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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ligand Locking on Quantum Dot Surfaces via a Mild Reactive Surface Treatment

At the outermost surface of colloidal QDs are organic surface ligands which dynamically bind and release in solution to control the growth kinetics, control the size/shape of the crystals, passivate surface states, and provide colloidal stability through favorable interactions with the solvent. However, the dynamicity comes at the expense of the stability of the QD suspension. Here, we show that ligands can be permanently locked on the QD surface by a thin layer of an inert metal oxide which forms within the ligand shell, over the headgroup. By interrogating the surface chemistry with different spectroscopic methods, we prove the ligand locking on the QD surface. As a result, an exceptional stability of the coated QD inks is achieved in a wide concentration range, even in the presence of chemically competing surface ligands in solution. We anticipate that this critical breakthrough will benefit different areas related to colloidal QDs, spanning from single-particle studies to displays and solar cells and biological applications. Furthermore, the same chemistry could be easily translated to surface treatments of bulk materials and thin films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effects of groundwater pumping on ground surface temperature: A regional modeling study in the North China Plain

Over-exploitation of groundwater (GW) in the North China Plain (NCP) since the 1960s has many environmental consequences. However, understanding of the dominant mechanisms remains limited, particularly at regional scale. In this study, the coupled ParFlow.CLM model representing subsurface and land-surface processes and their interactions was applied in the NCP at high spatio-temporal resolutions. The model was validated using the water and energy fluxes reported in previous studies and from the JRA-55 reanalysis. Numerical experiments were designed to examine the relative impacts of GW pumping and irrigation on the ground surface temperature (GST). Results show significant effects of GW pumping on GST in the NCP. Generally, the subsurface acts as a buffer to temporal variations in heat fluxes at the land-surface, but long-term pumping can gradually weaken this buffer, resulting in increases in the spatio-temporal variability of GST, as exemplified by hotter summers and colder winters. Considering that changes of water table depth (WTD) can significantly affect land surface heat fluxes when WTD ranges roughly between 0.01–10 m, the 0.5 m/year increase of WTD simulated by the model due to pumping can continue to increase the average WTD and hence, disturb GST, for about 20 years from the pre-pumping WTD in the NCP, before the WTD exceeds 10 m. The variations of GST are expected to be faster initially and gradually slow down due to the nonlinear behaviors of GST with WTD. The findings from this study in the NCP may also have implications for other regions with GW depletion.

Yang, Chen↗
DOE OSTI2020

Strong surface magnetic field generation in relativistic short pulse laser–plasma interaction with an applied seed magnetic field

Abstract While plasma often behaves diamagnetically, we demonstrate that the laser irradiation of a thin opaque target with an embedded target-transverse seed magnetic field B seed can trigger the generation of an order-of-magnitude stronger magnetic field with opposite sign at the target surface. Strong surface field generation occurs when the laser pulse is relativistically intense and results from the currents associated with the cyclotron rotation of laser-heated electrons transiting through the target and the compensating current of cold electrons. We derive a predictive scaling for this surface field generation, B gen ∼ −2 πB seed Δ x / λ 0 (in the large spot size limit), where Δ x is the target thickness and λ 0 is the laser wavelength, and conduct 1D and 2D particle-in-cell simulations to confirm its applicability over a wide range of conditions. We additionally demonstrate that both the seed and surface-generated magnetic fields can have a strong impact on application-relevant plasma dynamics, for example substantially altering the overall expansion and ion acceleration from a μ m-thick laser-irradiated target with a kilotesla-level seed magnetic field.

Weichman, K. (ORCID:0000000234877922)↗
DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗
DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Processing aluminum alloy with hybrid wire arc additive manufacturing and ultrasonic nanocrystalline surface modification to improve porosity, surface finish, and hardness

Here, in this paper, a novel hybrid wire arc additive manufacturing (WAAM) and ultrasonic nanocrystal surface modification (UNSM) on porosity manipulation and surface properties of aluminum 5356 alloys was studied. The goal is to improve the quality of the WAAM-built part by eliminating bigger pores and reducing its size, reducing surface roughness, and increasing surface hardness. The as-built WAAM and WAAM-UNSM-treated samples were quantitatively studied for porosity using an X-ray micro-computed tomography (μ-CT). The surface roughness was measured on the surface profile of the same samples before and after UNSM treatment. Followed by the Vickers micro-hardness tests to evaluate the hardness modified by the influence of the UNSM treatment. It was found that the bigger pores in the as-built WAAM samples were eliminated and the medium-sized pores were shrunk to almost half the size after the UNSM treatment. Further, the UNSM treatment showed a significant improvement in both surface roughness and hardness on the WAAM Al5356 samples. This experimental work demonstrates the critical advantages of hybrid WAAM-UNSM in improving the qualities of the WAAM processed parts.

