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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tailoring Fibre Structure Enabled by X-ray Analytics for Targeted Biomedical Applications

The rising interest in designing fibres via spinning techniques combining the properties of various polymeric materials into advanced functionalised materials is directed towards targeted biomedical applications such as drug delivery, wearable sensors or tissue engineering. Understanding how these functional polymers exhibit multiscale structures ranging from the molecular level to nano-, micro-and millimetre scale is a key prerequisite for their challenging applications that can be addressed by a non-destructive X-ray based analytical approach. X-ray multimodalities combining X-ray imaging, scattering and diffraction allow the study of morphology, molecular structure, and the analysis of nano-domain size and shape, crystallinity and preferential orientation in 3D arrangements. The incorporation of X-ray analytics in the design process of polymeric fibers via their nanostructure under non-ambient conditions (i.e. temperature, mechanical load, humidity…) allows for efficient optimization of the fabrication process as well as quality control along the product lifetime under operating environmental conditions. Here, we demonstrate the successful collaboration between the laboratory of Biomimetic Textiles and Membranes and the Center of X-ray Analytics at Empa for the design, characterisation and optimisation of advanced functionalised polymeric fibrous material systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Analytical Tools to Assess Polymer Biodegradation: A Critical Review and Recommendations

Many petroleum-derived plastic materials are highly recalcitrant and persistent in the environment, posing significant threats to human and ecological receptors due to their accumulation in ecosystems. In recent years, research efforts have focused on advancing biological methods for polymer degradation. Enzymatic depolymerization has emerged as particularly relevant for biobased plastic recycling, potentially scalable for industrial use. Biodegradation involves adsorption to the plastic solid surface, followed by an interfacial reaction, resulting in cleavage of bonds of polymer chains exposed on the surface. Here, widely varying substrate-specific kinetics are observed, with the polymer’s properties possessing a significant impact on the rate of this interfacial catalysis. Thus, there is a critical need for sensitive and accurate characterization of the material surface during and after interfacial depolymerization to fully understand the reaction mechanisms. Here, we provide a critical review of a range of techniques used in the analysis of material surfaces to characterize the chemical, topological, and morphological features relevant to the study of enzymatic biocatalysis, including microscopy techniques, spectroscopic techniques (e.g., X-ray diffraction analysis, Fourier transform infrared attenuated total reflectance spectroscopy, and mass spectrometry detection of analytes associated with degradation). Techniques for evaluation of surface energy and topology in their relevancy for sensitive detection of biological surface modifications are also discussed. In addition, this paper provides an overview of the strengths of these techniques and compares their performance in both sensitivity and throughput, including emerging techniques, which can be useful, particularly for the rapid analysis of the surface properties of polymeric materials in high-throughput screening of candidate biocatalysts. This research serves as a starting point in selecting and applying appropriate methodologies that provide direct evidence to the ongoing biotic degradation of polymeric materials.

Colachis, Matthew↗
DOE OSTI2023

Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes

Lagrangian particle tracking schemes allow a wide range of flow and transport processes to be simulated accurately, but a major challenge is numerically implementing the inter-particle interactions in an efficient manner. This article develops a multi-dimensional, parallelized domain decomposition (DDC) strategy for mass-transfer particle tracking (MTPT) methods in which particles exchange mass dynamically. We show that this can be efficiently parallelized by employing large numbers of CPU cores to accelerate run times. In order to validate the approach and our theoretical predictions we focus our efforts on a well-known benchmark problem with pure diffusion, where analytical solutions in any number of dimensions are well established. In this work, we investigate different procedures for “tiling” the domain in two and three dimensions (2-D and 3-D), as this type of formal DDC construction is currently limited to 1-D. An optimal tiling is prescribed based on physical problem parameters and the number of available CPU cores, as each tiling provides distinct results in both accuracy and run time. We further extend the most efficient technique to 3-D for comparison, leading to an analytical discussion of the effect of dimensionality on strategies for implementing DDC schemes. Increasing computational resources (cores) within the DDC method produces a trade-off between inter-node communication and on-node work. For an optimally subdivided diffusion problem, the 2-D parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to around 2700 cores, reducing a 5 h simulation to 8 s, while the 3-D algorithm maintains appreciable speedup up to 1700 cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Understanding Biomass and Polymer Feedstock Variability Through Analytical Pyrolysis and Two Dimensional Gas Chromatography and Mass Spectrometry

