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At least 271 records · Page 15

Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators under Mesh Refinement

This paper analyzes a popular computational framework to solve infinite-dimensional Bayesian inverse problems, discretizing the prior and the forward model in a finite-dimensional weighted inner product space. We demonstrate the benefit of working on a weighted space by establishing operator-norm bounds for finite element and graph-based discretizations of Matérn-type priors and deconvolution forward models. For linear-Gaussian inverse problems, we develop a general theory to characterize the error in the approximation to the posterior. We also embed the computational framework into ensemble Kalman methods and MAP estimators for nonlinear inverse problems. Furthermore, our operator-norm bounds for prior discretizations guarantee the scalability and accuracy of these algorithms under mesh refinement.

Bayesian inverse problem↗

Proton internal pressure from deeply virtual Compton scattering on collider kinematics

Abstract The unique experimental connection to the QCD energy–momentum tensor offered by generalised parton distributions has been strongly highlighted in the past few years with attempts to extract the pressure and shear forces distributions within the nucleon. If, in principle, this can be performed in a model independent way from experimental data, in practice, the current limited precision and kinematic coverage make such an extraction very challenging. Moreover, the limitation to a leading-order description in the strong coupling of the data has provided only an indirect and weakly sensitive access to gluon degrees of freedom, solely through their mixing to quarks via evolution. In this paper we address this issue by providing a next-to-leading order formalism allowing a reanalysis of global fits with genuine gluonic degrees of freedom. In addition, we provide an estimate of the reduction in uncertainty that could stem from the extended kinematic range relevant for the future Electron Ion Collider. Finally, we stress the connection between the analysis of the dispersion relation in terms of generalised parton distributions and the deconvolution problem.

Dutrieux, H. (ORCID:0000000183344885)↗

Sequential Electrochemical Flow Cell for Complex Multicomponent Electrocatalysis

A highly efficient flow cell for sequential electrolysis containing two complete electrochemical cells, capable of generating reactive species at the upstream working electrode and transporting them to the downstream working electrode, is demonstrated. Deconvolution of the intermixed electrode circuits is accomplished through analysis of the inherent resistance of the electrolyte, which allows for precise and independent control of the electrochemical potential at each electrode without altering concentrations of supporting or background electrolyte species. Sequential electrolysis involving oxidation of hydrogen and reduction of the generated protons downstream is demonstrated at nearly 100% efficiency on Pt-decorated dealloyed porous Nb catalysts. The conversion efficiency of the catalysts is discussed in terms of their geometries and active surface composition, elucidating strategies for use of sequential electrolysis cells for fundamental and applied studies.

25 ENERGY STORAGE↗

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗

Assessing Electrolyte Fluorination Impact on Calendar Aging of Blended Silicon-Graphite Lithium-Ion Cells Using Potentiostatic Holds

Silicon-based lithium-ion batteries have started to meet cycle life metrics, but they exhibit poor calendar life. Here, electrolyte fluorination impact on calendar fade of blended silicon-graphite anodes is explored using a LiPF 6 in EC:EMC:FEC electrolyte vs LiBOB in EC:EMC electrolyte. We utilize a combined experimental-modeling approach applying potentiostatic voltage holds (V-hold) to evaluate electrolyte suitability for calendar life in a shortened testing timeframe (~2 months). Our theoretical framework deconvolutes the irreversible parasitic capacity losses (lithium lost to the solid electrolyte interphase) from the V-hold electrochemical data. Unfluorinated electrolyte (dominant LiBOB reduction) exhibits higher cell resistance as compared to fluorinated electrolyte (dominant FEC reduction). Both systems have similar irreversible capacities during the voltage hold duration with slower rate of parasitic capacity loss for the LiBOB system. Extrapolation of the parasitic losses to end of life capacity fade of 20% shows LiBOB electrolyte outperforming LiPF 6 electrolyte in calendar life. The results demonstrate the applicability of the V-hold protocol as a rapid material screening tool providing semi-quantitative calendar lifetime estimates.

25 ENERGY STORAGE↗

Quantifying the Entropy and Enthalpy of Insertion Materials for Battery Applications Via the Multi-Species, Multi-Reaction Model

The entropy coefficient of a battery cell is the property that governs the amount of reversible heat that is generated during operation. In this work, we propose an extension of the Multi-Species, Multi-Reaction (MSMR) model to capture the entropy coefficient of a large format lithium-ion battery cell. We utilize the hybridized time-frequency domain analysis (HTFDA) method using a multi-functional calorimeter to probe the entropy coefficient of a large format pouch type lithium-ion battery with a NMC 811 cathode and a graphite anode. The measured entropy coefficient profile of the battery cell is deconvoluted into an entropy coefficient for each active material, which is then estimated using an extension of the MSMR model. Finally, we extend the entropy of a material to individual entropy for each gallery as treated by the model.