Hardness↗
DOE OSTI2022

Effect of applied potential on metal surfaces: Surface energy, Wulff shape and charge distribution

Here we use grand canonical density functional theory to predict the surface energies, Wulff shapes, charge distributions and catalytically active sites of different metal surfaces under electrochemical conditions. We propose a method for computing surface energies from grand canonical density functional theory (GC-DFT) calculations of periodic slab models and use it to compute the surface energies of the facets of Pt, Cu, and Ag crystals to predict their Wulff shapes under electrochemical conditions. GC-DFT predicts that, for the pure metals studied, solvation only slightly affects the Wulff shape while applied potentials considerably affect the surface energies and corresponding Wulff shapes. We used Bader charge analysis of GC-DFT computed electron densities to investigate the effect of applied potential on the distribution of electron density over the atoms of the surfaces of Pt, Cu, Ag, and the 75–25 Ag-Pt and Au-Ni alloys. This analysis shows that, under an applied potential, the electron density is unevenly distributed over the surface atoms and that the charges of atoms more exposed to solvent are more sensitive to bias. Our results show that the most sensitive atom to bias can be used to identify the most favorable adsorption site and thus, the active sites of electrochemical reactions, which is computationally less demanding than calculating the adsorption energies on all possible adsorption sites.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of surface chemistry on Li nucleation energetics on graphene-based surfaces

Lithium metal is a promising high-capacity anode material for solid-state batteries, but it typically suffers from poor cyclability. Carbon scaffold hosts have the potential to improve this performance due to their high electronic conductivity and large surface area, which facilitates lithium-ion adsorption and desorption. Scaffold surface chemistry is known to significantly influence performance outcomes, but the details of these interactions are not fully understood. Here, this study employs first-principles simulations to explore lithium transport and nucleation on graphene anodes with various surface chemistries. Using enhanced sampling techniques, ab initio molecular dynamics, and density functional theory calculations, we find that although surface chemistry has a minimal impact on lithium interfacial transport, it influences surface nucleation significantly. Both heteroatom dopants and intrinsic defects lower the nucleation barrier, creating a more favorable environment for lithium nucleation compared to pristine graphene. In addition, our results reveal a complex interplay between surface lithium concentration, lithium transport, and nucleation kinetics. These findings highlight the potential of surface modifications to precisely control nucleation processes on carbon-based anodes and provide design guidance for reducing dendrite formation and improving the cycle life of solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparison of Surface Tension Generation Methods in Smoothed Particle Hydrodynamics for Dynamic Systems

Developing robust numerical models of dynamic surface tension dominated multiphase systems is an ongoing challenge, especially in scenarios with large density and viscosity ratios. This is critical to the design and understanding of various physical and engineering systems, such as fluidized beds, fuel injectors, and drug delivery schemes. Much of the computational work in surface tension dominated multiphase flows has employed the continuum surface force method (CSF) of Brackbill et al. [1], which recasts surface tension from a surface force to a volumetric force that can be imposed in the vicinity of an interface. The CSF method produces accurate results across a variety of systems, however it relies on the identication of surface normals, which can be unreliable under certain conditions. Alternative methods of simulating surface tension have been proposed. Here the advantages and disadvantages of the CSF method in comparison to a pairwise forces (PF) method proposed by Tartakovsky and Panchenko [2] are explored. The CSF and PF methods are used in a smoothed particle hydrodynamics (SPH) framework to model dynamic systems. Results are compared to existing test cases from the literature and to analytic solutions derived from fundamental normal mode behavior of bubbles and droplets. A physical system for which the PF method is more stable and physically appropriate than the CSF method is identied.

smoothed particle hydrodynamics, multiphase flow↗
DOE OSTI2025

Selective Adsorption of Thiol-Containing Molecules on Copper Sulfide Surfaces via Molecule–Surface Disulfide Bridges

