectroscopy (GERS)-Based Stark-Shifts. ACS Applied Materials & Interfaces, 11, 36252-36258 (2019).Chen, J., C.S. Bailey, D. Cui, Y. Wang, B. Wang, H. Shi, Z. Cai, E. Pop, C. Zhou and S.B. Cronin, Stacking Independence and Resonant Interlayer Excitation of Monolayer WSe2/MoSe2 Heterostructures for Photocatalytic Energy Conversion. ACS Applied Nano Materials, DOI:10.1021/acsanm.9b01898 (2020).Montenegro, A., C. Dutta, M. Mammetkuliev, H.T. Shi, B.Y. Hou, D. Bhattacharyya, B.F. Zhao, S.B. Cronin and A.V. Benderskii, Asymmetric response of interfacial water to applied electric fields. Nature, 594, 62 (2021).Xu, Z.H., B.Y. Hou, F.Y. Zhao, Z. Cai, H.T. Shi, Y.W. Liu, C.L. Hill, D.G. Musaev, M. Mecklenburg, S.B. Cronin and T.Q. Lian, Nanoscale TiO2 Protection Layer Enhances the Built-In Field and Charge Separation Performance of GaP Photoelectrodes. Nano Letters, 21, 8017-8024 (2021).Yu Wang, Yi Wang, Indu Aravind, Zhi Cai, Lang Shen, Boxin Zhang, Bo Wang, Jihan Chen, Bofan Zhao, Haotian Shi, Jahan M. Dawlaty, and Stephen B. Cronin. In Situ Investigation of Ultrafast Dynamics of Hot Electron-Driven Photocatalysis in Plasmon-Resonant Grating Structures. Journal of the American Chemical Society. DOI: 10.1021/jacs.1c12069 (2022).Haotian Shi, Ryan T. Pekarek, Ran Chen, Boxin Zhang, Yu Wang, Indu Aravind, Zhi Cai, Lasse Jensen, Nathan R. Neale, and Stephen B. Cronin. Monitoring Local Electric Fields using Stark Shifts on Napthyl Nitrile-Functionalized Silicon Photoelectrodes. The Journal of Physical Chemistry C, 124, 17000-17005 (2020).

Towards a Reversible Calcium Anode through Electrolyte and Interface Engineering for Calcium Metal Batteries

Lithium-ion batteries have played an important role in decarbonizing the transportation sector, but broader utilization is currently limited by practically-attainable energy densities, safety concerns, and supply chain issues. Batteries based on calcium (Ca) metal anodes offer higher theoretical energy densities, as well as significant potential improvements in scalability and sustainability. The field of Ca metal batteries is currently in its early stages, however, due to a limited number of electrolytes that can reversibly plate and strip Ca. Two important challenges to overcome are (1) the formation of passivating solid electrolyte interphases (SEI) between Ca and the electrolyte that prevent Ca2+ transport, and (2) Ca2+-anion interactions in the electrolyte that promote cluster formation and hinder electrochemistry.1,2 This talk will explore research performed in both aspects of Ca battery development and identify strategies for future advancements. First, the electrochemical signatures of three model interfaces on Ca foil electrodes were investigated in a baseline electrolyte using cyclic voltammetry;3 the long-term cycling behavior was governed to a greater extent by electrolyte properties than the initial surface layers. Subsequent efforts have focused on electrolyte engineering, and specifically, on studying the impact that the Ca2+ coordination environment has on reversible Ca plating and stripping. For example, strong coordination between Ca2+ and the anion TFSI- has been demonstrated to deactivate Ca plating behavior via TFSI- decomposition.4,5 However, competition between coordinating molecules can be exploited to favor specific Ca2+ speciation; preferential coordination between Ca2+ and BH4 - displaces bidentate TFSI---Ca2+, unlocking Ca plating behavior in tetrahydrofuran.5 Further studies into preferential coordination are ongoing in order to better identify the connections between Ca2+ coordination, SEI formation, and anode performance. We hope to identify specific electrolyte design criteria that can advance the functionality of Ca electrolytes and ultimately examine the feasibility of Ca as a novel battery chemistry.1 Aurbach, D., Skaletsky, R. & Gofer, Y. The Electrochemical Behavior of Calcium Electrodes in a Few Organic Electrolytes. Journal of The Electrochemical Society 138, 3536-3545 (1991).2 Arroyo-de Dompablo, M. E., Ponrouch, A., Johansson, P. & Palacín, M. R. Achievements, Challenges, and Prospects of Calcium Batteries. Chemical Reviews (2019).3 Melemed, A. M. & Gallant, B. M. Electrochemical Signatures of Interface-Dominated Behavior in the Testing of Calcium Foil Anodes. Journal of The Electrochemical Society 167, 140543 (2020).4 Hahn, N. T. et al. Influence of Ether Solvent and Anion Coordination on Electrochemical Behavior in Calcium Battery Electrolytes. ACS Applied Energy Materials 3, 8437-8447 (2020).5 Melemed, A. M., Skiba, D. A. & Gallant, B. M. Toggling Calcium Plating Activity and Reversibility through Modulation of Ca2+ Speciation in Borohydride-Based Electrolytes. The Journal of Physical Chemistry C 126, 892-902 (2022).

