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DOE OSTI2021

Excited Rydberg states in MoSe 2 /WSe 2 heterostructures

The functional form of Coulomb interactions in the transition metal dichalcogenides (TDMs) and other van der Waals solids is critical to many of their unique properties, e.g. strongly-correlated electron states, superconductivity and emergent ferromagnetism. This paper presents measurements of key excitonic energy levels in MoSe 2 /WSe 2 heterostructures. These measurements are obtained from resonance Raman experiments on specific Raman peaks only observed at excited states of the excitons. This data is used to validate a model of the Coulomb potential in these structures which predicts the exciton energies to within ~5 meV. This model is used to determine the effect of heterostructure formation on the single-particle band gaps of the layers and will have a wide applicability in designing the next generation of more complex TDM structures.

Materials Science↗

DOE OSTI2018

Influence of magnetism and correlation on the spectral properties of doped Mott insulators

Unraveling the nature of the doping-induced transition between a Mott insulator and a weakly correlated metal is crucial to understanding novel emergent phases in strongly correlated materials. Here, for this purpose, we study the evolution of spectral properties upon doping Mott insulating states by utilizing the cluster perturbation theory on the Hubbard and t – J -like models. Specifically, a quasifree dispersion crossing the Fermi level develops with small doping, and it eventually evolves into the most dominant feature at high doping levels. Although this dispersion is related to the free-electron hopping, our study shows that this spectral feature is, in fact, influenced inherently by both electron-electron correlation and spin-exchange interaction: the correlation destroys coherence, while the coupling between spin and mobile charge restores it in the photoemission spectrum. Due to the persistent impact of correlations and spin physics, the onset of gaps or the high-energy anomaly in the spectral functions can be expected in doped Mott insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Halogen Thermochemistry Assessed with Density Functional Theory: Systematic Errors, Swift Corrections and Effects on Electrochemistry

Abstract Despite its sizable errors, density functional theory (DFT) is extensively used to evaluate thermochemical properties of gases, liquids and their interfaces with solids. As numerous halogen‐containing compounds appear as reactants, products and/or electrolytes in electrochemical reactions, and ionic effects are currently an active area of research, it is important to evaluate the accuracy of DFT for halogen thermochemistry. Herein, we assess the formation energies of interhalogens, hydrogen halides, diatomic and atomic halogens and their ions using six widespread functionals at the GGA, meta‐GGA and hybrid levels. We observe that DFT errors with respect to experiments are correlated with the electronegativity of the species and there are systematic trends across functionals, such that swift corrections were devised. Specifically, the average of the mean absolute errors for the six functionals decreased from 0.19 eV before the corrections to 0.08 eV after them. Besides, the overall maximum absolute error (MAX) decreased from 0.76 to 0.44 eV and the average of the MAXs decreased from 0.51 to 0.24 eV. Finally, we illustrate the qualitative and quantitative impact of gas‐phase errors on the predictions of surface Pourbaix diagrams.

Chemistry↗

DOE OSTI2016

Evaluating the influence of life‐history characteristics on genetic structure: a comparison of small mammals inhabiting complex agricultural landscapes

Abstract Conversion of formerly continuous native habitats into highly fragmented landscapes can lead to numerous negative demographic and genetic impacts on native taxa that ultimately reduce population viability. In response to concerns over biodiversity loss, numerous investigators have proposed that traits such as body size and ecological specialization influence the sensitivity of species to habitat fragmentation. In this study, we examined how differences in body size and ecological specialization of two rodents (eastern chipmunk; Tamias striatus and white‐footed mouse; Peromyscus leucopus ) impact their genetic connectivity within the highly fragmented landscape of the Upper Wabash River Basin ( UWB ), Indiana, and evaluated whether landscape configuration and complexity influenced patterns of genetic structure similarly between these two species. The more specialized chipmunk exhibited dramatically more genetic structure across the UWB than white‐footed mice, with genetic differentiation being correlated with geographic distance, configuration of intervening habitats, and complexity of forested habitats within sampling sites. In contrast, the generalist white‐footed mouse resembled a panmictic population across the UWB , and no landscape factors were found to influence gene flow. Despite the extensive previous work in abundance and occupancy within the UWB , no landscape factor that influenced occupancy or abundance was correlated with genetic differentiation in either species. The difference in predictors of occupancy, abundance, and gene flow suggests that species‐specific responses to fragmentation are scale dependent.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Polarized gluon pseudodistributions at short distances