Recent results in the fields of nanoenhanced agriculture and expanding interest in prebiotic chemistry have placed increased emphasis on understanding the chemically selective interaction of small molecules with the surfaces of metal sulfides. Here, we present an integrated experimental and computational study of the interaction of thiol-containing molecules with copper sulfide (covellite) surfaces in aqueous media. In situ Fourier-transform infrared (FTIR) measurements and ex situ X-ray photoelectron spectroscopy (XPS) measurements show that molecules bearing free thiol groups, including glutathione and cysteine, bind strongly to CuS (covellite) nanoparticles and to CuS (001) single crystals, while control studies show that similar molecules lacking the free thiol group exhibit much less binding. Additional experiments show that these thiol-containing molecules interact transiently with CuO nanoparticle surfaces but are readily removed by rinsing. The FTIR and XPS experiments demonstrate that adsorption of molecular thiols to CuS surfaces occurs in a chemically selective manner. Further experimental studies and density functional calculations show that the preferred mode of binding is through the surface S atoms, forming a Solid–S–S–Molecule disulfide linkage. While the role of disulfide linkages in controlling structure and function of proteins and other biomolecules is widely known, the formation of surface disulfide linkages as a motif for covalent molecular binding at surfaces has not been established previously.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Methanol Partial Oxidation on Cu(111) and PtCu(111) Single-Atom Alloy Surfaces: Effect of Surface Oxygen Coverage on Selectivity

The selective oxidation of methanol to formaldehyde on Cu surfaces is an important and well-studied reaction. However, a systematic analysis of product selectivity as a function of oxygen coverage on Cu(111) and Cu-based single-atom alloys (SAAs) has not been previously reported. In this work, we present a comprehensive investigation of deuterated methanol (CD 3 OH) partial oxidation on Cu(111) and 1% PtCu(111) SAA surfaces as a function of preadsorbed oxygen coverage. Temperature-programmed desorption (TPD) and X-ray photoelectron spectroscopy (XPS) reveal that isolated Pt atoms inhibit the initial surface oxidation of Cu(111) under low oxygen exposures. Despite this difference in oxidation kinetics, the product selectivity remains largely unaffected: on both Cu(111) and PtCu(111), formaldehyde (CD 2 O) is the predominant partial oxidation product over a broad range of oxygen coverages. The selectivity toward formaldehyde peaks at intermediate oxygen coverages (∼0.3 monolayers, ML), indicating the existence of an optimal oxygen loading for partial oxidation. Notably, the similar product selectivities on Cu(111) and PtCu(111) over a range of surface oxygen coverage indicate that Pt single atoms do not significantly alter the reaction pathway or shift the optimal oxygen coverage for formaldehyde formation. Control experiments confirm that Cu(111) is unreactive toward methanol in the absence of oxygen, while PtCu(111) surfaces produce a small amount of formaldehyde even when oxygen is not preadsorbed, indicating that isolated Pt atoms facilitate O−H activation at below 150 K, leading to H 2 desorption, followed by C−D activation at higher temperatures (∼350 K). Density functional theory (DFT)-based calculations show that Pt atoms increase the O 2 dissociation barrier relative to Cu(111), consistent with the observed inhibition of oxidation at low exposures. Overall, this work provides the first detailed selectivity map for methanol oxidation on oxidized Cu(111) and PtCu(111) SAA surfaces. By linking classical mechanistic insights such as methoxy- and formate-mediated pathways with single-atom alloy catalyst design, this work demonstrates that while Pt substitution modulates the oxidation kinetics and oxygen binding, the overall selectivity toward formaldehyde is governed primarily by oxygen coverage. These findings underscore the potential of isolated dopants to tune surface oxidation behavior without compromising the intrinsic partial oxidation selectivity of copper-based catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reduction of Oxidized Pd/Ag(111) Surfaces by H 2 : Sensitivity to PdO Island Size and Dispersion