Moving toward a circular carbon economy requires enabling reuse of carbon-based macromolecules like those in biomass and polymers. Meeting this goal requires increased upcycling of waste products into higher value products. For biomass waste such as corn stover, pine needles, or bark, one approach is using pyrolysis to convert these feedstocks into bio-oil that can be used for liquid fuel or transformed into other hydrocarbon based products, like bio-polymers. Waste plastics can be upcycled or recycled into new products, or alternatively converted into bio-oil by pyrolysis. Macromolecules from biomass and polymers are challenging to convert into liquid fuel or chemical feedstocks, due to large and sometimes heterogeneous networks of polymeric bonds. We work with the Idaho National Laboratory’s Biomass Feedstock National User Facility and Department of Energy’s Feedstock Conversion Interface Consortium to develop a molecular understanding of biomass variability that occurs naturally and as a result of storage or preprocessing techniques applied to feedstocks, to understand chemical reactions occurring during pyrolysis and other biomass or polymer conversion techniques. Using two dimensional gas chromatography mass spectrometry coupled to analytical pyrolysis provides insight into the molecular changes that occur during the pyrolysis event, and these insights can extend to bench or pilot scale pyrolysis conversions. Understanding pyrolysis of biomass and polymers at a molecular level contributes to development of new tools to predict and manipulate the optimum conditions and identify the best storage, preprocessing, and conversion techniques to maximize output of specific high-value chemical species in the conversion to fuels, or to characterize feedstocks for blending before pyrolysis. Identification and understanding of the molecular level changes resulting from novel preprocessing techniques that can be used to control and manipulate the chemical output of bench or pilot scale pyrolysis is another focus of investigation, including the use of gamma irradiation, acid, or enzyme pre-treatments. We also focus on the impacts of storage conditions and techniques, which can affect moisture levels, degradation, and impacts from naturally occurring microbes in the environment.

09 BIOMASS FUELS↗
DOE OSTI2025

Efficient Measurement of Length Distribution of 1D Nanoparticles in Solution via Optical Polarimetry

The efficient measurement of the length distribution of nanotubes, nanowires, and other one-dimensional (1D) nanoparticles in solution is important to enable their incorporation into materials and devices and to optimize their processing for properties of interest, such as thermal/electrical conductivity or mechanical strength, in suspensions and composites. We report an electric-field (E-field)-assisted optical-polarimetry technique to measure the length distribution of ensembles of high-aspect-ratio particles in dilute suspension. The degree of alignment of polarizable 1D particles suspended in a fluid under Brownian motion explicitly depends on the E-field strength and the particle length. We show that it is possible to extract the length distribution of 1D nanoparticles suspended in an insulating fluid by applying a range of E-fields and using optical polarimetry to measure the corresponding alignment order parameter. Notably, the method is relatively insensitive to the diameter of the 1D particles, which can be poorly known or vary within a sample. The technique is validated with silver nanowires and carbon nanotubes of known lengths, as well as polymer-depletion-length-separated single-wall carbon nanotube samples with length distributions independently measured with analytical ultracentrifugation. Finally, we demonstrate the ability of the optical-polarimetry technique to quantify changes in the length distribution of ultranarrow, sub-nanometer-diameter single-wall carbon nanotubes under different types and durations of ultrasonication. Within its range of applicability (polarizable 1D nanoparticles in the 0.5 to 15 μm length range, constrained by the voltage stability of the media and the suspended particles), the E-field-assisted optical-polarimetry method is a particularly efficient and accurate method to measure the length distribution of nanowires and nanotubes in suspension.

