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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Compressed Expanded Natural Graphite (CENG) Processing for PCM Composites

The use of phase change materials (PCMs) in thermal energy storage applications has received considerable attention in recent decades. Organic PCMs are popular due to their high latent heat of fusion, noncorrosive properties, and relative stability over many charge and discharge cycles. A primary limitation of these materials is their low thermal conductivity. This has led researchers to develop various methods to increase thermal conductivity by seeding PCM with or impregnating them into more conductive materials. One method is to impregnate PCMs into compressed expanded natural graphite (CENG) matrices, which can improve thermal conductivity by a factor of 100. CENG matrices have received particular interest due to their low cost, high porosity, small (nano/micro) pore size, high pore density, high thermal conductivity, and ability to be compressed into many geometries. PCM/CENG matrix composites have been extensively studied; however, the effect that CENG processing has on PCM saturation and the overall matrix thermal conductivity has not been well investigated. This processing includes four major steps including graphite intercalation, thermal shock, compression, and PCM saturation. Intercalation involves soaking graphite flakes in sulfuric and/or nitric acid to intercalate the acids between the graphene layers. The graphite flakes are then subjected to a high-temperature thermal shock, during which the intercalated acid is gasified rapidly, pushing the graphene layers apart, resulting in accordion-shaped graphite "worms". The "worms" are then compacted to a desired bulk density and then soaked with molten PCM until fully saturated. The properties of the produced CENG matrix, and its ability to allow PCM permeation, are sensitive to the processing parameters, namely, the thermal shock temperature and exposure time, as well as the matrix apparent density or porosity. Here, we study the effect of the thermal shock conditions necessary to expand intercalated graphite flakes on PCM saturation and the expanded graphite's thermal conductivity and morphology. We found that the thermal shock temperature exhibits the greatest influence. At greater shock temperatures, SEM images showed that expanded graphite worms exhibited greater density of pores, thus increasing total surface area within the matrices. Increasing thermal shock temperature yielded greater overall PCM saturation, as well as an increased rate of saturation. Improvements in PCM saturation rate and overall saturation are obtained as the shock temperature is increased. Longer exposure to thermal shock also improves initial saturation rates and is beneficial if a shortened impregnation time is needed. Thermal shock conditions did not impact thermal conductivity; however, conductivity was largely affected by matrix porosity. A local maximum in axial thermal conductivity was observed at around 83% porosity, which is similar to that observed in previous studies.

compressed expanded natural graphite↗
DOE OSTI2026

QuadSync: Quadrifocal tensor synchronization via Tucker decomposition

In structure from motion, quadrifocal tensors capture more information than their pairwise counterparts (essential matrices), yet they have often been thought of as impractical and only of theoretical interest. In this work, we challenge such beliefs by providing a new framework to recover n cameras from the corresponding collection of quadrifocal tensors. We form the block quadrifocal tensor and show that it admits a Tucker decomposition whose factor matrices are the stacked camera matrices, and which thus has a multilinear rank of (4,4,4,4) independent of n. We develop the first synchronization algorithm for quadrifocal tensors, using Tucker decomposition, alternating direction method of multipliers, and iteratively reweighted least squares. We further establish relationships between the block quadrifocal, trifocal, and bifocal tensors, and introduce an algorithm that jointly synchronizes these three entities. Numerical experiments demonstrate the effectiveness of our methods on modern datasets, indicating the potential and importance of using higher-order information in synchronization.

Miao, Daniel [University of Minnesota]↗
DOE OSTI2026

Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth

Matrix chain multiplication -- computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$-- arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present \emph{Two-Tower Matrix Multiplication}, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.