Machine Learning-Assisted Battery Electrode Microstructure Characterization through Secondary-Ions Imaging

Electrodes are a key component of modern Li-ion and solid-state batteries, and their microstructure is recognized to affect their cycle life, safety, energy and power densities, underlying the importance of microstructure characterization.1–4 Among the different techniques used to this scope, Secondary Electrons Microscopy (SEM) and Focused-Ion Beam SEM (FIB-SEM) are widely used for acquiring 2D and 3D information, respectively.5,6 Despite the advantages of these techniques, one main limitation is that chemically different species having similar atomic components or weights are often not distinguishable, not allowing the characterization of, for instance, the solid electrolyte interfaces (SEI), i.e., degradation products formed at the active material surfaces and playing a key role in the electrode performance and lifetime.Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) is a surface technique based on the analysis of the secondary ions generated through the impact between an accelerated primary ion and the sample (Figure 1A). ToF-SIMS allows obtaining chemically-specific information and acquiring images of sizes in the order of hundreds of um, with a resolution down to 150 nm.7,8 However, the long acquisition time for imaging limits its applications to 2D microstructural characterization.In this work, we combined a devoted experimental set-up to image a statistically representative section of the electrode (its cross-section) through ToF-SIMS, and a machine learning procedure9 based on generative adversarial networks to reconstruct a realistic 3D electrode microstructure using, as input, the 2D ToF-SIMS image (Figure 1B). This approach showed to be applicable not only to characterize the spatial distribution of the electrode main components, but also to map the spatial distribution of degradation products forming the SEI, opening the door to more in-depth analyses of the relationships between electrode microstructure, spatial distribution of the degradation products, and electrochemical performance. This approach could be of use for both experimental and computational analyses, the latter through 3D electrochemical models using as input the so-obtained 3D electrode microstructure. References (1) Xu, H.; Zhu, J.; Finegan, D. P.; Zhao, H.; Lu, X.; Li, W.; Hoffman, N.; Bertei, A.; Shearing, P.; Bazant, M. Z. Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning. Adv Energy Mater 2021, 2003908, 2003908. https://doi.org/10.1002/aenm.202003908.(2) Lu, X.; Bertei, A.; Finegan, D. P.; Tan, C.; Daemi, S. R.; Weaving, J. S.; Regan, K. B. O.; Heenan, T. M. M.; Hinds, G.; Kendrick, E.; Brett, D. J. L.; Shearing, P. R. 3D Microstructure Design of Lithium-Ion Battery Electrodes Assisted by X-Ray Nano-Computed Tomography and Modelling. Nat Commun 2020, 11 (2079), 1–13. https://doi.org/10.1038/s41467-020-15811-x.(3) Chouchane, M.; Franco, A. A. Deconvoluting the Impacts of the Active Material Skeleton and the Inactive Phase Morphology on the Performance of Lithium Ion Battery Electrodes. Energy Storage Mater 2022, 47, 649–655. https://doi.org/10.1016/j.ensm.2022.02.016.(4) Bielefeld, A.; Weber, D. A.; Janek, J. Microstructural Modeling of Composite Cathodes for All-Solid-State Batteries. Journal of Physical Chemistry C 2019, 123 (3), 1626–1634. https://doi.org/10.1021/acs.jpcc.8b11043.(5) Joos, J.; Buchele, A.; Schmidt, A.; Weber, A.; Ivers-Tiffée, E. Virtual Electrode Design for Lithium-Ion Battery Cathodes. Energy Technology 2021, 2000891. https://doi.org/10.1002/ente.202000891.(6) Zielke, L.; Hutzenlaub, T.; Wheeler, D. R.; Chao, C. W.; Manke, I.; Hilger, A.; Paust, N.; Zengerle, R.; Thiele, S. Three-Phase Multiscale Modeling of a LiCoO2 Cathode: Combining the Advantages of FIB-SEM Imaging and X-Ray Tomography. Adv Energy Mater 2015, 5 (5). https://doi.org/10.1002/aenm.201401612.(7) Walther, F.; Strauss, F.; Wu, X.; Mogwitz, B.; Hertle, J.; Sann, J.; Rohnke, M.; Brezesinski, T.; Janek, J. The Working Principle of a Li2CO3/LiNbO3Coating on NCM for Thiophosphate-Based All-Solid-State Batteries. Chemistry of Materials 2021, 33 (6), 2110–2125. https://doi.org/10.1021/acs.chemmater.0c04660.(8) Walther, F.; Koerver, R.; Fuchs, T.; Ohno, S.; Sann, J.; Rohnke, M.; Zeier, W. G.; Janek, J. Visualization of the Interfacial Decomposition of Composite Cathodes in Argyrodite-Based All-Solid-State Batteries Using Time-of-Flight Secondary-Ion Mass Spectrometry. Chemistry of Materials 2019. https://doi.org/10.1021/acs.chemmater.9b00770.(9) Kench, S.; Cooper, S. J. Generating Three-Dimensional Structures from a Two-Dimensional Slice with Generative Adversarial Network-Based Dimensionality Expansion. Nat Mach Intell 2021, 3 (4), 299–305. https://doi.org/10.1038/s42256-021-00322-1. Figure 1