1D nanoparticles↗
DOE OSTI2024

Quantifying Uncertainty in HPC Job Queue Time Predictions

High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.

HPC↗
DOE OSTI2021

Temporal characterization of fundamental plasma parameters in pulsed liquid electrode plasma (LEP) optical emission spectrometry

The fundamental characteristics of liquid electrode plasma (LEP), a pulsed plasma source for optical emission spectrometry, were investigated. Two distinct phases were observed during the process of pulsed plasma generation, namely bubble generation and active plasma discharge. Additionally the ionization efficiency of the LEP, with Mg as a representative analyte, was gauged from the ratio of Mg II 279.553 nm to Mg I 285.213 nm emission and was found to increase from about 5% to 20% in a close-to-linear fashion with the discharge voltage from 800 V to 1200 V. The Mg II/Mg I ratio of the LEP was 2.5 to 3 orders of magnitude less than that typically offered by an inductively coupled plasma (ICP) but was comparable to other solution-based glow discharges. It was found that an off-time interval of more than 150 ms between successive discharge pulses was required to obtain a stable pulse-to-pulse discharge current. Temporally resolved emissions of Mg II 279.6 nm, Mg I 285.2 nm, Fe I 373.5 nm, OH band head at 306 nm, and Hα line at 656.3 nm showed that the background species (OH band and Hα line) reached their maximum emission intensities at around 0.5 ms to 0.7 ms with respect to the onset of the discharge pulse whereas the maximum emissions were observed between 0.7 ms to 0.9 ms for analyte species (Mg and Fe lines). The electron density observed in the present work was in the range from 5.7 × 10 15 cm -3 to 8.2 × 10 15 cm -3 , which was similar to those found in an analytical ICP. The temporal averaged OH rotational temperature was 3300 K, which was comparable to the values of an analytical ICP and solution-based glow discharges. By contrast, the temporally averaged Fe I excitation temperature was around 8900 K, which was even higher than that of an analytical ICP and roughly triple the values obtained by techniques based on glow discharge of liquid samples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Tuning Solid Electrolyte Interphase Formation before Plating Onset in Anode-Free Sodium Batteries

Sodium (Na) batteries are of growing interest due to the higher earth abundance of sodium than lithium, as well as their promising theoretical energy density when metallic Na anodes are used. However, Na plating and stripping are heavily influenced by the physicochemical properties of the solid electrolyte interphase (SEI), which is directly influenced by the solvent and salt used for the electrolyte. While most studies focus on the SEI that forms on the surface of Na metal after plating, we expand this analysis by identifying a nanoscale “pre-plating” SEI that forms on the current collector (CC) prior to the onset of Na plating. Here, we systematically investigate an array of Na salt and glyme solvents in the electrolyte and determine the associated impacts on pre-plating SEI formation on aluminum CCs. By combining analytical electrochemistry approaches with a multimodal suite of spectroscopy techniques (X-ray, infrared, and Raman), supported by density functional theory calculations, we reveal a direct correlation between the Na + coordination environment and pre-plating SEI composition. We find that longer-chain glymes produce larger proportions of organic alkoxide products in the interphase, consistent with increased Na + −glyme interactions, while the fraction of salt-derived inorganic products (e.g., NaF) correlates with Na + −anion coordination. These insights highlight the critical influence of electrolyte composition particularly solvent identity and Na + coordination on the initial SEI formation in anode-free Na batteries.