Antonioli, Giacomo [Pisa U.] (ORCID:00090000668703↗
DOE OSTI2024

Efficient Unitary Designs from Random Sums and Permutations

A unitary k-design is an ensemble of unitaries that matches the first k moments of the Haar measure. In this work, we provide two efficient constructions of k-designs on n-qubits using new random matrix theory techniques. Our first construction is based on exponentiating sums of random i.i.d. Hermitian matrices and uses O(k2n2)-many gates. In the spirit of central limit theorems, we show that this random sum approximates the Gaussian Unitary Ensemble (GUE). We then show that the product of just two exponentiated GUE matrices is already approximately Haar random. Our second construction is based on products of exponentiated sums of random permutations and uses Õ(k poly (n)) many gates. The k dependence is optimal (up to polylogarithmic factors) and is inherited from the efficiency of existing k-wise independent permutations. Furthermore, replacing random permutations with quantum-secure pseudorandom permutations (PRPs), we also obtain a pseudorandom unitary (PRU) ensemble that is secure under nonadaptive queries. A central feature of both proofs is a new connection between the polynomial method in quantum query complexity and the large-dimension (N) expansion in random matrix theory. In particular, the first construction uses the polynomial method to control high moments of certain random matrix ensembles without requiring delicate Weingarten calculations. In doing so, we define and solve a moment problem on the unit circle, asking whether a finite number of equally weighted points can reproduce a given set of moments. In our second construction, the key step is to exhibit an orthonormal basis for irreducible representations of the partition algebra that has a low-degree large-N expansion. This allows us to show that the distinguishing probability is a low-degree rational polynomial of the dimension N.

algebra↗
DOE OSTI2021

Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in various graph, scientific computing and machine learning algorithms. In this paper, we consider SpGEMMs performed on hundreds of thousands of processors generating trillions of nonzeros in the output matrix. Distributed SpGEMM at this extreme scale faces two key challenges: (1) high communication cost and (2) inadequate memory to generate the output. Furthermore, we address these challenges with an integrated communication-avoiding and memory-constrained SpGEMM algorithm that scales to 262,144 cores (more than 1 million hardware threads) and can multiply sparse matrices of any size as long as inputs and a fraction of output fit in the aggregated memory. As we go from 16,384 cores to 262,144 cores on a Cray XC40 supercomputer, the new SpGEMM algorithm runs 10x faster when multiplying large-scale protein-similarity matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Atmospheric and Soil Parameters in Five Urban Sites in Knoxville, Tennessee. 2024

This dataset, which contains ten csv files, reports several meteorological conditions such as temperature, wind speed, solar radiation, and net radiation measured in several urban parks in Knoxville, Tennessee, USA: Cumberland Estates Park (CEP), Socially Equal Energy Efficient Development (SEEED), West View Park (WVP), Victor Ashe Park (VAP), and West Hills Park (WHP). Also, hourly average of soil parameters such soil temperature, moisture, and matric potential measured in the five sites are included in this dataset. Air temperature, wind speed and direction, and solar radiation data were obtained from a METER ATMOS 41 All-in-One Weather Station (Pullman, Washington, USA). Soil moisture and temperature parameters were measured the METER Teros 12 probes embedded to a depth of 5 cm into the soil, while soil matric potential was measured with a METER Teros 21 probe. Incident and emitted radiation (shortwave and longwave) measurements were made using an Apogee (Logan, Utah, USA) net radiometer (Model SN-500-SS). This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Polymer Zwitterions for Stabilization of CsPbBr 3 Perovskite Nanoparticles and Nanocomposite Films

Abstract Functional polymers with sulfobetaine or phosphorylcholine zwitterions as pendent groups are demonstrated as both ligands and host matrices for CsPbBr 3 perovskite nanoparticles (PNPs). These polymers produce nanocomposite films with excellent NP dispersion, optical transparency, and impressive resistance to NP degradation upon exposure to water. Multidentate interactions of the zwitterion‐containing copolymers with the PNPs induce dispersed or weakly aggregated nanocomposite morphologies, depending on the extent of zwitterionic functionality in the polymer. Incorporating additional functionality into the polymers, such as benzophenone pendent groups, yields lithographically patternable films, while time‐resolved photoluminescence measurements provide insight into the electronic impact of PNPs in zwitterionic polymer matrices.