RTILs as Electrolytes in Electrochemical Gas Sensors for O2 and Other Gases

Oxygen is the third-most abundant element on this planet and is essential to life, the lifestyle of humans and virtually all sentient life. We need O2 to live and additionally use it for both heating and transportation. Since O2 is so essential in our everyday life, there are several applications where the oxygen levels need to be controlled or maintained within a certain range. To make sure that the O2 level is within the necessary range, devices are needed that can monitor and feedback/communicate O2 levels continuously. There are several types of chemical gas sensors for O2 which include chemoresistive gas sensors and electrochemical gas sensors. The Clark-type electrochemical sensor is the oldest and probably the most used sensor for oxygen especially in medical applications. One of the most well-known industrial applications for gas-phase oxygen sensors is probably the control of oxygen levels in combustion engines with the help of a Lambda probe, a solid-state electrochemical cell operated in amperometric and potentiometric modes.Electrochemical sensors have evolved over the past decades. By finding the suitable combination of electrolyte, electrode material, cell design and operation conditions, electrochemical sensors are tunable to meet the specific requirements of the many different applications. For example, by changing the electrode material from gold to platinum while keeping everything else the same, you can reduce the response to CO by orders of magnitude improving the selectivity in low level measurements. Further, by adjusting the thermodynamic voltage of the sensing electrode, the electrochemical reactivity is adjusted to maximize the sensor’s selectivity for the target analyte. While these developments have occurred over time, recent work implements room temperature ionic liquids (RTILs) as electrolytes. This idea has some serious merit to it for multiple reasons. Firstly, many electrochemical sensors have aqueous electrolytes which freeze at low temperatures and rapidly evaporate at elevated temperatures. Additionally, aqueous electrolytes can change in real time with variations in background humidity levels. To be more exact, aqueous electrolytes dry out when operated in low humidity backgrounds and significantly increase in volume (swell) in high humidity background levels. While drying out is an issue because this leads to poor ionic conductivities, swelling is an issue because the electrolyte needs expansion room in the sensor, typically an extensive cavity within the cell body. RTILs have shown promise because they can extend the operating temperature range as well as lead to new sensor designs operatable over a wider range of environmental conditions. The implementation of RTILs might even allow for smaller sensor designs due to a smaller volume change of the electrolyte in dependence of changing humidity levels.Several research groups have investigated the oxygen sensing capabilities of RTILs in electrochemical devices. Silvester et al. investigated the oxygen solubility in several different imidazolium cations combined with [bis(trifluoromethylsulfonyl)imide] ([NTf2]-) anions and found a high oxygen solubility in 3-butyl-1-methyl imidazolium [NTf2]- [1]. They further investigated the influence of humidity on the oxygen reduction reaction and found the most stable behavior for [3-etyhl-1-methyl imidiazolium] [NTf2]- over a broad range of different humidity levels [2]. Yin et al. investigated 1-butyl-1-methylpyrrolidinium [NTf2]- as an electrolyte in oxygen sensors and found good linear correlation of the sensor output to the oxygen concentration [3].In this work, we investigated different RTILs, including the before mentioned 1-butyl-1-methylpyrrolidinium [NTf2]- and 3-butyl-1-methyl imidazolium [NTf2]-, regarding their suitability for thin layer electrochemical oxygen sensors in a background of mostly nitrogen. The performance was investigated using CV (cyclic voltammetry) and other time dependent voltametric techniques. The ability to detect oxygen of sensors with different RTILs as electrolyte was compared to that of aqueous H2SO4.[1] S. Doblinger, D.S. Silvester, M. Costa Gomes, Functionalized Imidazolium Bis(trifluoromethylsulfonyl)-imide Ionic Liquids for Gas Sensors: Solubility of H2, O2 and SO2, Fluid Phase Equilib. 549 (2021). https://doi.org/10.1016/j.fluid.2021.113211.[2] S. Doblinger, J. Lee, D.S. Silvester, Effect of Ionic Liquid Structure on the Oxygen Reduction Reaction under Humidified Conditions, Journal of Physical Chemistry C. 123 (2019) 10727–10737. https://doi.org/10.1021/acs.jpcc.8b12123.[3] H. Yin, H. Wan, L. Lin, X. Zeng, A.J. Mason, Miniaturized Planar RTIL-based Electrochemical Gas Sensor for Real-Time Point-of-Exposure Monitoring, 2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT). (2016) 85–88. https://doi.org/10.1109/HIC.2016.7797703.