Understanding the migration of species across interfaces in bimetallic systems is key to exploiting their bifunctionality for chemical reactivity and heterogeneous catalysis. The present study demonstrates that the sizes and dispersion of oxidized Pd islands present on oxidized Ag(111) in addition to the concentration of active Pd sites have a significant influence on the rate of surface reduction by H 2 . Two distinct types of Pd oxide islands were generated for this investigation and characterized using X-ray photoelectron spectroscopy and scanning tunneling microscopy. Small, uniformly-dispersed PdO x islands (1-5 nm diameter) were created by depositing Pd onto AgO x surfaces, while larger, non-uniformly dispersed PdO x agglomerates (30-50 nm) were produced by depositing Pd on Ag(111) prior to oxidizing. Based on X-ray photoelectron spectroscopy, the small PdO x islands have a higher concentration of undercoordinated Pd atoms than the large agglomerates. Both types of PdO x are found to dramatically enhance the reduction of AgO x by H 2 at 300 K due to the ability of the PdO x to dissociate H 2 ; the pure AgO x surfaces are unreactive toward H 2 . The rate of reduction at 300 K is found to be 2-4 times larger for the AgO x surface covered by small, uniformly dispersed PdO x islands. The higher reactivity of this surface is attributed to enhanced migration of oxygen and hydrogen atoms between the PdO x and AgO x phases due to the sizes and high dispersion of the small PdO islands as well as the higher concentration of active Pd sites on the PdO x . Furthermore, the results of this study demonstrate that reactant migration between co-existing surface phases is highly sensitive to both the intrinsic chemical activity and morphological properties of the active phase (PdO x ) and reveal that these properties can be significantly influenced by the method of synthesizing the oxidized bimetallic surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Topological surface states on the nonpolar (110) and (111) surfaces of SmB 6

In order to clarify the controversial issue of the topological nature in a mixed-valent Kondo system, SmB 6 , we have explored the surface states on the nonpolar (110) surface of SmB 6 , employing both angle-resolved photoemission spectroscopy (ARPES) experiment and ab initio density-functional theory (DFT) band calculations. Based on ARPES spectroscopic fingerprints and the DFT surface band structures, we ascribe the observed spectral weights at $\bar{X}$ and $\bar{Y}$ on the (110) surface Brillouin zone to topological surface states (TSSs) of “topological insulator (TI)” nature and of “topological crystalline insulator (TCI)” nature, respectively. With varying the chemical potential, the double Dirac cones of the TCI nature exhibit a Lifshitz transition of Fermi surfaces with intriguing spin textures. Further, we have also examined the TSSs on the nearly nonpolar (111) surface of SmB 6 in connection with a recently reported ARPES result and proposed a way to probe the Dirac points that are buried in the bulk-projected bands.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Surface Wettability Analysis from Adsorption Energy and Surface Electrical Charge

Surface wettability is determined by the attraction of a liquid phase to a solid surface. It is typically quantified by using contact angle measurements at mineral surfaces in the case of the flotation of mineral particles. Contact angle research to describe wettability has been investigated at different scales by sessile drop measurements, molecular dynamic simulation, and atomic force microscopy. In this study, the density functional theory (DFT) was employed for predicting the surface free energy and contact angles of a well-known hydrophobic phyllosilicate mineral talc and a well-known hydrophilic phyllosilicate mineral muscovite based on the calculated interfacial energy and surface charge. The results revealed that the predicted contact angle at the atomic scale was larger than the experimental value, and identified two interactions: electrostatic interaction and hydrogen bonding, between the hydrophilic muscovite surface and the water layer, while a water-exclusion zone of 3.346 Å was found between the hydrophobic talc surface and the first water layer. This investigation gives a new perspective for wettability determination at the atomic scale.

Geochemistry & Geophysics↗
DOE OSTI2021

Droplet Evaporation on Hot Micro-Structured Superhydrophobic Surfaces: Analysis of Evaporation from Droplet Cap and Base Surfaces