We formulate the basic points of the pseudo-PDF approach to the lattice calculation of polarized gluon PDFs. We present the results of our calculations of the one-loop corrections for the bilocal G μα (z)G~ λβ (0) correlator of gluonic fields. Expressions are given for a general situation when all four indices are arbitrary, and also for specific combinations of indices corresponding to three matrix elements that contain the twist-2 invariant amplitude related to the polarized PDF. We study the evolution properties of these matrix elements, and derive matching relations between Euclidean and light-cone Ioffe-time distributions. These relations are necessary for extraction of the polarized gluon distributions from the lattice data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

The Influence of Galvanizing Parameters on the Structural Development of Zn-Al-Based Coatings

The evolution of some layers’ characteristics, deposited by galvanization, was monitored according to the technological parameters of the process. Two types of alloys from the Zn-Al and Zn-Al-Ti-B systems were used for deposition. The structure of the deposited layers was analyzed by optical and electron microscopy. The chemical composition, phases and compounds in the structures were identified. The mechanical properties of the structural constituents of the layers were determined by nanoindentation. These techniques highlighted the typical non-uniformities in terms of composition and properties in the layers, mainly due to the diffusion and distribution of iron from the steel substrate in the deposited layers. The evaluation of iron diffusion in the deposited layer was done by differential thermal analysis. The values of the critical temperatures (melting temperature, eutectic temperature and solidification temperature) were correlated with the parameters used during deposition. It was observed that the structure of the coatings is layered, with a specific order from the steel substrate to the edge. In these layers, the constituents are mixtures of soft solid solutions of Al in Zn (η and β) and hard intermetallic compounds. Moreover, increasing the immersion time in the galvanizing bath and the bath temperature leads to an increase in iron diffusion in the coating layer, which contributes to lower coating thickness, thus reducing its durability in operation.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Efficient tree decomposition of high-rank tensors [Efficient decomposition of high-rank tensors]

Tensors are a natural way to express correlations among many physical variables, but storing tensors in a computer naively requires memory which scales exponentially in the rank of the tensor. This is not optimal, as the required memory is actually set not by the rank but by the mutual information amongst the variables in question. Representations such as the tensor tree perform near-optimally when the tree decomposition is chosen to reflect the correlation structure in question, but making such a choice is non-trivial and good heuristics remain highly context-specific. In this work I present two new algorithms for choosing efficient tree decompositions, independent of the physical context of the tensor. The first is a brute-force algorithm which in most cases produces optimal decompositions but is generally impractical for high-rank tensors, as the number of possible choices grows exponentially in rank. Here, the second is a greedy algorithm, and while it is not optimal it performs extremely well in numerical experiments while having runtime which makes it practical even for tensors of very high rank.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Development and formulation of physics based metallic fuel models and comparison to integral irradiation data

Metallic fuel has an important historical significance in the development of nuclear reactors and continues to be relevant to the progression of advanced test and power reactors. A number of models, ranging from empirical to mechanistic, have been developed and implemented in various fuel performance codes to describe U-Zr and U-Pu-Zr fuel and typical fast reactor cladding materials. One challenge of using these models to simulate fuel performance is the inevitable tangling of coupled phenomena that can cloud proper implementation, calibration, and eventual utilization of new models. Here in an effort to provide a baseline capability that will facilitate the use of advanced models, new capabilities have been implemented into the fuel performance code BISON specific to metallic fuel simulations, ranging from materials properties, fission gas release and swelling calculations, coolant channel models, and cladding correlations. These models have been applied to the X441/X441A EBR-II experimental assembly data, a set of irradiated metallic UPuZr fuel rods of varying pin designs. The models implemented in BISON are able to capture the general trend of the expected response of the fuel and cladding to irradiation in EBR-II, especially when considering the spread in experimental measurements and the uncertainties inherited from the historical material models. Ultimately, the models outlined here provide the baseline capabilities on which new models can build upon in order to improve the prediction of metallic fuel performance simulations in off-normal designs or operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗

DOE OSTI2017

Structural, Chemical, and Dynamical Frustration: Origins of Superionic Conductivity in closo -Borate Solid Electrolytes

Li 2 B 12 H 12 , Na 2 B 12 H 12 , and their closo-borate relatives exhibit unusually high ionic conductivity, making them attractive as a new class of candidate electrolytes in solid-state Li- and Na-ion batteries. However, further optimization of these materials requires a deeper understanding of the fundamental mechanisms underlying ultrafast ion conduction. To this end, we use ab initio molecular dynamics simulations and density-functional calculations to explore the motivations for cation diffusion. We find that superionic behavior in Li 2 B 12 H 12 and Na 2 B 12 H 12 results from a combination of key structural, chemical, and dynamical factors that introduce intrinsic frustration and disorder. A statistical metric is used to show that the structures exhibit a high density of accessible interstitial sites and site types, which correlates with the flatness of the energy landscape and the observed cation mobility. Furthermore, cations are found to dock to specific anion sites, leading to a competition between the geometric symmetry of the anion and the symmetry of the lattice itself, which can facilitate cation hopping. Finally, facile anion reorientations and other low-frequency thermal vibrations lead to fluctuations in the local potential that enhance cation mobility by creating a local driving force for hopping. In conclusion, we discuss the relevance of each factor for developing new ionic conductivity descriptors that can be used for discovery and optimization of closo-borate solid electrolytes, as well as superionic conductors more generally.