Electrochemistry↗

Design Trade-Offs in Composite Fuel Cell Membranes: Effects of Reinforcement and Chemical Additives

Perfluorosulfonic acid (PFSA) membranes are critical components in proton exchange membrane fuel cells, where performance depends on balancing ionic conductivity, mechanical durability, and chemical stability. This study characterizes a composite membrane (NC700) featuring PFSA-impregnated expanded polytetrafluoroethylene (ePTFE) reinforcement and cerium-based radical scavengers, benchmarked against unreinforced NR211. Complementary techniques, including electron microscopy, X-ray scattering, infrared spectroscopy, thermogravimetric analysis, and dynamic mechanical analysis, identify the structural and compositional strategies employed in NC700. Water sorption isotherms reveal lower water uptake for NC700 across all conditions, attributed to reinforcement and cerium incorporation. Reinforcement reduces in-plane swelling from 11% to 2.1% at 90% RH, confirming strong swelling anisotropy, while maintaining mechanical properties at elevated temperatures. While the ionic conductivity of NC700 is approximately 10% lower than that of NR211, the reduced thickness yields a 40% decrease in calculated area-specific resistance, suggesting the composite architecture can favorably shift the conductivity-stability trade-off. The composite structure also reduces gas permeability, indicating potential for improved separator function alongside favorable transport properties. Systematic deconvolution of reinforcement and additive contributions shows that conductivity losses from cerium incorporation are largely offset by gains from the lower equivalent-weight polymer, providing quantitative relationships that may guide composite membrane design for fuel cells and other electrochemical applications.

25 ENERGY STORAGE↗

Mathematical Modeling of Hydroxide-Exchange-Membrane Water Electrolyzer

Water electrolyzers can transform intermittent renewable energy like solar energy and wind energy into the chemical energy of hydrogen with zero greenhouse-gas emissions. The hydroxide-exchange membrane electrolyzer (HEME) combines the capability to produce pressurized hydrogen with the advantage of being able to use low or non-platinum group metal (PGM) electrocatalysts in the alkaline environment.1 Hydroxide salts, for example, KOH, are added to the HEME water feed on both anode and cathode to improve its performance. However, the specific mechanism of performance improvement still needs to be further understood. In addition, at high current densities, bubble evolution can result in mass-transport limitations, a less well studied phenomena. Mathematical modeling is ideal to explore these issues as it is cost and time efficient and can deconvolute the physics, processes, and observed phenomena and study the applied-voltage breakdown. In this work, we extend our previously developed 1D two-phase continuum model2 to study the varies processes in the HEME and provide insights on performance optimizations. First, the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) kinetics at different hydroxide concentrations have been studied by rotating disk electrodes (RDE) and implemented in the model. Then, the model is calibrated and validated against experimental HEME polarization curves for different KOH concentrations as a liquid electrolyte. The model clearly shows a performance increase with increasing KOH concentrations, which is consistent with the experimental results. The reduced ohmic resistance and increased electrochemical active surface area (ECSA) are the two main reasons for performance increase. The large amount of hydroxide in the liquid electrolyte not only helps to distribute the reactant hydroxide throughout the catalyst layer (CL), which reduces ohmic loss, but also enables reaction at the interface between the liquid electrolyte and electrocatalyst, which increases the ECSA. Applied-voltage breakdown demonstrates that the electrolyzer performance is dominated by anode kinetics and ohmic loss. A comparison with the DI water feed shows a more uniform current distribution in the anode CL when KOH is added, which indicates a higher utilization of the CL. Second, we present modeling on the effects of bubble coverage. As gas evolves, part of the ECSA is minimized due to bubble coverage. To account for this effect, an empirical relationship between the fractional bubble coverage and the current density is implemented in the model.3 The model shows this bubble coverage effect is more pronounced at large current densities with DI water feed. Acknowledgements This work was funded under the HydroGEN Consortium by the Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office, of the U. S. Department of Energy under contract number DE-AC02-05CH11231. References R. Abbasi, B. P. Setzler, S. Lin, J. Wang, Y. Zhao, H. Xu, B. Pivovar, B. Tian, X. Chen, G. Wu and Y. Yan, 31, 1805876 (2019). L. N. Stanislaw, M. R. Gerhardt and A. Z. Weber, ECS Transactions, 92, 767 (2019). H. Vogt and R. J. Balzer, Electrochimica Acta, 50, 2073 (2005).