Kim, Hyunki↗
DOE OSTI2024

Catalytically Active Site Mapping Realized through Energy Transfer Modeling

Abstract The demands of a sustainable chemical industry are a driving force for the development of heterogeneous catalytic platforms exhibiting facile catalyst recovery, recycling, and resilience to diverse reaction conditions. Homogeneous‐to‐heterogeneous catalyst transitions can be realized through the integration of efficient homogeneous catalysts within porous matrices. Herein, we offer a versatile approach to understanding how guest distribution and evolution impact the catalytic performance of heterogeneous host–guest catalytic platforms by implementing the resonance energy transfer (RET) concept using fluorescent model systems mimicking the steric constraints of targeted catalysts. Using the RET‐based methodology, we mapped condition‐dependent guest (re)distribution within a porous support on the example of modular matrices such as metal–organic frameworks (MOFs). Furthermore, we correlate RET results performed on the model systems with the catalytic performance of two MOF‐encapsulated catalysts used to promote CO 2 hydrogenation and ring‐closing metathesis. Guests are incorporated using aperture‐opening encapsulation, and catalyst redistribution is not observed under practical reaction conditions, showcasing a pathway to advance catalyst recyclability in the case of host–guest platforms. These studies represent the first generalizable approach for mapping the guest distribution in heterogeneous host–guest catalytic systems, providing a foundation for predicting and tailoring the performance of catalysts integrated into various porous supports.

Thompson, William J.↗
DOE OSTI2020

Polymer Zwitterions for Stabilization of CsPbBr 3 Perovskite Nanoparticles and Nanocomposite Films

Functional polymers with sulfobetaine or phosphorylcholine zwitterions as pendent groups are demonstrated as both ligands and host matrices for CsPbBr 3 perovskite nanoparticles (PNPs). These polymers produce nanocomposite films with excellent NP dispersion, optical transparency, and impressive resistance to NP degradation upon exposure to water. Multidentate interactions of the zwitterion-containing copolymers with the PNPs induce dispersed or weakly aggregated nanocomposite morphologies, depending on the extent of zwitterionic functionality in the polymer. Incorporating additional functionality into the polymers, such as benzophenone pendent groups, yields lithographically patternable films, while time-resolved photoluminescence measurements provide insight into the electronic impact of PNPs in zwitterionic polymer matrices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Catalytically Active Site Mapping Realized through Energy Transfer Modeling

Abstract The demands of a sustainable chemical industry are a driving force for the development of heterogeneous catalytic platforms exhibiting facile catalyst recovery, recycling, and resilience to diverse reaction conditions. Homogeneous‐to‐heterogeneous catalyst transitions can be realized through the integration of efficient homogeneous catalysts within porous matrices. Herein, we offer a versatile approach to understanding how guest distribution and evolution impact the catalytic performance of heterogeneous host–guest catalytic platforms by implementing the resonance energy transfer (RET) concept using fluorescent model systems mimicking the steric constraints of targeted catalysts. Using the RET‐based methodology, we mapped condition‐dependent guest (re)distribution within a porous support on the example of modular matrices such as metal–organic frameworks (MOFs). Furthermore, we correlate RET results performed on the model systems with the catalytic performance of two MOF‐encapsulated catalysts used to promote CO 2 hydrogenation and ring‐closing metathesis. Guests are incorporated using aperture‐opening encapsulation, and catalyst redistribution is not observed under practical reaction conditions, showcasing a pathway to advance catalyst recyclability in the case of host–guest platforms. These studies represent the first generalizable approach for mapping the guest distribution in heterogeneous host–guest catalytic systems, providing a foundation for predicting and tailoring the performance of catalysts integrated into various porous supports.

