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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Efficient Simulation of Open Quantum Systems on NISQ Trapped‐Ion Hardware

Abstract Simulating open quantum systems, which interact with external environments, presents significant challenges on noisy intermediate‐scale quantum (NISQ) devices due to limited qubit resources and noise. In this study, an efficient framework is proposed for simulating open quantum systems on NISQ hardware by leveraging a time‐perturbative Kraus operator representation of the system's dynamics. This approach avoids the computationally expensive Trotterization method and exploits the Lindblad master equation to represent time evolution in a compact form, particularly for systems satisfying specific commutation relations. The efficiency of this method is demonstrated by simulating quantum channels, such as the continuous‐time Pauli channel and damped harmonic oscillators, on NISQ trapped‐ion hardware, including IonQ Harmony and Quantinuum H1‐1. Additionally, hardware‐agnostic error mitigation techniques are introduced, including Pauli channel fitting and quantum depolarizing channel inversion, to enhance the fidelity of quantum simulations. These results show strong agreement between the simulations on real quantum hardware and exact solutions, highlighting the potential of Kraus‐based methods for scalable and accurate simulation of open quantum systems on NISQ devices. This framework opens pathways for simulating more complex systems under realistic conditions in the near term.

Burdine, Colin [Department of Electrical and Compu↗
DOE OSTI2021

Wide-Gap Perovskite via Synergetic Surface Passivation and Its Application toward Efficient Stacked Tandem Photovoltaics

Superior bandgap tunability enables solution-processed halide perovskite a promising candidate for multi-junction photovoltaics (PVs). Particularly, optically coupling wide-gap perovskite by stacking with commercially available PVs such as silicon and CIGS (also known as 4-terminal tandem) simplifies the technology transfer process, and further advances the commercialization potential of perovskite technology. However, compared with matured PV materials and the phase-pure FAPbI 3 , wide-gap perovskite still suffers from huge voltage deficits. Here, the authors take advantage of the synergetic effect behind a sequential fluoride and organic ammonium salt surface passivation strategy to control non-radiative energy losses, and obtained a 17.7% efficiency in infrared-transparent wide-gap perovskite solar cells (21.1% for opaque device), and achieved efficiencies of over 25% when stacked with commercial Si and CIGS products with original PCEs of 18–20% under a 4-terminal working condition.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomic Molybdenum for Synthesis of Ammonia with 50% Faradic Efficiency

The electrochemical dinitrogen (N 2 ) reduction reaction (NRR) under ambient conditions has gained significant interest as an environmentally friendly alternative to the traditional Haber–Bosch process for the synthesis of ammonia (NH 3 ). However, up to now, most of the reported NRR electrocatalysts with satisfactory catalytic activities have been hindered by the large overpotential in N 2 activation. The preparation of highly efficient Mo-based NRR electrocatalyst in acidic electrolytes under ambient conditions is demonstrated here, consisting of stabilized single Mo atoms anchored on holey nitrogen-doped graphene synthesized through a convenient potassium-salt-assisted activation method. At -0.05 V versus a reversible hydrogen electrode (RHE), an electrode consisting of the resultant electrocatalyst immobilized on carbon fiber paper can attain an exceptional Faradaic efficiency of 50.2% and a NH3 yield rate of 3.6 µg h -1 mg cat -1 with low overpotentials. Density functional theory calculations further unveil that compared to the original graphene without holes, the edge coordinated Mo atoms and the existence of vacancies on holey graphene lower the overpotential of N 2 reduction, thereby promoting the NRR catalytic activity. Finally, this work could provide new guidelines for future designs in single-atom catalysis that would be beneficial to ambient N 2 fixation, and replacement of classical synthesis processes that are very energy-intensive.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Importance of Nonequilibrium to Equilibrium Transition Pathways for the Efficiency and Stability of Organic Solar Cells