Characteristics of Impactful Machine Learning Contributions to The Journal of Physical Chemistry

ADVERTISEMENT RETURN TO ISSUEEditorialNEXTCharacteristics of Impactful Machine Learning Contributions to The Journal of Physical ChemistryAndrew L. Ferguson*Andrew L. FergusonPritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States*[email protected]More by Andrew L. Fergusonhttps://orcid.org/0000-0002-8829-9726 and Jim Pfaendtner*Jim PfaendtnerDepartment of Chemical Engineering, University of Washington, Seattle, Washington 98195, United StatesPhysical Sciences Division, Pacific Northwest National Laboratory, Richmond, Washington 99354, United States*[email protected]More by Jim Pfaendtnerhttps://orcid.org/0000-0001-6727-2957Cite this: J. Phys. Chem. B 2023, 127, 2, 427–429Publication Date (Web):January 19, 2023Publication History Received12 December 2022Published online19 January 2023Published inissue 19 January 2023https://doi.org/10.1021/acs.jpcb.2c08703Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views197Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (992 KB) Get e-AlertsSUBJECTS:Computational chemistry,Computational modeling,Machine learning,Neural networks,Physical chemistry Get e-Alerts

Quantum Optics: A Scientometric Assessment of India’s Publications during 1996-2021

Objectives: The present study examines the publication output of authors from India on the topic of “Quantum Optics” during 1996-2021 using bibliometric methods. Methods: The Indian publications as listed in the Scopus database were identified by using “Quantum Optics” in the “Title” tag. Results: 67274 global publications emerged on the topic of “Quantum Optics” during 1996-2021. India contributed only 2108 publications on this topic and constituted a 3.13% share of global output. About 30.0% share of Indian publications received external funding support and were involved in international collaboration, respectively. The 455 organizations and 635 authors participated unevenly in the research on this topic, with the highest number of publications (96) emerging from the Indian Institute of Science, Bangalore, followed by the University of Calcutta (80 publications), Harish Chandra Research Institute, Allahabad (69 publications) and Tata Institute of Fundamental Research, Mumbai (68 publications). Indian Association for Cultivation of Science (IACS), Kolkata (69.9 and 5.68) registered the highest citation impact per paper and relative citation index, followed by Physical Research Laboratory, Ahmedabad (23.23 and 1.89), Harish Chandra Research Institute, Allahabad (22.93 and 1.86) and Tata Institute of Fundamental Research, Bombay (22.72 and 1.85). The highest number of publications (33) is contributed by G.S. Agarwal, followed by A.K. Pati (32 papers), A. Pathak (31 papers), and P.K. Panigrahi (29 papers). G.S. Agarwal (40.82 and 3.32) registered the highest citation impact per paper and relative citation index, followed by P.K. Panigrahi (21.83 and 1.77), A.K. Pati (21.06 and 1.71), and A. Pathak (19.87 and 1.61). The journals that published the highest number of publications (233) were Physical Review A (233 papers), Quantum Information Processing (109 papers), Physics Letters Section A (74 papers), and Spectrochimica Acta Part A (61 papers). Physical Review Letters (62.30) was the most impactful journal in terms of citations per paper, followed by the Journal of Optics (United Kingdom) (24.92), Physical Review E (19.07), and Journal of Optics B. Quantum &amp; Semiclassical Optics (18.85), Journal of Physical Chemistry C (18.58). The most commonly investigated topics (keywords) in terms of frequency of appearances were quantum optics (1390), followed by nonlinear optics (520), quantum theory (407), quantum entanglement (283)), photons (223), and quantum computers (223). Conclusion: Over the last two decades a large number of publications have emerged in the area of “Quantum Optics”, which are creating a significant impact on the development of many diverse quantum technologies both in India and abroad.

