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At least 721 records · Page 40

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DOE OSTI2025

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗

DOE OSTI2024

Composite Qdrift-product formulas for quantum and classical simulations in real and imaginary time

Recent study has shown that it can be advantageous to implement a composite channel that partitions the Hamiltonian H for a given simulation problem into subsets A and B such that H = A + B , where the terms in A are simulated with a Trotter-Suzuki channel and the B terms are randomly sampled via the Qdrift algorithm. Here we extend Qdrift and composite product formulas to imaginary time, formulating candidate classical algorithms for quantum Monte Carlo calculations. We upper bound the induced Schatten- 1 → 1 norm on both imaginary-time Qdrift and composite channels. Another recent result demonstrated that simulations of lattice Hamiltonians containing geometrically local interactions can be improved using a Lieb-Robinson argument to decompose H into subsets that contain only terms supported on that subset of the lattice. Here, we provide a quantum algorithm by unifying this result with the composite approach into “local composite channels” and we upper bound the diamond distance. We provide exact numerical simulations of algorithmic cost by counting the number of gates of the form e − i H j t and e − H j β to meet a certain error tolerance ε . In doing so, we optimize the partitioning into sets A and B using gradient boosted tree models from machine learning. These numerical studies are important given that product formulas have been historically known to outperform analytic upper bounds. We show constant factor advantages for a variety of interesting Hamiltonians, the maximum of which is a ≈ 20 -fold speedup that occurs in the simulation of Jellium. Published by the American Physical Society 2024

Pocrnic, Matthew (ORCID:0000000203089376)↗

NASA NTRS2005

Influence of Growth Parameters and Annealing on Properties of MBE Grown GaAsSbN SQWs

In this paper we report the growth of GaAsSbN/GaAs single quantum well (SQW) heterostructures by molecular beam epitaxy (MBE) and their properties. A systematic study has been carried out to determine the effect of growth conditions, such as the source shutter opening sequence and substrate temperature, on the structural and optical properties of the layers. The substrate temperatures in the range of 450-470 C were found to be optimal. Simultaneous opening of the source shutters (SS) resulted in N incorporation almost independent of substrate temperature and Sb incorporation higher at lower substrate temperatures. The effects of ex-situ annealing in nitrogen ambient and in-situ annealing under As ovepressure on the optical properties of the layers have also been investigated. A significant increase in photoluminescence (PL) intensity with reduced full width at half maxima (FWHM) in conjunction with a blue shift in the emission energy was observed on 10 annealing the samples. In in-situ annealed samples, the PL line shapes were more symmetric and the temperature dependence of the PL peak energy indicated significant decrease in the exciton localization energy as exhibited by a less pronounced S-shaped curve. The inverted S-shaped curve observed in the temperature dependence of PL FWHM is also discussed. 1.61 micrometer emission with FWHM of 25 meV at 20K has been obtained in in-situ annealed GaAsSbN/GaAs SQW grown at 470 C by SS.

Wu, Liangjin↗

DOE OSTI2024

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Charge carrier extraction and recombination effects in GaInAs/GaAsP multi-quantum well solar cells

The carrier extraction and transport mechanisms as well as the relative contributions of radiative and non-radiative recombination processes are investigated in high-quality strain-balanced GaInAs/GaAsP multi-quantum well solar cells recently implemented in record efficiency multijunction solar cells. A comprehensive suite of complementary characterization techniques including temperature- and suns-dependent photoluminescence and photovoltaic measurements are employed to analyze thermal escape and tunneling rates, which demonstrate the need to move beyond simple drift-diffusion models of p–n junctions. This study examines the processes that best characterize the operation of these devices across varying temperatures using a simple two-diode model, incorporating multiple transport protocols, and provides insights into the performance-limiting processes and pathways for their optimization.

14 SOLAR ENERGY↗

NASA NTRS2014

Advanced Inductively Coupled Plasma Etching Processes for Fabrication of Resonator-Quantum Well Infrared Photodetector

Resonator-quantum well infrared photodetectors (R-QWIPs) are the next generation of QWIP detectors that use resonances to increase the quantum efficiency (QE). To achieve the expected performance, the detector geometry must be produced in precise specification. In particular, the height of the diffractive elements (DE) and the thickness of the active resonator must be uniformly and accurately realized to within 0.05 lm accuracy and the substrates of the detectors have to be removed totally. To achieve these specifications, two optimized inductively coupled plasma (ICP) etching processes are developed. Using these etching techniques, we have fabricated a number of R-QWIP test detectors and FPAs with the required dimensions and completely removed the substrates of the test detectors and FPAs. Their QE spectra were tested to be in close agreement with the theoretical predictions. The operability and spectral non-uniformity of the FPA is about 99.57% and 3% respectively.

