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

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Game theoretic modeling and optimization of competition and collaboration in dual channel electronic waste supply chains

The rapid growth of electronic waste (e-waste) presents critical challenges for sustainable resource recovery and environmental protection. This study develops a dual-channel closed-loop supply chain (CLSC) model formulated as a hierarchical Stackelberg game, that integrates dynamic pricing and cost-sharing mechanisms to optimize both economic and environmental outcomes. The model explicitly captures strategic interactions between manufacturer-led and third-party recycling channels, accounting for consumer behavior, regulatory incentives, and market competition. Numerical simulations conducted (implemented over a four-iteration horizon using a commercial optimization solver) show that, relative to the baseline equilibrium, manufacturer profit increases from 11.6 thousand USD to 37.9 thousand USD (+226.8%), total recycled volume rises from 7,848 to 7,942 units (+1.2%), and collector profit nearly doubles under cost-sharing, enabling more equitable profit distribution. Furthermore, scenario-based simulations across Sub-Saharan Africa, high-income economies, and emerging Asian industrial countries reveal that infrastructure quality, policy intensity, and labor costs critically shape recycling efficiency and profit allocation. These findings demonstrate that subsidies alone are insufficient to ensure system efficiency. Instead, coordinated strategies that integrate internal incentive alignment with context-sensitive policy support are required. Overall, this study offers a robust framework for designing resilient, efficient, and regionally adaptable e-waste management systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Direct tests of cytochrome c and c 1 functions in the electron transport chain of malaria parasites

The mitochondrial electron transport chain (ETC) of Plasmodium malaria parasites is a major antimalarial drug target, but critical cytochrome (cyt) functions remain unstudied and enigmatic. Parasites express two distinct cyt c homologs (c and c-2) with unusually sparse sequence identity and uncertain fitness contributions. P. falciparum cyt c-2 is the most divergent eukaryotic cyt c homolog currently known and has sequence features predicted to be incompatible with canonical ETC function. We tagged both cyt c homologs and the related cyt c1 for inducible knockdown. Translational repression of cyt c and cyt c1 was lethal to parasites, which died from ETC dysfunction and impaired ubiquinone recycling. In contrast, cyt c-2 knockdown or knockout had little impact on blood-stage growth, indicating that parasites rely fully on the more conserved cyt c for ETC function. Biochemical and structural studies revealed that both cyt c and c-2 are hemylated by holocytochrome c synthase, but UV-vis absorbance and EPR spectra strongly suggest that cyt c-2 has an unusually open active site in which heme is stably coordinated by only a single axial amino acid ligand and can bind exogenous small molecules. These studies provide a direct dissection of cytochrome functions in the ETC of malaria parasites and identify a highly divergent Plasmodium cytochrome c with molecular adaptations that defy a conserved role in eukaryotic evolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Accelerating multilevel Markov Chain Monte Carlo using machine learning models

Here, this work presents an efficient approach for accelerating multilevel Markov Chain Monte Carlo (MCMC) sampling for large-scale problems using low-fidelity machine learning models. While conventional techniques for large-scale Bayesian inference often substitute computationally expensive high-fidelity models with machine learning models, thereby introducing approximation errors, our approach offers a computationally efficient alternative by augmenting high-fidelity models with low-fidelity ones within a hierarchical framework. The multilevel approach utilizes the low-fidelity machine learning model (MLM) for inexpensive evaluation of proposed samples thereby improving the acceptance of samples by the high-fidelity model. The hierarchy in our multilevel algorithm is derived from geometric multigrid hierarchy. We utilize an MLM to accelerate the coarse level sampling. Training machine learning model for the coarsest level significantly reduces the computational cost associated with generating training data and training the model. We present an MCMC algorithm to accelerate the coarsest level sampling using MLM and account for the approximation error introduced. We provide theoretical proofs of detailed balance and demonstrate that our multilevel approach constitutes a consistent MCMC algorithm. Additionally, we derive the expression for cost reduction due to machine learning model to facilitate cost analysis of the hierarchical sampling algorithm. Our technique is demonstrated on a standard benchmark inference problem in groundwater flow, where we estimate the probability density of a quantity of interest using a four-level MCMC algorithm. Our proposed algorithm accelerates multilevel sampling by a factor of two while achieving similar accuracy compared to sampling using the standard multilevel algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Quantum utility-scale error mitigation for quantum quench dynamics in Heisenberg spin chains