Beneficial Vs. Inhibiting Passivation By the Native Li SEI Revealed By Electrochemical Li+ Exchange

Li anodes represent a theoretical 10-fold upgrade over the capacity of graphite at comparable potential, and as such are key anode candidates for next-generation high energy density (> 1000 Wh/L) batteries. However, Li still falls below the 99.95-99.97% CE required for long-life cycling(1) and displays rate capability an order-of-magnitude lower than necessary for fast-charging (>2 C).(2) Interestingly, intrinsic Li0/Li+ redox has been reported to be more facile (j 0 > 10 mA/cm2)(3) than graphite intercalation (j 0 = 1-3 mA/cm2)(4). In spite of this, the chemical exchange of Li+ through the native solid electrolyte interphase (SEI) on Li is typically slow (0.5-3 mA/cm2),(5) and as such it can bottleneck Li+/Li0 redox(3) and increase charge-transfer resistance.(6) The SEI thus manifests itself by substantially decreasing the exchange current j 0 measured on Li down from its intrinsic kinetic value.(7) While multiple recent studies see j 0 as a relevant property in determining Li reversibility,(1) measuring j 0 in the presence of an SEI is not straightforward. Consequently, current literature presents widely varying numerical values of j 0 in the presence of an SEI, making it challenging to discern the relationship between j 0 and CE.To bridge this gap, Li+ exchange at the Li anode is here systematically quantified using cyclic voltammetry (CV) at slow scan rates and electrochemical impedance spectroscopy (EIS), both of which allow an SEI to develop natively. To avoid ambiguity with the intrinsic Li0/Li+ redox exchange current j 0, exchange rates are here interpreted in the framework of a “pseudo”-exchange current, j 0 p, that represents the total rate of Li+ exchange on the electrode. j 0 p was measured across a selection of historically-relevant and modern electrolytes, spanning low (78.0%) to high (99.3%) CE. In both methodologies, a strong dependence of j 0 p on electrolyte chemistry was identified. These differences reflect a strong correlation between CE and j 0 p, with electrolytes that display higher j 0 p typically also displaying higher CE. Upon cycling, a dynamic behavior of Li+ exchange on both Cu and Li were observed, with j 0 p typically increasing through cycling, attributed to morphological changes induced by non-uniform plating/stripping inherent to Li electrochemistry.(8) We will discuss the implications of this dynamic behavior on both the formation cycle on Cu, as well as how j 0 p changes report on SEI evolution during cycling. Finally, it was found that cycling Li with current densities j beyond j 0 p leads to substantial capacity loss and low CE, whereas electrolytes that can sustain high j 0 p are insensitive to j. Altogether, our results indicate that Li+ exchange plays a dominant role in determining the rate capability and CE of Li anodes, with high-j 0 p electrolytes displaying higher CE and better rate capability than their low-j 0 p counterparts. G. M. Hobold, J. Lopez, R. Guo, N. Minafra, A. Banerjee, Y. Shirley Meng, Y. Shao-Horn and B. M. Gallant, Nature Energy, 6, 951 (2021).P. Albertus, S. Babinec, S. Litzelman and A. Newman, Nature Energy, 3, 16 (2018).D. T. Boyle, X. Kong, A. Pei, P. E. Rudnicki, F. Shi, W. Huang, Z. Bao, J. Qin and Y. Cui, ACS Energy Letters, 5, 701 (2020).Y.-C. Chang, J.-H. Jong and G. T.-K. Fey, Journal of The Electrochemical Society, 147, 2033 (2000).A. B. Gunnarsdóttir, S. Vema, S. Menkin, L. E. Marbella and C. P. Grey, Journal of Materials Chemistry A, 8, 14975 (2020).A. Zaban, E. Zinigrad and D. Aurbach, The Journal of Physical Chemistry, 100, 3089 (1996).J. N. Butler, D. R. Cogley and J. C. Synnott, Journal of Physical Chemistry, 73, 4026 (1969).J. Z. Lee, T. A. Wynn, M. A. Schroeder, J. Alvarado, X. Wang, K. Xu and Y. S. Meng, ACS Energy Letters, 4, 489 (2019).