anode-free batteries↗
DOE OSTI2021

Fractional Laplacian spectral approach to turbulence in a dusty plasma monolayer

This work presents an analytical investigation of anomalous diffusion and turbulence in a dusty plasma monolayer, where energy transport across scales leads to the spontaneous formation of spatially disordered patterns. Many-body simulations of 10,000-particle dusty plasma monolayers are used to demonstrate how the global dynamics depend on the statistical properties of the dust assembly for realistic laboratory conditions. We find that disorder due to variations in the dust size distribution and charge-driven nonlocal interactions resulting in anomalous dust diffusion are key factors for the onset of instabilities. The resulting dynamics exhibit features of inertial turbulence over slightly more than half a decade of scales proportional or smaller than the Debye shielding length. These processes are examined analytically using a recently developed Fractional Laplacian Spectral (FLS) technique, which identifies the active energy channels as a function of scale, disorder concentration, and features of the nonlocal-interactions. The predictions from the theoretical (spectral) analysis demonstrate agreement with the results from the many-body (kinetic) simulations, thus providing a powerful tool for the study of active turbulence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Nonlinear mode coupling and energetics of driven magnetized shear-flow turbulence

To comprehensively understand the saturation of two-dimensional (2D) magnetized Kelvin–Helmholtz-instability-driven turbulence, energy transfer analysis is extended from the traditional interaction between scales to include eigenmode interactions, by using the nonlinear couplings of linear eigenmodes of the ideal instability. While both kinetic and magnetic energies cascade to small scales, a significant fraction of turbulent energy deposited by unstable modes in the fluctuation spectrum is shown to be re-routed to the conjugate-stable modes at the instability scale. They remove energy from the forward cascade at its inception. The remaining cascading energy flux is shown to attenuate exponentially at a small scale, dictated by the large-scale stable modes. Guided by a widely used instability-saturation assumption, a general quasi-linear model of instability is tested by retaining all nonlinear interactions except those that couple to the large-scale stable modes. These complex interactions are analytically removed from the magnetohydrodynamic equations using a novel technique. Observations are an explosive large-scale vortex separation instead of the well-known merger of 2D, a dramatic enhancement in turbulence level and spectral energy fluxes, and a reduced small-scale dissipation length scale. These show the critical role of the stable modes in instability saturation. Possible reduced-order turbulence models are proposed for fusion and astrophysical plasmas, based on eigenmode-expanded energy transfer analyses.

Physics↗
DOE OSTI2021

Generalized Toeplitz–Hankel matrices and their application to a layered electron gas

We extend the standard result for the eigenspectrum of the Toeplitz matrix C ij = e –κ|i–j| with 0 ≤ i,j ≤ N and κ ϵ C to a combination of a Toeplitz matrix and a Hankel matrix. We apply this result to find the plasma modes of a layered assembly of a 2-dimensional electron gas. We find a sum rule relating the geometric mean of the frequencies of the plasma modes to the determinant of this Toeplitz matrix, for which an analytical expression is obtained. Here, we apply the same technique to the generalized case when the layers are not evenly spaced, where the corresponding matrix is not a Toeplitz-Hankel combination. Despite this fact, it is possible to find properties of the eigenspectrum, and the eigenmodes are localized to a few layers instead of extending across the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

High Temperature Additive Architectures for 65% Efficiency (Final Report)

GE Power (GEP) proposed a development program that targets advanced high temperature additive components that contribute towards the DOE’s goal for advanced gas turbines that are capable of 65%, or greater, efficiency in combined cycle application. GEP proposed to leverage state-of-the-art additive manufacturing to develop novel and innovative component airfoil and end wall architectures that provide cooling flow savings while maintaining the component durability expected in today’s gas turbines. The objective of this program was to develop advanced component designs and architectures enabled by additive manufacturing, and the materials systems and additive manufacturing technology required for these designs. This Phase I program leveraged existing design and analysis knowledge and techniques for additive materials and methods and utilized extensive analytical evaluations to develop and refine designs for advanced turbine hot gas path (HGP) components. The design will be the basis for development and testing in a potential Phase II program. The goal of this Phase I program was to establish a feasible conceptual design for advanced additive turbine hot section components along with a technology maturation plan involving testing to address risk areas and needed validation. It was approached through two primary elements: 1) conceptual design and analysis of wall architectures, advanced airfoil cooling concepts, and advanced system-level concepts, and 2) investigation of additive modalities and associated materials systems. The Phase I program has concluded with the down-select of a primary design concept for a potential Phase II program.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A consistent, Bayesian, approach to the cross section probability distribution in the unresolved resonance region