Liu, Jiangjin↗

Current-Voltage Analysis Tool for Solar Fuel Production (CATS) v0.1

The program is expected to be a useful tool during operation of a range of solar-driven electrochemical devices, such as PV-electrolyzers and photoelectrochemical (PEC) devices. It makes use of current-voltage data collected during operation, operation parameters that are easily accessible for many devices of interest. The program captures the time-dependence of loss mechanisms at play during PEC device operation and opens the door for real-time optimizations of operational parameters like the feed humidity to minimize performance losses. Currently, the program is useful for applications where the current-voltage polarization response of the photoabsorber and electrolyzer are pre-recorded, and changes over time can be estimated based on the pre-recorded current-voltage scans. More complicated scenarios that involve permanent degradation of the PV component or complex calculations of the electrolyzer current-voltage characteristics may be included in future versions of this software. Aside from the possibility of deconvoluting loss mechanisms, this software can also reveal possible performance benefits by convective PV cooling when the photoabsorber is integrated into the electrolysis cell. The latter can highlight why certain device architectures may be beneficial over others. No similar technologies are known to the developer.

Kistler, Tobias↗

Colorectal Cancer Metastases in the Liver Establish Immunosuppressive Spatial Networking between Tumor-Associated SPP1 + Macrophages and Fibroblasts

Abstract Purpose: The liver is the most frequent metastatic site for colorectal cancer. Its microenvironment is modified to provide a niche that is conducive for colorectal cancer cell growth. This study focused on characterizing the cellular changes in the metastatic colorectal cancer (mCRC) liver tumor microenvironment (TME). Experimental Design: We analyzed a series of microsatellite stable (MSS) mCRCs to the liver, paired normal liver tissue, and peripheral blood mononuclear cells using single-cell RNA sequencing (scRNA-seq). We validated our findings using multiplexed spatial imaging and bulk gene expression with cell deconvolution. Results: We identified TME-specific SPP1-expressing macrophages with altered metabolism features, foam cell characteristics, and increased activity in extracellular matrix (ECM) organization. SPP1+ macrophages and fibroblasts expressed complementary ligand–receptor pairs with the potential to mutually influence their gene-expression programs. TME lacked dysfunctional CD8 T cells and contained regulatory T cells, indicative of immunosuppression. Spatial imaging validated these cell states in the TME. Moreover, TME macrophages and fibroblasts had close spatial proximity, which is a requirement for intercellular communication and networking. In an independent cohort of mCRCs in the liver, we confirmed the presence of SPP1+ macrophages and fibroblasts using gene-expression data. An increased proportion of TME fibroblasts was associated with the worst prognosis in these patients. Conclusions: We demonstrated that mCRC in the liver is characterized by transcriptional alterations of macrophages in the TME. Intercellular networking between macrophages and fibroblasts supports colorectal cancer growth in the immunosuppressed metastatic niche in the liver. These features can be used to target immune-checkpoint–resistant MSS tumors.

60 APPLIED LIFE SCIENCES↗

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗

Snapshot multifocal light field microscopy

Light field microscopy (LFM) is an emerging technology for high-speed wide-field 3D imaging by capturing 4D light field of 3D volumes. However, its 3D imaging capability comes at a cost of lateral resolution. In addition, the lateral resolution is not uniform across depth in the light field dconvolution reconstructions. To address these problems, here, we propose a snapshot multifocal light field microscopy (MFLFM) imaging method. The underlying concept of the MFLFM is to collect multiple focal shifted light fields simultaneously. We show that by focal stacking those focal shifted light fields, the depth-of-field (DOF) of the LFM can be further improved but without sacrificing the lateral resolution. Also, if all differently focused light fields are utilized together in the deconvolution, the MFLFM could achieve a high and uniform lateral resolution within a larger DOF. We present a house-built MFLFM system by placing a diffractive optical element at the Fourier plane of a conventional LFM. The optical performance of the MFLFM are analyzed and given. Both simulations and proof-of-principle experimental results are provided to demonstrate the effectiveness and benefits of the MFLFM. We believe that the proposed snapshot MFLFM has potential to enable high-speed and high resolution 3D imaging applications.

He, Kuan↗

Chirped-grating spectrometer-on-a-chip

We demonstrate an on-chip spectrometer readily integrable with CMOS electronics. The structure is comprised of a SiO 2 /Si 3 N 4 /SiO 2 waveguide atop a silicon substrate. A transversely chirped grating is fabricated, in a single-step optical lithography process, on a portion of the waveguide to provide angle and wavelength dependent coupling to the guided mode. The spectral and angular information is encoded in the spatial dependence of the grating period. A uniform pitch grating area, separated from the collection area by an unpatterned propagation region, provides the out-coupling to a CMOS detector array. A resolution of 0.3 nm at 633 nm with a spectral coverage tunable across the visible and NIR (to ∼ 1 µm limited by the Si photodetector) by changing the angle of incidence, is demonstrated without the need for any signal processing deconvolution. This on-chip spectrometer concept will cost effectively enable a broad range of applications that are beyond the reach of current integrated spectroscopic technologies.

