The Interplay of Structure and Dynamics in the Raman Spectrum of Liquid Water over the Full Frequency and Temperature Range

While many vibrational Raman spectroscopy studies of liquid water have investigated the temperature dependence of the high-frequency O-H stretching region, few have analyzed the changes in the Raman spectrum as a function of temperature over the entire spectral range. Here, we obtain the Raman spectra of water from its melting to boiling point, both experimentally and from simulations using an ab initio-trained machine learning potential. We use these to assign the Raman bands and show that the entire spectrum can be well described as a combination of two temperature-independent spectra. We then assess which spectral regions exhibit strong dependence on the local tetrahedral order in the liquid. Further, this work demonstrates that changes in this structural parameter can be used to elucidate the temperature dependence of the Raman spectrum of liquid water and provides a guide to the Raman features that signal water ordering in more complex aqueous systems

Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations

The transport of excess protons and hydroxide ions in water underlies numerous important chemical and biological processes. Accurately simulating the associated transport mechanisms ideally requires utilizing ab initio molecular dynamics simulations to model the bond breaking and formation involved in proton transfer and path-integral simulations to model the nuclear quantum effects relevant to light hydrogen atoms. These requirements result in a prohibitive computational cost, especially at the time and length scales needed to converge proton transport properties. Here, we present machine-learned potentials (MLPs) that can model both excess protons and hydroxide ions at the generalized gradient approximation and hybrid density functional theory levels of accuracy and use them to perform multiple nanoseconds of both classical and path-integral proton defect simulations at a fraction of the cost of the corresponding ab initio simulations. We show that the MLPs are able to reproduce ab initio trends and converge properties such as the diffusion coefficients of both excess protons and hydroxide ions. We use our multi-nanosecond simulations, which allow us to monitor large numbers of proton transfer events, to analyze the role of hypercoordination in the transport mechanism of the hydroxide ion and provide further evidence for the asymmetry in diffusion between excess protons and hydroxide ions

Impact of cell degradation on transport and structural properties of the cathodic catalyst layer in a PEMFC

Over the last decades, catalysts and ionomers have been significantly improved to increase the efficiency and lower the PGM content in PEMFCs. This reduction of PGM electrode loadings has a significant impact on performance and degradation due to local transport challenges near the catalyst surface, which is often only attributed to oxygen diffusion limitations. But up to the present date, it is not proven that this limitation is not also caused by oxygen convection or proton and water transport. Thus, the origin and importance of different transport limitations are still under discussion. The presented study applied a 500 h dynamic degradation test to a low Pt-loaded MEA and analyzed the impact of the applied load cycling to the transport and structural properties of the cathodic catalyst layer. This includes electrochemical analysis of the catalyst layer properties and identification of reasons for the appearing performance losses and changes in the transport limitations. Additionally, local AFM measurements are applied to evaluate structural changes in different positions of the cell and to improve the understanding of ionomer/catalyst interaction in the catalyst layer and the resulting changes during load cycling. The combination of different techniques enabled the detailed understanding of the degradation mechanisms causing the performance decay and can provide useful guidelines to design future PEMFC electrodes with significantly improved performance and durability. The project FURTHER-FC has received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under Grant Agreement No 875025. This Joint Undertaking receives support from the European Union’s Horizon 2020 Research and Innovation program, Hydrogen Europe and Hydrogen Europe Research

Experimental and numerical study on catalyst layer of polymer electrolyte membrane fuel cell prepared with diverse drying methods

High manufacturing cost is a major challenge to commercialization of the polymer electrolyte membrane fuel cell (PEMFC) technology in high volume market. Catalyst layer (CL) of PEMFC should incorporate high effective porosity, electrochemically active surface-area, gas permeability, and favorable ionomer distribution. Drying of the CL is a very significant step of electrode fabrication, and determines most of the properties mentioned above, but is rarely a subject of investigation. From various possible drying processes of CL, freeze-drying shows some beneficial properties, such as higher porosity, better ionomer distribution, and reduces the mass transport resistance significantly by allowing more reactant gas into reactive interface. In this work, the influence of diverse drying techniques on the microstructure and performance is investigated. Complementarily, a transient 2D physical continuum-model is used to investigate the effect of the structural properties on cell performance of electrodes prepared with different drying methods. A sensitivity analysis has been also performed to determine the influence of individual parameters applied in the model. Both of the experimental and simulation results stress on the fact that the freeze-drying technique not only significantly enhances the oxygen transport properties through ionomer but also improves the porosity along with the tortuosity of the CL microstructure

Magnesium Anode Protection by an Organic Artificial Solid Electrolyte Interphase for Magnesium-Sulfur Batteries

In the search for post-lithium battery systems, magnesium–sulfur batteries have attracted research attention in recent years due to their high potential energy density, raw material abundance, and low cost. Despite significant progress, the system still lacks cycling stability mainly associated with the ongoing parasitic reduction of sulfur at the anode surface, resulting in the loss of active materials and passivating surface layer formation on the anode. In addition to sulfur retention approaches on the cathode side, the protection of the reductive anode surface by an artificial solid electrolyte interphase (SEI) represents a promising approach, which contrarily does not impede the sulfur cathode kinetics. In this study, an organic coating approach based on ionomers and polymers is pursued to combine the desired properties of mechanical flexibility and high ionic conductivity while enabling a facile and energy-efficient preparation. Despite exhibiting higher polarization overpotentials in Mg–Mg cells, the charge overpotential in Mg–S cells was decreased by the coated anodes with the initial Coulombic efficiency being significantly increased. Consequently, the discharge capacity after 300 cycles applying an Aquivion/PVDF-coated Mg anode was twice that of a pristine Mg anode, indicating effective polysulfide repulsion from the Mg surface by the artificial SEI. This was backed by operando imaging during long-term OCV revealing a non-colored separator, i.e. mitigated self-discharge. While SEM, AFM, IR and XPS were applied to gain further insights into the surface morphology and composition, scalable coating techniques were investigated in addition to ensure practical relevance. Remarkably therein, the Mg anode preparation and all surface coatings were prepared under ambient conditions, which facilitates future electrode and cell assembly. Overall, this study highlights the important role of Mg anode coatings to improve the electrochemical performance of magnesium–sulfur batteries

The crustal stress field of Germany: a refined prediction

Information about the absolute stress state in the upper crust plays a crucial role in the planning and execution of, e.g., directional drilling, stimulation and exploitation of geothermal and hydrocarbon reservoirs. Since many of these applications are related to sediments, we present a refined geomechanical–numerical model for Germany with focus on sedimentary basins, able to predict the complete 3D stress tensor. The lateral resolution of the model is 2.5 km, the vertical resolution about 250 m. Our model contains 22 units with focus on the sedimentary layers parameterized with individual rock properties. The model results show an overall good fit with magnitude data of the minimum (S$_{hmin}$) and maximum horizontal stress (SS$_{Hmax}$) that are used for the model calibration. The mean of the absolute stress differences between these calibration data and the model results is 4.6 MPa for Shmin and 6.4 MPa for SS$_{Hmax}$. In addition, our predicted stress field shows good agreement to several supplementary in-situ data from the North German Basin, the Upper Rhine Graben and the Molasse Basin