25 ENERGY STORAGE↗

DOE OSTI2020

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data

In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. Furthermore, the new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data.

42 ENGINEERING↗

DOE OSTI2019

Tunable Porosity in Fused Filament 3D-Printed Blends of Intrinsically Porous Polymer and Thermoplastic Aliphatic Polyesters Polycaprolactone and Polylactic Acid

Future advances and usage of all-organic polymeric materials with permanent void spaces and high surface areas, in applications such as separations or as supports, depends heavily on the development of processing techniques to produce complex geometry objects. Here, the high free volume glassy microporous polymer PIM-1 was fabricated, as a major component in a polymer blend, into complex and customizable 3D objects by fused filament fabrication (FFF). PIM-1 was found to be compatible with polycaprolactone (PCL) and polylactic acid (PLA) and thus could be processed by extrusion into filaments with high loadings of PIM-1 (50% by mass). Ternary PCL/PLA/PIM-1 composite filaments provided an optimal balance of durability and melt flow characteristics for consistent FFF 3D printing of intricate structures. As printed, the micropores of PIM-1 were blocked and inaccessible to N2 during sorption experiments; however, the ternary composite structures displayed significant meso- and macroporosity and nanostructured phase separation. Postprinting immersion in 3-chloro-1-propanol was identified to selectively remove PCL within the composites, re-expose the characteristic micropores of PIM-1, and retain the macrostructure of the printed object. After postprinting treatments, specific surface areas by the Brunauer–Emmett–Teller method (as high as 460 m2 g–1) were found to directly correlate with the PCL content originally present. In conclusion, the extrusion-based processing methodology provides a new approach for production of intrinsically porous polymer objects in custom and complex shapes by reinforcement with thermoplastics (PCL and PLA).

36 MATERIALS SCIENCE↗

DOE OSTI2025

Surface Charge in Electrical Double Layer as a Kinetic Descriptor of Electrocatalytic Reactions

The successful commercialization of electrochemical energy-conversion systems hinges on a deeper understanding of electrocatalytic reaction kinetics. Despite extensive research, a key descriptor that characterizes electrolyte effects on reaction kinetics remains elusive. Here, surface charge in electrical double layers (EDLs) is introduced as a descriptor for electrolyte-dependent kinetics. The surface charge is calculated with a continuum EDL model parameterized by density-functional theory. The model is validated by reproducing the anomalously low slope of Pt(111) in Parsons-Zobel plots. Strong correlations are observed between calculated surface charge and experimental kinetic currents for hydrogen evolution, oxygen reduction, and CO 2 -reduction reactions across various pH levels and cationic species. These correlations can be either promotional or inhibitory, depending on solute-intermediate interactions. In acidic media, incorporating adsorbate charge captures specific adsorption effects in oxygen reduction reaction. In conclusion, these findings establish surface charge density as a key descriptor for electrolyte-dependent kinetics, which will guide the design of the electrode/electrolyte interface.

Adsorption↗

DOE OSTI2021

Structural descriptor for enhanced spin-splitting in 2D hybrid perovskites

Abstract Two-dimensional (2D) hybrid metal halide perovskites have emerged as outstanding optoelectronic materials and are potential hosts of Rashba/Dresselhaus spin-splitting for spin-selective transport and spin-orbitronics. However, a quantitative microscopic understanding of what controls the spin-splitting magnitude is generally lacking. Through crystallographic and first-principles studies on a broad array of chiral and achiral 2D perovskites, we demonstrate that a specific bond angle disparity connected with asymmetric tilting distortions of the metal halide octahedra breaks local inversion symmetry and strongly correlates with computed spin-splitting. This distortion metric can serve as a crystallographic descriptor for rapid discovery of potential candidate materials with strong spin-splitting. Our work establishes that, rather than the global space group, local inorganic layer distortions induced via appropriate organic cations provide a key design objective to achieve strong spin-splitting in perovskites. New chiral perovskites reported here couple a sizeable spin-splitting with chiral degrees of freedom and offer a unique paradigm of potential interest for spintronics.