Nezhadbadeh, Shima↗

Band-limited photodetection of temporal coherence

The quantum theory of optical coherence plays a ubiquitous role in identifying optical emitters. An unequivocal identification, however, presumes that the photon number statistics is resolved from timing uncertainties. We demonstrate from first principle that the observed nth-order temporal coherence is a n-fold convolution of the instrument responses and the expected coherence. The consequence is detrimental in which the photon number statistics is masked from the unresolved coherence signatures. The experimental investigations are thus far consistent with the theory developed. We envision the present theory will mitigate the false identification of optical emitters and enlarge the coherence deconvolution to an arbitrary order.

42 ENGINEERING↗

Understanding the Quadrupole Mass Filter and Testing a High-Resolution QMS RGA for ITER

A common type of residual gas analyzer is the quadrupole mass spectrometer. One of the main components within this instrument is a mass filter known as the quadrupole. It is responsible for the selective throughput of the ionized gas particles - by ascending mass number - prior to ion impacts on the analyzer (or detector) surface from which the ion current signal is generated for processing. However, the quadrupole is not fully described in relation to the electric field characteristics and the function as an ion mass separator. This paper describes the basic origins of the electrical design, the intricate assembly criteria, and performance of the quadrupole within the spectrometer. A specialized quadrupole mass spectrometer is part of a configuration for a diagnostic gas analyzer system planned for ITER, a fusion research machine. It has a verified capability, essential as a diagnostic criterion for this reactor project, to successfully deconvolute the mass signals of Helium-4 and deuterium (reactor fuel exhaust gases, separated by only 0.026 atomic mass units), down to a relative three-percent concentration of the former gas. The associated preliminary testing, performed at the Oak Ridge National Laboratory, is also addressed. Finally, one of the key parameters used to express gas concentration, the relative sensitivity factor, will be explained, including an evaluation of dependency on other variables.

Marcus, Chris [ORNL] (ORCID:0000000190139636)↗

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 3c Raw Data

XPS after 0hr of chronoampometry. Surface chemical composition and valence band structure of GaN were obtained by X-ray photoemission spectroscopy (XPS) on a Kratos Axis Ultra DLD system at a takeoff angle of 0° relative to the surface normal. An Al Kα source (hν = 1486.6 eV) was used to excite the core level electrons. Pass energy of 20 eV was used for the narrow scan of core levels and valence band spectra, and step size of 0.05 eV and 0.025 eV, respectively. The Spectral fitting was conducted using CasaXPS analysis software. The binding energy scales of all core levels were corrected to the N 1s of Ga – N bond at 397.8 eV. XPS O1s core level spectra from as-received Si/GaN sample, and deconvolution shows O - Ga bond and OH - H2O bond.

photocathode↗

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 3d Raw Data

XPS of Si/GaN photocathode after 1 hour chronoamperometry (CA) testing. Surface chemical composition and valence band structure of GaN were obtained by X-ray photoemission spectroscopy (XPS) on a Kratos Axis Ultra DLD system at a takeoff angle of 0° relative to the surface normal. An Al Kα source (hν = 1486.6 eV) was used to excite the core level electrons. Pass energy of 20 eV was used for the narrow scan of core levels and valence band spectra, and step size of 0.05 eV and 0.025 eV, respectively. The Spectral fitting was conducted using CasaXPS analysis software. The binding energy scales of all core levels were corrected to the N 1s of Ga – N bond at 397.8 eV. X-ray photoemission spectroscopy (XPS) O1s core level spectra from 1 hour chronoamperometry (CA) tested Si/GaN sample, and deconvolution shows O - Ga bond, O - N - Ga bond, and OH - H2O bond.

photocathode↗

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 3f Raw Data

XPS of Si/GaN photocathode after 10 hour chronoamperometry (CA) testing. Surface chemical composition and valence band structure of GaN were obtained by X-ray photoemission spectroscopy (XPS) on a Kratos Axis Ultra DLD system at a takeoff angle of 0° relative to the surface normal. An Al Kα source (hν = 1486.6 eV) was used to excite the core level electrons. Pass energy of 20 eV was used for the narrow scan of core levels and valence band spectra, and step size of 0.05 eV and 0.025 eV, respectively. The Spectral fitting was conducted using CasaXPS analysis software. The binding energy scales of all core levels were corrected to the N 1s of Ga – N bond at 397.8 eV. XPS O1s core level spectra from 10 hours CA tested Si/GaN sample, and deconvolution shows O - Ga bond, O - N - Ga bond and OH - H2O bond.

photocathode↗