Thompson, William J.↗
DOE OSTI2020

On‐site surrogates for large‐scale calibration

Abstract Motivated by a computer model calibration problem from the oil and gas industry, involving the design of a honeycomb seal, we develop a new Bayesian methodology to cope with limitations in the canonical apparatus stemming from several factors. We propose a new strategy of on‐site design and surrogate modeling for a computer simulator acting on a high‐dimensional input space that, although relatively speedy, is prone to numerical instabilities, missing data, and nonstationary dynamics. Our aim is to strike a balance between data‐faithful modeling and computational tractability in a calibration framework—tailoring the computer model to a limited field experiment. Situating our on‐site surrogates within the canonical calibration apparatus requires updates to that framework. We describe a novel yet intuitive Bayesian setup that carefully decomposes otherwise prohibitively large matrices by exploiting the sparse blockwise structure. Empirical illustrations demonstrate that this approach performs well on toy data and our motivating honeycomb example.

Huang, Jiangeng↗
DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗
DOE OSTI2021

Green synthesis of sulfur‐doped g‐C 3 N 4 nanosheets for enhanced removal of oxytetracycline under visible‐light irradiation and reduction of its N ‐nitrosodimethylamine formation potential

Abstract BACKGROUND In this study, sulfur‐doped g‐C 3 N 4 (SCN) nanosheets were synthesized using thiourea as a precursor, and then used to catalyze the degradation of oxytetracycline (OTC) under visible‐light irradiation. OTC was chosen as target contaminant because of it being an important precursor of N ‐nitrosodimethylamine (NDMA). RESULTS The removal of OTC was influenced by its initial concentration, initial pH, SCN dosage and water matrices. OTC (≤10 mg L −1 ) was almost completely removed in 40 min under the conditions of an initial pH of 7.0 and a SCN dose of 1.0 g L −1 , and its degradation was well described by the pseudo‐first‐order kinetics model. Water matrices would also influence the degradation of OTC in the system. Electron paramagnetic resonance analysis and trapping experiments confirmed that the function of the radicals for OTC removal followed the order of • O 2 − > • OH > h + . Eight transformation products were determined during the degradation of OTC, it being removed through four pathways: methyl oxidization, demethylation, decarbonylation and secondary alcohol oxidation. SCN was stable in the system, as the removal efficiency of OTC was not significantly reduced even after three recycles. In addition, 55.5% of NDMA formation potential of OTC was reduced after SCN catalytic oxidation. CONCLUSIONS The results imply that the visible‐light‐driven SCN catalytic oxidation is an effective technology not only for the removal of OTC but also for the reduction of NDMA formation potential. © 2021 Society of Chemical Industry

Dou, Yicheng↗
DOE OSTI2020

Vacuum-Free, All-Solution, and All-Air Processed Organic Photovoltaics with over 11% Efficiency and Promoted Stability Using Layer-by-Layer Codoped Polymeric Electrodes

Nonfullerene organic photovoltaics (OPVs) have achieved a breakthrough in pushing the efficiency beyond 15%. Although this sheds light on OPV commercialization, the high cost associated with the scalable device fabrications remains a giant challenge. Herein, a vacuum-free, all-solution and all-air processed OPV is reported that yields 11.12% efficiency with a fill factor of 0.725, due to the usages of high-merit polymeric electrodes and modified active blends. The design principle toward the high-merit electrodes is to induce heavy acid doping into the matrices for a raised carrier concentration and mobility, make a large removal of insulating components in the whole matrices rather than surfaces, and restrain the formation of large-domain aggregates. A unique layer-by-layer doping is developed to enable the polymeric electrodes with record-high trade-offs between optical transmittance and electrical conductivity. Moreover, solvent vapor annealing is proposed to boost device efficiency and it has the advantages of finely adjusting the active blend morphology and raising the electron mobility. The resulting devices are highly efficient and most (≈91%) of the initial efficiency are maintained in 30 day storage. Finally, this work indicates bright future for making cost-effective all-solution processed OPVs in air.