Controlled morphology of solution-processed thin films have realized impressive achievements for non-fullerene acceptor (NFA)–based organic solar cells (OSCs). Given the large set of donor–acceptor pairs, employing various processing conditions to realize optimal morphology for high efficiency and stable OSCs is a strenuous task. Therefore, comprehensive correlations between processing conditions and morphology evolution pathways have to be developed for efficient performance and stability of devices. Within the framework of the blend system, crystallization transitions of NFA molecules are tracked utilizing the first heating scan of differential scanning calorimeter (DSC) measurement correlating with respective morphology evolution of blend films. Real-time dynamics measurements and morphology characterizations are combined to provide optimal morphology transition pathways as NFA molecules are shown to be released from the mixed phase to form balanced ordered packing with variant processing conditions. Polymer:NFA films are fabricated using blade coating incorporating solvent additive or thermal annealing as processing conditions as a correlation is formulated between performance and stability of solar cells with morphology transition pathways. In conclusion, this work demonstrates the significance of processing condition-controlled transition pathways for the realization of optimal morphology leading to superior OSC devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Efficient Perovskite Solar Cells Achieved via Rapid Photonic Annealing of all Stacking Layers: Unveiling the Crystallization Energy Window

In this study, we report high-performance perovksite solar cells (PSCs) with rapid photonic annealing (RPA) of all stacking layers, enabled by ultraviolet (UV) light-emitting diode (LED) sources, to replace lengthy and energy-intensive thermal annealing (TA). The UV-LED annealing technique allows for layer-specific annealing, where the selected light source provides a precise UV wavelength for maximizing the amount of light absorption by the target layer. The disparity in optical absorption between the target layer and the underlying films allows the stack of the underlying films to remain relatively unaffected, making this process ideal for heating sensitive substrates. Along with a systematic investigation into the layer-specific annealing mechanism of RPA, the results demonstrated that this UV-LED-based photonic annealing of all stacking layers (7 s for perovskite absorber) can produce PSCs with the power conversion efficiency (PCE) of over 23%, the highest reported among optically annealed PSCs. Moreover, the RPA device retains over 80% of the initial PCE over 1000 h under continuous 1 sun illumination at 55 °C and 30%–60% relative humidity (RH), while TA control device drops to 50% of its initial efficiency. Furthermore, these findings represent significant strides toward achieving rapid, cost-effective, and scalable manufacturing of commercial perovskite photovoltaics (PV).

14 SOLAR ENERGY↗
DOE OSTI2021

Super Flexible Transparent Conducting Oxide-Free Organic–Inorganic Hybrid Perovskite Solar Cells with 19.01% Efficiency (Active Area=1 cm 2 )

Highly efficient organic-inorganic hybrid perovskite solar cells (OIHP-SCs) are often fabricated on a transparent conducting oxide (TCO) substrate such as indium tin oxide (ITO). However, the presence of TCOs is disadvantageous to the development of flexible OIHP-SCs due to the brittle nature of ITO which is easily breakable during bending. Herein, a flexible TCO-free OIHP-SC is demonstrated by using lithium bis(trifluoromethane)sulfonimide (Li-TFSI) as a codopant for the single-layer graphene transparent conducting electrode and poly(triarylamine) hole-transporting material (HTM) on a flexible polydimethylsiloxane substrate. The optical and electrical properties of the Li-TFSI-doped graphene substrate are measured by controlling the doping amount and the best conditions for charge extraction are established at a doping concentration of 20 mm Li-TFSI, thus optimizing the device photovoltaic performance. As a result, a highest power conversion efficiency of 19.01% is demonstrated by the flexible TCO-free OIHP-SC devices with an active area of 1 cm 2 . In addition, the flexible TCO-free OIHP-SCs exhibit good bending stability after 5000 bending cycles at radii of 6, 4, and 2 mm and excellent light soaking stability under 1 Sun light intensity over 1000 h as opposed to the poor stability when using poly(3,4-ethylenedioxythiophene) polystyrene sulfonate as the HTM.