42 ENGINEERING↗

DOE OSTI2018

Architecture-Guided Fluid Flow Directs Renal Biomineralization

Nephrocalcinosis often begins on a calcium phosphate deposit, at the tip of the medullo-papillary complex (MPC) known as Randall’s plaque (RP). Contextualizing proximally observed biominerals within the MPC has led us to postulate a mechanobiological switch that can trigger interstitial biomineralization at the MPC tip, remote from the intratubular biominerals. Micro X-ray computed tomography scans of human MPCs correlated with transmission and scanning electron micrographs, and X-ray energy dispersive spectrometry demonstrated novel findings about anatomically-specific biominerals. An abundance of proximal intratubular biominerals were associated with emergence of distal interstitial RP. The fundamental architecture of the MPC and mineral densities at the proximal and distal locations of the MPC differed markedly. A predominance of plate-like minerals or radially oriented plate-like crystallites within spheroidal minerals in the proximal intratubular locations, and core-shell type crystallites within spheroidal minerals in distal interstitial locations were observed. Based on the MPC anatomic location of structure-specific biominerals, a biological switch within the mineral-free zone occurring between the proximal and distal locations is postulated. The “on” and “off” switch is dependent on changes in the pressure differential resulting from changes in tubule diameters; the “Venturi effect” changes the “circumferential strain” and culminates in interstitial crystal deposits in the distal tubule wall in response to proximal tubular obstruction. These distal interstitial mineralizations can emerge into the collecting system of the kidney linking nephrocalcinosis with nephrolithiasis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Design principles from multiscale simulations to predict nanostructure in self-assembling ionic liquids

Molecular dynamics simulations (up to the nanoscale) were performed on the 3-methyl-1-pentylimidazolium ionic liquid cation paired with three anions; chloride, nitrate, and thiocyanate as aqueous mixtures, using the effective fragment potential (EFP) method, a computationally inexpensive way of modeling intermolecular interactions. The simulations provided insight (preferred geometries, radial distribution functions and theoretical proton NMR resonances) into the interactions within the ionic domain and are validated against 1 H NMR spectroscopy and small- and wide-angle X-ray scattering experiments on 1-decyl-3-methylimidazolium. Ionic liquids containing thiocyanate typically resist gelation and form poorly ordered lamellar structures upon mixing with water. Conversely, chloride, a strongly coordinating anion, normally forms strong physical gels and produces well-ordered nanostructures adopting a variety of structural motifs over a very wide range of water compositions. Nitrate is intermediate in character, whereby upon dispersal in water it displays a range of viscosities and self-assembles into nanostructures with considerable variability in the fidelity of ordering and symmetry, as a function of water content in the binary mixtures. The observed changes in the macro and nanoscale characteristics were directly correlated to ionic domain structures and intermolecular interactions as theoretically predicted by the analysis of MD trajectories and calculated RDFs. Specifically, both chloride and nitrate are positioned in the plane of the cation. Anion to cation proximity is dependent on water content. Thiocyanate is more susceptible to water insertion into the second solvent shell. Experimental 1 H NMR chemical shifts monitor the site-specific competition dependence with water content in the binary mixtures. As a result, thiocyanate preferentially sits above and below the aromatic ring plane, a state disallowing interaction with the protons on the imidazolium ring.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Magnetic properties of the quasi-one-dimensional S = 1 spin chain antiferromagnet BaNi Te 2 O 7

We report a quasi-one-dimensional S=1 spin chain compound BaNiTe 2 O 7 . This magnetic system has been investigated by magnetic susceptibility, specific heat, and neutron powder diffraction. These results indicate that BaNiTe 2 O 7 develops a short-range magnetic correlation around T ~ 22K. With further cooling, an antiferromagnetic phase transition is observed at T N ~ 5.4K. Neutron powder diffraction revealed antiferromagnetic noncollinear order with a commensurate propagation vector k = (1/2,1,0). The refined magnetic moment size of Ni 2+ at 1.5 K is 1.84 μB , and its noncollinear spin texture is confirmed by first-principles calculations. In conclusion, inelastic neutron-scattering results and density functional theory calculations confirmed the quasi-one-dimensional nature of the spin systems.

1-dimensional spin chains↗

DOE OSTI2025

Two-channel multi-impurity Kondo model: RKKY-induced criticality

We show that the Ruderman-Kittel-Kasua-Yoisida interaction between overscreened spins in two-channel Kondo impurity systems is a relevant perturbation when the number of impurities N is greater than 3 driving the system to a new quantum critical point with anomalous dimensions $\frac{1}{(𝑁+1)}$ for the spin operator and the Sommerfeld coefficient of the specific heat scales as 𝛾 ∼ 𝑇 −$\frac{3}{𝑁+1}$ . The critical point universal properties are relevant to many strong correlation problems, such as impurity placed in a Majorana metal and the multichannel Kondo lattice model of heavy fermion materials. In conclusion, we discuss relevance of our results for cluster DMFT studies of quantum criticality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