Here, we implement a quantum error mitigation method termed self-mitigation, which is comparable to zero-noise extrapolation, at large scales to achieve quantum utility on near-term, noisy quantum computers. We investigate the effectiveness of several quantum error mitigation strategies, including self-mitigation, by simulating quantum quench dynamics for Heisenberg spin chains with system sizes up to 104 qubits using IBM quantum processors. In particular, we discuss the limitations of zero-noise extrapolation and the advantages offered by self-mitigation at large scales. The self-mitigation method demonstrates stable accuracy with large systems of 104 qubits comprising more than 3,000 CNOT gates. Also, we combine the discussed quantum error mitigation methods with practical entanglement entropy measuring methods, and it shows a good agreement with the theoretical estimation. Our study illustrates the usefulness of near-term noisy quantum hardware in examining the quantum quench dynamics of many-body systems at large scales and lays the groundwork for surpassing classical simulations with quantum methods prior to the development of fault-tolerant quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Preparing exact eigenstates of the open XXZ chain on a quantum computer

The open spin-1/2 XXZ spin chain with diagonal boundary magnetic fields is the paradigmatic example of a quantum integrable model with open boundary conditions. Here, we formulate a quantum algorithm for preparing Bethe states of this model, corresponding to real solutions of the Bethe equations. The algorithm is probabilistic, with a success probability that decreases with the number of down spins. For a Bethe state of L spins with M down spins, which contains a total of $(^{L}_{M})$ $2^{M} M!$ terms, the algorithm requires L+M 2 +2M qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Floquet Engineering of Interactions and Entanglement in Periodically Driven Rydberg Chains

Neutral atom arrays driven into Rydberg states constitute a promising approach for realizing programmable quantum systems. Enabled by strong interactions associated with Rydberg blockade, they allow for simulation of complex spin models and quantum dynamics. We introduce a new Floquet engineering technique for systems in the blockade regime that provides control over novel forms of interactions and entanglement dynamics in such systems. Our approach is based on time-dependent control of Rydberg laser detuning and leverages perturbations around periodic many-body trajectories as resources for operator spreading. These time-evolved operators are utilized as a basis for engineering interactions in the effective Hamiltonian describing the stroboscopic evolution. As an example, we show how our method can be used to engineer strong spin exchange, consistent with the blockade, in a one-dimensional chain, enabling the exploration of gapless Luttinger liquid phases. In addition, we demonstrate that combining gapless excitations with Rydberg blockade can lead to dynamic generation of large-scale multipartite entanglement. Experimental feasibility and possible generalizations are discussed.

Floquet systems↗
DOE OSTI2025

Cavity-assisted magnetization switching in a quantum spin-phonon chain

Néel order switching in antiferromagnets has typically required intense optical driving, leading to substantial heating and limited efficiency. By placing antiferromagnets inside a terahertz-driven optical cavity, we propose a multi-particle mechanism for Néel order switching that benefits from reduced heating. Our analysis reveals that phonons are indispensable to this mechanism. A driven cavity mode couples to a spin-phonon chain, with all excitations dissipating energy through external baths. Mean-field analysis shows that cavity photons induce sublattice spin-density imbalance—an intrinsic symmetry-breaking effect absent without the cavity. Contrary to known (1–10 V/nm) laser fields required to switch the Néel order, our mechanism enables switching at remarkably low laser fields (1–5 V/μm), selectively targeting low-energy and perpendicular magnon modes. By virtue of the suppressed heating, the switching remains highly tunable through laser fluence, damping, and photon loss, establishing a low-dissipation route toward cavity-assisted opto-spintronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Inelastic neutron scattering study of the anisotropic S = 1 spin chain [ Ni ( HF 2 ) ( 3 – Clpyridine ) 4 ] BF 4