plasma etching process↗

DOE OSTI2026

Carrier Dynamics of Strongly Confined CsPbI 3 Nanowires

Here, we investigate the carrier dynamics of strongly confined cesium lead iodide (CsPbI 3 ) nanowires and compare them with weakly confined quantum dots (QDs) to understand how dimensionality affects recombination processes. Using time-resolved photoluminescence and ultrafast transient absorption spectroscopy, we find that nanowires exhibit a 5× faster recombination rate and more rapid carrier cooling than QDs. These differences are attributed to enhanced carrier interactions with trap states. Although nanowires exhibit slightly enhanced radiative rates as a result of confinement, their photoluminescence quantum yield remains relatively low, 23 ± 8%, due to competition from nonradiative recombination processes that occur at a faster rate. These findings highlight a dimensionality-dependent trade-off between radiative efficiency and nonradiative losses, providing insight into the limitations and opportunities for low-dimensional perovskite nanostructures. Our results establish design principles for tailoring CsPbI 3 nanocrystal dimensionality to optimize optical performance in optoelectronic applications such as LEDs and solar cells.

Oddo, Alexander M. [University of California, Berk↗

DOE OSTI2025

SYCL for Performance Portability: Application Experience with Coupled Cluster Formalism in Quantum Chemistry on Exascale Systems

The exascale computing has brought unprecedented heterogeneity in node architectures, with systems such as Frontier and Aurora featuring diverse GPU accelerators, network connectivity among others. Ensuring performance portability across these platforms is a key challenge. To address this, we employ the SYCL programming model to develop portable, high-performance quantum chemistry workloads. As a representative application, we focus on the non-iterative Triples component of the coupled-cluster CCSD(T) method, a key driver in quantum chemistry. In this work, we report on our experience deploying SYCL-based implementations using both DPC++ and AdaptiveCPP across two flagship exascale platforms: OLCF Frontier with AMD MI250X GPUs and ALCF Aurora with Intel GPUs. Our results demonstrate that SYCL enables efficient, single-source implementations that scale to thousands of nodes, delivering performance on par with vendor-optimized HIP solutions. We highlight key insights into runtime behavior, kernel portability, and scaling characteristics, showing that SYCL offers a viable path for performance-portable computing.

Bagusetty, Abhishek [Argonne National Laboratory (↗

DOE OSTI2025

Bi-chromatic intensity squeezing using four-wave mixing in 85 Rb vapor

We experimentally investigate four-wave mixing (FWM) in a diamond interaction scheme using 85 Rb vapor, and identify the optimal conditions for joint amplification and relative intensity squeezing of two optical fields: one near the 85 Rb D1 optical transition (λ = 794.6 nm) and the other in the telecom O-band (λ = 1324 nm). We achieved a reduction of relative intensity noise by up to 2.6 ± 0.4 dB compared with the shot noise level, signifying the non-classical quantum correlations. The observed level of intensity squeezing is primarily limited by the available pump laser power, which constrains the achievable FWM gain. Numerical simulations show good agreement with the experimental results.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

Low-dimensional carbon materials decorated FAPbI 3 for carbon-based perovskite solar cells

Carbon nanomaterials are at the forefront of research in perovskite solar cells (PSCs) due to their exceptional electrical, optical, and stability properties. Their diverse applications include serving as interfacial layers, additives, hole and electron transport materials, and back electrodes. While the influence of various low-dimensional carbon nanomaterial structures on crystallinity, optical and electrical performance, and overall device efficiency has been a topic of interest, it has not been thoroughly explored until now. In this study, we effectively integrated carbon quantum dots (CQDs), multi-walled carbon nanotubes (MWCNTs), and graphene into the FAPbI 3 photoactive layer using a two-step sequential deposition method. Our experiments revealed marked improvements in the photovoltaic performance of PSCs that incorporated all three types of carbon nanomaterials. In particular, the data shows significant enhancements in power conversion efficiency, demonstrating the effectiveness of these materials in optimizing device functionality. Notably, MWCNTs distinguished themselves by exhibiting a remarkable potential for enhancing long-term stability. This finding underscores the importance of selecting the right carbon nanomaterials for future PSC developments, paving the way for more reliable and efficient solar energy solutions. As a result, our research highlights the critical role of carbon nanomaterials in advancing perovskite solar technology.