14 SOLAR ENERGY↗
DOE OSTI2024

Evaluation of a practical approach for field scale moisture flow modeling in heterogeneous media at a semiarid site

Abstract A practical approach for modeling field‐scale moisture flow in a highly heterogeneous unsaturated medium is described in this study. The validity of this approach is demonstrated through comparison of the numerical simulations with field observations at a semiarid site located in southcentral Washington State. The methodology is based on upscaling the core scale hydraulic properties and combining power‐law and tensorial connectivity‐tortuosity (PA‐TCT) approaches to derive macroscopic anisotropy parameters for each hydrostratigraphic unit (HSU) identified in the field. Each heterogeneous HSU is approximated by an equivalent homogeneous medium (EHM) model for which PA‐TCT parameters are used in the flow simulations. The available field data on moisture content and matric potential are compared with steady‐state flow simulations based on the mean form of Richards' equation. While the homogenization or averaging of heterogeneities, embedded in the EHM modeling approximation, cannot capture all of the field‐scale variability, the simulated steady‐state moisture and matric potential profiles capture well the central tendency of the field data. This approach is deemed practical for assessing the fate and transport of contaminants in highly heterogeneous unsaturated media at the transport scale of hundreds of meters.

Khaleel, Raziuddin↗
DOE OSTI2025

Finite- and infinite-volume study of DDπ scattering

We develop a comprehensive framework for extracting the pole position and properties of the doubly-charmed tetraquark $T$$^{+}_{cc}$(3875) from lattice QCD data using the relativistic three-particle formalism. This approach incorporates the effect of the one-pion exchange diagram in DDπ and DD ∗ scattering, making it applicable at energies coinciding with the left-hand cut in the partial-wave projected DD ∗ amplitude. We present an example application of this framework to existing lattice QCD data at mπ = 280 MeV. We solve the integral equations describing the DDπ reaction, use LSZ reduction to determine the corresponding DD ∗ amplitude, and find the values of the infinite-volume two- and three-body K matrices that lead to agreement with lattice DD ∗ phase shifts within their uncertainties. Using these K matrices in the three-particle quantization condition, we describe the finite- volume DD ∗ spectrum and find good agreement with the lattice QCD energies. Our results suggest that, at this pion mass, the tetraquark appears as a pair of subthreshold complex poles whose precise location strongly depends on the value of the DDπ three-particle K matrix.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Multi-matrix correlators and localization

Abstract We study generating functions of$$ \frac{1}{4} $$ 1 4 -BPS states in$$ \mathcal{N} $$ N = 4 super Yang-Mills at finiteNby attempting to generalize the Harish-Chandra-Itzykson-Zuber integral to multiple commuting matrices. This allows us to compute the overlaps of two or more generating functions; such calculations arise in the computation of two-point correlators in the free-field limit. We discuss the four-matrix HCIZ integral in the U(2) context and lay out a prescription for finding a more general formula forN> 2. We then discuss its connections with the restricted Schur polynomial operator basis. Our results generalize readily to arbitrary numbers of matrices, opening up the opportunity to study more generic BPS operators.

Physics↗
DOE OSTI2022

Entanglement in the Quantum Hall Matrix Model

Characterizing the entanglement of matrix degrees of freedom is essential for understanding the holographic emergence of spacetime. The Quantum Hall Matrix Model is a gauged U(N) matrix quantum mechanics with two matrices whose ground state is known exactly and describes an emergent spatial disk with incompressible bulk dynamics. We define and compute an entanglement entropy in the ground state associated to a cut through the disk. There are two contributions. A collective field describing the eigenvalues of one of the matrices gives a gauge-invariant chiral boundary mode leading to an expected logarithmic entanglement entropy. Further, the cut through the bulk splits certain ‘off-diagonal’ matrix elements that must be duplicated and associated to both sides of the cut. Sewing these duplicated modes together in a gauge-invariant way leads to a bulk ‘area law’ contribution to the entanglement entropy. All of these entropies are regularized by finite N.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