[Ni(HF 2 )(3–Clpyridine) 4 ]BF 4 (NBCT) is a one-dimensional, S = 1 spin chain material that shows no magnetic neutron Bragg peaks down to temperatures of 0.1 K. Previous work identified NBCT as being in the Haldane phase and near a quantum phase transition as a function of D/J to the large-D quantum paramagnet phase (QPM), where D is the axial single-ion anisotropy and J is the intrachain superexchange. Herein, inelastic neutron scattering results are presented on partially deuterated, 11B-enriched NBCT polycrystalline samples in zero magnetic field and down to temperatures of 0.3 K. Comparison to density matrix renormalization group calculations yields D/J = 1.51 and a significant rhombic single-ion anisotropy E (E/D ≈ 0.03, E/J ≈ 0.05). Here, these D, J, and E values place NBCT in the large-D QPM phase but precipitously near a quantum phase transition to a long-range ordered phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Gapless to gapless phase transitions in quantum spin chains

We investigate spin chains with bilinear-biquadratic (BLBQ) spin interactions as a function of an applied magnetic field h. At the Uimin-Lai-Sutherland (ULS) critical point we find a gapless to gapless transition revealed by the dynamical structure factor S(q,ω) as a function of h. At h=0, the envelope of the lowest-energy excitations goes soft at two points, q 1 =2π/3 and q 2 =4π/3, dubbed the phase A. With increasing field, the spectral peaks at each of the gapless points bifurcate, making in total four soft modes, and combine to form a new set of excitations that soften at a single point q=π at h c1 ≈0.94. Beyond h c1 the system enters another gapless B phase until the transition at h c2 =4 to the fully polarized phase. We compare the ULS model results with those for the Affleck-Kennedy-Lieb-Tasaki model as a representative of the gapped Haldane phase. We explain the mechanism of the gapless to gapless transition in the ULS model using its conserved charges and a spinon band picture. We also discuss the universality of central charges of the BLBQ family of models subjected to a magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

High-pressure inelastic neutron scattering study of the anisotropic S = 1 spin chain [ Ni ( HF 2 ) ( 3 - Clpyradine ) 4 ] B F 4

[Ni(HF 2 )(3-Clpyradine) 4 ]BF 4 (NBCT) is a one-dimensional, S=1 spin-chain material that shows no long-range magnetic order down to thermometer temperatures of 0.1 K. Previous ambient pressure inelastic neutron scattering experiments identified NBCT to be in the large-D quantum paramagnetic phase of the D/J phase diagram, where D is the axial single-ion anisotropy and J is the intrachain superexchange. In this work, we extend the previous experiments to a hydrostatic pressure of 0.9 GPa. By comparing to density matrix renormalization group calculations, we find D/J increases from 1.5 to 3.2 as pressure increases from 0 GPa to 0.9 GPa, which pushes the system further into the large-D phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

One-dimensional Rashba states with unconventional spin texture in Bi chains

Spin-polarized electrons confined in low-dimensional structures are of high interest for spintronics applications. Here, in this study, we investigate the electronic structure of an ordered array of Bi monomer and dimer chains on the Ag(110) surface. By means of spin-resolved photoemission spectroscopy, we find Rashba-Bychkov split bands crossing the Fermi level with one-dimensional constant energy contours. These bands are up-spin polarized for positive wave vectors and down-spin polarized for negative wave vectors, at variance with the Rashba-Bychkov model that predicts a pair of states with opposite spin in each half of the surface Brillouin zone. Density functional theory shows that spin-selective hybridization with the Ag bulk bands originates this unconventional spin texture.

1-dimensional spin chains↗
DOE OSTI2023

Open-system spin transport and operator weight dissipation in spin chains

Here, we use nonequilibrium steady states to study the effect of dissipation-assisted operator evolution (DAOE) on the scaling behavior of transport in one-dimensional spin chains. We consider three models in the XXZ family: the XXZ model with staggered anisotropy, which is chaotic; XXZ model with no external field and tunable interaction, which is Bethe-ansatz integrable and (in the zero interaction limit) free-fermion integrable; and the disordered XY model, which is free-fermion integrable and Anderson localized. We find evidence that DAOE's effect on transport is controlled by its effect on the system's conserved quantities. To the extent that DAOE preserves those symmetries, it preserves the scaling of the system's transport properties; to the extent it breaks those conserved quantities, it pushes the system towards diffusive scaling of transport.