14 SOLAR ENERGY↗

DOE OSTI2025

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗

DOE OSTI2026

Electrochemical Characterization of Photo-Driven Hole-Scavenging by Cadmium Sulfide Quantum Dot-Nitrogenase Biohybrid Complexes

Light-driven biohybrid systems that couple semiconductor nanocrystals with enzymes offer a promising strategy for solar-to-chemical energy-conserving reduction reactions, yet are often limited by inefficient hole scavenging. Hole scavenging is critical for maintaining charge separation in the light-absorbing electron donor molecule and, thus, for sustaining catalytic turnover, making quantification essential to improving system efficiency. Here, we introduce a photoelectrochemical approach for real-time monitoring of hole scavenging in cadmium sulfide (CdS) quantum dot (QD)-nitrogenase MoFe protein biohybrids that catalyze the reduction of H+ and N2. Using hydroquinone (HQ) as the sacrificial electron donor (SED), oxidation of HQ to benzoquinone (BQ) by photogenerated valence-band holes is coupled to the electrochemical reduction of BQ at an electrode, enabling quantification of the hole-scavenging reaction via chronoamperometry. This approach provides a continuous, real-time readout of charge-transfer dynamics under illumination. Systematic variation of light intensity and donor concentration reveals that hole scavenging scales with photon flux and exhibits a non-linear dependence on SED concentration, with an optimum at intermediate HQ concentrations. These results establish chronoamperometry as a powerful tool for probing photoinduced charge transfer, advancing the quantitative understanding of hole-scavenging in biohybrid systems, and offering a generalizable framework for optimizing solar-driven biocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Exploring the Structural Origins of Optically Efficient One-Dimensional Lead Halide Perovskite Nanostructures

Metal halide perovskites have excellent optoelectronic properties. This study aims to determine how the optoelectronic properties of a model perovskite, cesium lead bromide (CsPbBr3), change with length and thickness in one dimension (1D). By examining the photophysics of CsPbBr3 quantum dots (QDs), nanowires (NWs), and nanorods (NRs), we observe the influence of confinement, exciton diffusion, and trapping on their optical properties. Our findings reveal that exciton diffusion to trap states limits the photoluminescence quantum yield (PLQY) of 1D CsPbBr3 in the weakly confined regime (8-14 nm) and explains their long-lived exciton dynamics, while enhanced radiative rates contribute to achieving near-unity PLQY in the strongly confined regime (<7 nm). Consequently, blue-emitting, 2.4 nm-thick CsPbBr3 NRs were 3.6X more emissive than the conventional CsPbBr3 QDs. This study underscores how structural optimization can improve the optoelectronic performance of CsPbBr3 and provides insight into the complex interplay of radiative and nonradiative processes in 1D ionic semiconductors.

Oddo, Alexander M↗

DOE OSTI2025

Maximizing Free Energy Gain

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy—and by extension, the maximum extractable work—that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

Physics↗

DOE OSTI2025

Study of the Scintillating Properties of Materials Based on Self- Assembling Quantum Dots Embedded into a Semiconductor Bulk

The goal of the project is to investigate scintillating properties of materials based on self-assembled InAs QDs embedded into GaAs bulk. According to theoretical predictions, such materials can have scintillating properties and low self-absorption. Compared to scintillators based on inorganic scintillating crystals, QD-based scintillators could have significantly higher light yield and shorter emission times. We intend to check the theoretical predictions experimentally, measure scintillation parameters and their dependence on the QD-based materials and learn how the properties could be optimized for practical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗

DOE OSTI2024

Optimizing spectral phase transfer in four-wave mixing with gas-filled capillaries

Four-wave mixing (FWM) in gas-filled hollow-core capillaries, a nonlinear optical process that mixes signal and pump photon frequencies to generate idler frequency photons, offers a method for precise spectral phase transfer from signal to idler at ultrashort timescales and extreme powers. However, this regime is challenged by competing linear and nonlinear dynamics, leading to significant trade-offs between spectral phase transfer and conversion efficiency. Our computational investigation focuses on the upconversion of femtosecond pulses from the infrared (IR) to the ultraviolet (UV), a range notoriously difficult to manipulate. We explore an intermediate energy regime that strikes an optimal balance between FWM-mediated phase-transfer fidelity and nonlinear conversion efficiency. By adjusting the energy ratios and spectral phase profiles of the input signal, we achieve conversion efficiencies of approximately 5-15% while maintaining an effective quasi-linear spectral phase transfer. These findings will contribute to establishing first-principles and scaling laws essential for applications such as high-precision imaging, spectroscopy, quantum transduction, and distributed entangled interconnects, facilitating advanced control of ultrafast photonic and electronic wavepackets in quantum materials with unprecedented spatial and temporal precision.

Zhang, Hao↗

NASA NTRS1992

A Gaussian measure of quantum phase noise

We study the width of the semiclassical phase distribution of a quantum state in its dependence on the average number of photons (m) in this state. As a measure of phase noise, we choose the width, delta phi, of the best Gaussian approximation to the dominant peak of this probability curve. For a coherent state, this width decreases with the square root of (m), whereas for a truncated phase state it decreases linearly with increasing (m). For an optimal phase state, delta phi decreases exponentially but so does the area caught underneath the peak: all the probability is stored in the broad wings of the distribution.

Schleich, Wolfgang P.↗