The cross sections of neutron-induced reactions can be divided into three energy ranges: the resolved resonance region (RRR), the unresolved resonance region (URR), and the fast region. In general, the cross sections in the URR show significant fluctuations that cannot be predicted and cannot be experimentally resolved, thus, it is commonly assumed that the cross section at a specific energy is given by a probability distribution function (PDF) over a range of values that can span several orders of magnitude. The current methodology used to describe such behavior is to construct the PDF by stochastically generating resonance ladders and numerically measuring the PDF. The resonance ladders are sampled using known resonance statistical properties and average resonance widths and spacings extrapolated from the RRR. Although this is a standard and widely used technique, it is computationally very expensive, therefore, an alternative, analytical, approach would be preferable due to the considerable speed up of the computational time in real life applications. Moreover, the current methodology does not take into account existing experimental data, such for total and capture cross sections, that are available for many nuclei. Finally, this approach was developed to be used in reactor-scale applications and it is not suited for use in single-event applications. In this work we will rethink the entire approach to the PDF construction using a Bayesian mindset. This will allow us to provide a different definition of the PDF that allows a much faster calculation of the higher-temperature PDFs and a proper combination of theoretical and experimental PDFs following the probability theory. We will also show that our definition is well suited for single-event applications and we will make an explicit connection between our method and the standard approach. We do this by showing that the central limit theorem applies and our method leads to the same PDF obtained with the standard methodology, for a large number of events per history.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Long-Length SiC/SiC Tube Irradiation Experiment at LWR Temperatures Inserted into HFIR

This report describes the pre-irradiation characterization and successful assembly of a High Flux Isotope Reactor (HFIR) irradiation experiment designed to assess radiation-induced lateral bowing of silicon carbide fiber–reinforced, silicon carbide matrix composite (SiC/SiC) components under a radial fast neutron flux gradient at representative light-water reactor (LWR) temperatures of approximately 300 °C. The over-arching goal of this work is to validate thermomechanical models of SiC/SiC composite fuel assembly distortion used to predict the extent of lateral bowing and dose at which bowing reaches a maximum value. Ultimately, these models are used to ensure that fuel assembly distortion does not block coolant channels, interfere with control rod/blade movements, and/or impact local reactivity. The experiment contains six cladding tube specimens that are approximately 558.5 mm long with representative pressurized water reactor (PWR) outer and inner diameters of 9.5 mm and 7.5 mm, respectively. The specimens were thoroughly characterized prior to irradiation using traditional dimensional inspection and surface profilometry so that these measurements can later be compared with similar measurements that will be made post-irradiation to determine radiation-induced deformations. Furthermore, fine engraving markers were inscribed along the outer surfaces of the specimen and mapped using analytic photography and a three-dimensional stage. This technique allowed for accurate measurements of the marker spacings, which can be compared with similar measurements that will be made post-irradiation to provide local radiation-induced strain mapping. A light curtain optical micrometer was also employed to measure the pre-irradiation bowing of each specimen. The experiment was successfully assembled and inserted into position VXF-19 for HFIR cycle 516, which began May 12, 2026. The experiment will be removed after cycle 519, which is currently scheduled to end in December 2026.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Monochromation of pulsed electron beams with terahertz radiation at a planar mirror

Exquisite control of electron beam energy is required for many electron spectroscopy and imaging applications. For both continuous and pulsed beams, the beam energy spread is fundamentally limited by the electron source, and is typically a sizable fraction of an electron-volt. In this paper, we present a means to reduce electron beam energy spread after emission to the level of a few 10s of meV rms using femtosecond photoemission and an interaction with laser-derived single- to few-cycle terahertz (THz) radiation. We show analytically and in particle tracking simulations that this interaction can remove energy spread stored in both the transverse and longitudinal degrees of freedom. We analytically formulate the limit of energy spread that this technique can achieve, and map the non-ideal affects arising at high frequencies. The interaction is mediated by the beam's passage through a mirror which is reflective to terahertz radiation but allows transmission of the majority of the electron beam (e.g. a wire mesh). This method then only requires beam current losses of a few tens of percent, far smaller than what is achieved in prism and slit-based electron monochromators.