1-dimensional spin chains↗
DOE OSTI2023

Decay rates of almost strong modes in Floquet spin chains beyond Fermi's Golden Rule

The stability and dynamics of almost strong zero and π modes in weakly nonintegrable Floquet spin chains are investigated. Such modes can also be viewed as localized Majorana modes at the edge of a topological superconductor. Perturbation theory in the strength of integrability breaking interaction J z is employed to estimate the decay rates of these modes, and compared to decay rates obtained from exact diagonalization. Here, the structure of the perturbation theory and thus the lifetime of the modes is governed by the conservation of quasienergy modulo 2π/T, where T is the period of the Floquet system. If there are 4n – 1 bulk excitations whose quasienergies add up to zero (or π/T for a π mode), one obtains a decay channel of the Majorana mode with a decay rate proportional to $J$$^{2n}_{z}$. Thus the lifetime is sensitively controlled by the width of the single-particle Floquet bands. For regimes where the decay rates are quadratic in J z , an analytic expression for the decay rate in terms of an infinite temperature autocorrelation function of the integrable model is derived, and shown to agree well with exact diagonalization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Witnessing Nonequilibrium Entanglement Dynamics in a Strongly Correlated Fermionic Chain

Many-body entanglement in condensed matter systems can be diagnosed from equilibrium response functions through the use of entanglement witnesses and operator-specific quantum bounds. Here, we investigate the applicability of this approach for detecting entangled states in quantum systems driven out of equilibrium. We use a multipartite entanglement witness, the quantum Fisher information, to study the dynamics of a paradigmatic fermion chain undergoing a time-dependent change of the Coulomb interaction. Our results show that the quantum Fisher information is able to witness distinct signatures of multipartite entanglement both near and far from equilibrium that are robust against decoherence. Here, we discuss implications of these findings for probing entanglement in light-driven quantum materials with time-resolved optical and x-ray scattering methods.

1-dimensional spin chains↗
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

Emulation of quantum correlations by classical dynamics in a spin-$\frac{1}{2}$ Heisenberg chain

We simulate the dynamical spin structure factor (DSSF) 𝒮⁡(𝑞,𝜔) of the spin-1/2 Heisenberg antiferromagnetic chain using classical simulations. By employing Landau-Lifshitz Dynamics, we emulate quantum correlations through temperature-dependent corrections, including rescaling of magnetic dipoles and renormalization of exchange interactions. Here, our results closely match Quantum Monte-Carlo calculations for 𝑘 B⁢ 𝑇/𝐽≳1, extending the applicability of classical dynamics to the challenging case of gapless excitations. At higher temperatures, our simulations comply with general predictions for uncorrelated paramagnetic fluctuations in the infinite temperature limit. Entanglement witnesses derived from the quantum-equivalent DSSF act as sensitive diagnostics for the quantum-to-classical crossover. Their reliability stems from their dependence on spectral features alone, enabling classical dynamics to emulate quantum thresholds without genuine entanglement. This framework also reproduces transverse spin correlations in finite magnetic fields, in agreement with quantum simulations. Together, our results establish quantum-corrected classical dynamics as a scalable and predictive tool for interpreting scattering experiments and exploring quantum correlations in strongly correlated spin systems.

Inelastic neutron scattering↗
DOE OSTI2022

Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo

Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis. Hamiltonian MCMC, a state-of-the-art development in the field of MCMC, has become popular in recent years. It utilizes Hamiltonian dynamics for indirect but much more efficient drawings of the model parameters. We described the principle of the Hamiltonian MCMC for inversion problems in X-ray scattering analysis by estimating high-dimensional models for several motivating scenarios in small-angle X-ray scattering, reflectivity, and X-ray fluorescence holography. Hamiltonian MCMC with appropriate preconditioning can deliver superior performance over the random-walk MCMC, and thus can be used as an efficient tool for the statistical analysis of the parameter distributions, as well as model predictions and confidence analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Obstacles to Practical Digital Supply Chain Risk Management in the Energy Sector

Cyber supply chain risk management (C-SCRM) programs must consider operations that depend on the lifecycles of digital components such as hardware, firmware, software, and services. We integrate academic literature, historical incidents, and existing standards to identify obstacles faced by C-SCRM programs.

Business Process Management & Integration↗