In this study, evaporation of sessile water droplets on hot micro-structured superhydrophobic surfaces is experimentally and theoretically investigated. Water droplets of 4 µL are placed on micro-pillared silicon substrates with the substrate temperature heated up to 120°C. A comprehensive thermal circuit model is developed to analyze the effects of substrate roughness and substrate temperature on the sessile droplet evaporation. For the first time, two components of heat and mass transfer, i.e., one from the droplet cap surface and the other from the droplet base surface, during droplet evaporation are distinguished and systematically studied. As such, the evaporation heat transfer rates from both the droplet cap surface and the interstitial liquid-vapor interface between micropillars at the droplet base are calculated in various conditions. For droplet evaporation on the heated substrates in the range of 40°C – 80°C, the predicted droplet cap temperature matches well with the experimental results. Furthermore, during the constant contact radius mode of droplet evaporation, the decrease of evaporation rate from the droplet base contributes most to the continuously decreasing overall evaporation heat transfer rate, whereas the decrease of evaporation rate from the droplet cap surface is dominant in the constant contact angle mode. The influence of internal fluid flow is considered for droplet evaporation on substrates heated above 100°C, and an effective thermal conductivity is adopted as a correction factor to account for the effect of convection heat transfer inside the droplet. Temperature differences between the droplet base and the substrate base are estimated to be about 2°C, 5°C, 8°C, 13°C and 18°C for droplet evaporation on substrates heated at 40°C, 60°C, 80°C, 100°C, and 120°C, respectively, elucidating the delayed or depressed boiling of water droplets on a heated rough surface due to evaporative cooling.

42 ENGINEERING↗
DOE OSTI2023

Tomographic optical emission spectroscopy of an atmospheric pressure plasma jet and surface ionization waves on planar and structured surfaces

Here in this paper, an approach for 3D plasma structure diagnostics using tomographic optical emission spectroscopy (Tomo-OES) of a nanosecond pulsed atmospheric pressure plasma jet (APPJ) is presented. In contrast to the well-known Abel inversion, Tomo-OES does not require cylindrical symmetry to recover 3D distributions of plasma light emission. Instead, many 2D angular projections are measured with intensified cameras and the multiplicative algebraic reconstruction technique is used to recover the 3D distribution of light emission. This approach solves the line-of-sight integration problem inherent to optical diagnostics, allowing recovery of localized OES information within the plasma that can be used to better infer plasma parameters within complex plasma structures. Here, Tomo-OES was applied to investigate an APPJ operated with helium in ambient air and impinging on planar and structured dielectric surfaces. Surface charging caused the guided streamer from the APPJ to transition to a surface ionization wave (SIW) that propagated along the surface. The SIW experienced variable geometrical and electrical material properties as it propagated, leading to 3D configurations that were non-symmetric and spatially complex. Light emission from He, N$_2^+$, and N2 were imaged at ten angular projections and the respective time-resolved 3D emission distributions in the plasma were then reconstructed. The spatial resolution of each tomographic reconstruction was 7.4 µm and the temporal resolution was 5 ns, sufficient to observe the guided streamer and the effects of the structured surface on the SIW. Emission from He showed the core of the jet and emission from N$_2^+$ and N2 indicated effects of entrainment of ambient air. Penning ionization of N2 created a ring or outer layer of N$_2^+$ that spatially converged to form the 'plasma bullet' or spatially diverged across a surface as part of a SIW. The SIW entered trenches of size 150 µm, leading to decreases in plasma light emission in regions above the trenches. The plasma light emission was higher in some regions with trenches, possibly due to effects of field enhancement.

plasma interactions with complex surfaces↗
DOE OSTI2021

In Situ ATR-FTIR Study of the Cathode–Electrolyte Interphase: Electrolyte Solution Structure, Transition Metal Redox, and Surface Layer Evolution

We present a study of the lithium nickel manganese cobalt oxide (LiNi 0.6 Mn 0.2 Co 0.2 O 2 , NMC622) cathode-electrolyte interphase (CEI) during galvanostatic charging and discharging using in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) methods to investigate the voltage dependent electrolyte solution structure changes at the interface, transition metal (TM) redox chemistry, and cathode/electrolyte interfacial layer evolution. Furthermore, our in situ cell design provides both reliable electrochemical device testing and strong FTIR vibrational absorption signals near the cathode surface. Specifically, advanced spectral analysis elucidates changes of near-surface Li+ ion (de)solvation by solvent molecules during galvanostatic cycling. Moreover, cathode metal-oxygen vibrational absorptions, sensitive to TM redox behaviors and subsequent local structural variations, were correlated to cathode de-lithiation (and lithiation) and electrolyte solution structure changes. In addition, we have detected the formation and evolution of a CEI surface layer on the NMC622 cathode that contributes to the cell's capacity fade.

25 ENERGY STORAGE↗