Accelerator Physics (physics.acc-ph)↗
DOE OSTI2023

Local Molecular Field Theory for Coulomb Interactions in Aqueous Solutions

Coulomb interactions play a crucial role in a wide array of processes in aqueous solutions but present conceptual and computational challenges to both theory and simulations. We review recent developments in an approach addressing these challenges–local molecular field (LMF) theory. LMF theory exploits an exact and physically suggestive separation of intermolecular Coulomb interactions into strong short-range and uniformly slowly varying long-range components. This allows us to accurately determine the averaged effects of the long-range components on the short-range structure using effective single particle fields and analytical corrections, greatly reducing the need for complex lattice summation techniques used in most standard approaches. Furthermore, the simplest use of these ideas in aqueous solutions leads to the short solvent (SS) model, where both solvent–solvent and solute–solvent Coulomb interactions have only short-range components. Here we use the SS model to give a simple description of pairing of nucleobases and biologically relevant ions in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

R “SHINY” GUI DEVELOPMENT FOR URANIUM ISOTOPIC ANALYSIS WITH MATRIX-ASSISTED IONIZATION MASS SPECTROMETRY

The international nuclear safeguards community continues to seek rapid, accurate, and precise characterization capabilities for the in-field measurement of uranium isotopic compositions in nuclear facilities. Mass spectrometry (MS) is considered the “gold standard” for analysis of relatively long-lived actinides such as uranium (U) and plutonium; however, conventional MS analysis often requires time consuming sample preparation and complex analytical methodologies that are difficult to perform in-field or in-facility. Matrix assisted ionization (MAI) is a novel ambient ionization MS technique (i.e., MAI-MS) that potentially addresses these challenges due to the relative simplicity of the ionization phenomenon and ruggedness of ambient MS instrumentation. Savannah River National Laboratory (SRNL, USA) has demonstrated this technique for nanogram-level 235U/238U isotope ratio measurements within seconds, with percent-level analytical uncertainties capable of discriminating depleted, natural, and low-enriched uranium. Current experimental work on developing MAI methods for uranium isotopic analysis has been enabled by parallel development of a comprehensive MAI-MS data analysis suite at SRNL. Development of this bespoke data analysis software was necessary because commercially available ambient MS software is poorly suited for uranium isotope ratio measurement. The effort leverages the power of R, a popular open-source programming language, and Shiny, an R package providing tools for graphical user interface (GUI) and web interface coding. This software allows researchers without any programming experience to harness and utilize R’s considerable data analysis/visualization power.

LaBone, Elizabeth D.↗
DOE OSTI2024

Deconvolution of dynamic heterogeneity in protein structure

Heterogeneity is intrinsic to the dynamic process of a chemical reaction. As reactants are converted to products via intermediates, the nature and extent of heterogeneity vary temporally throughout the duration of the reaction and spatially across the molecular ensemble. The goal of many biophysical techniques, including crystallography and spectroscopy, is to establish a reaction trajectory that follows an experimentally provoked dynamic process. It is essential to properly analyze and resolve heterogeneity inevitably embedded in experimental datasets. We have developed a deconvolution technique based on singular value decomposition (SVD), which we have rigorously practiced in diverse research projects. In this review, we recapitulate the motivation and challenges in addressing the heterogeneity problem and lay out the mathematical foundation of our methodology that enables isolation of chemically sensible structural signals. We also present a few case studies to demonstrate the concept and outcome of the SVD-based deconvolution. Finally, we highlight a few recent studies with mechanistic insights made possible by heterogeneity deconvolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