14 SOLAR ENERGY↗
DOE OSTI2022

Codesigning Alloy Compositions of CdSe y Te 1− y Absorbers and Mg x Zn 1− x O Contacts to Increase Solar Cell Efficiency

Thin‐film solar cells such as CdTe are a major commercial photovoltaic technology, with more than 25 GW installed worldwide and levelized costs of electricity competitive with fossil fuels. Further progress may result from integrating CdSe y Te 1− y absorbers with Mg x Zn 1− x O contacts, but the device efficiency is difficult to maximize due to coupled dependence on chemical composition of both alloys. Herein, a high‐throughput approach is demonstrated to codesign chemical compositions in alloyed Mg x Zn 1− x O/CdSe y Te 1− y thin‐film solar cells, using combinatorial libraries of PV devices with orthogonal composition gradients in CdSe y Te 1− y absorbers and Mg x Zn 1− x O contacts. It is found that the solar cell performance is a strong and coupled function of both elemental compositions, with efficiency up to 17.7% ( V OC = 836 mV, fill factor = 69%, J SC = 30.6 mA cm −2 ) at atomic compositions of Mg/(Mg + Zn) ≈18% and average Se/(Se + Te) ≈4%. These performance trends among >100 devices are explained by >100 ns lifetime of photoexcited charge carriers at the Mg x Zn 1− x O/CdSe y Te 1− y interface where strong Se accumulation is also observed. This study reports the optimal compositions of the commercially relevant Mg x Zn 1− x O/CdSe y Te 1− y solar cells and demonstrates a general approach to codesigning performance of alloyed thin‐film solar cells and other optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2022

Highly Efficient Layer-by-Layer Processed Quaternary Organic Solar Cells with Improved Charge Transport and Reduced Energy Loss

We report how to improve charge transport properties and reduce energy losses are the two main challenges of organic solar cells (OSCs). Herein, a new device fabrication strategy that combines the layer-by-layer (LBL) method and a quaternary active layer is demonstrated to realize highly efficient photovoltaic performance of the OSCs based on PM6:PM7/Y6:O1-2F. The introduction of the second donor, PM7,forms a cascade energy-level alignment with PM6 that facilitates effective charge transfer. The second acceptor, O1-2F, which is poorly miscible with the donors, helps to reduce the miscibility between the donors and acceptors, and thus delivers a more desirable vertical phase separation of the active layer. Furthermore, the alloy acceptor of O1-2F and Y6 can optimize the horizontal and vertical morphology of the active layer, forming an effective charge separation and continuous charge transport channel. As a result, the PM6:PM7/Y6:O1-2F system shows a distinct increase in charge mobility and a reduced nonradiative lossΔVnrof 0.231 V compared to the PM6/Y6 system, achieving a high-power conversion efficiency of18.23%. The results indicate that the quaternary LBL OSCs are promising for future large-scale and industrial manufacture of the OSCs.

14 SOLAR ENERGY↗
DOE OSTI2022

An Anthradithiophene Donor Polymer for Organic Solar Cells with a Good Balance between Efficiency and Synthetic Accessibility

Over the past few years, the organic photovoltaics technology (OPV) has reached remarkable power conversion efficiencies (PCEs), mostly thanks to the advent of nonfullerene acceptors as well as to a high level of materials engineering. Yet, the complex materials syntheses behind these results ultimately limit technological readiness. The quest for scalable organic compounds offering high PCE and reasonably low synthetic complexity is a must to close the gap between laboratory R&D and commercial products. The synthesis and full characterization of a new conjugated polymer called PATTD is reported herein, based on a novel anthradithiophene as an electron–rich building block coupled with a commercially available dithienylbenzodithiophenedione as an electron–withdrawing comonomer. Its photovoltaic properties are studied in blends with IT–4F and IDIC as acceptors. PATTD:IT–4F–based photovoltaic devices exhibit a PCE approaching 10% and over 2300 h shelf–life stability. Finally, the PATTD scalability factor (SF), together with the PATTD–based photovoltaic performances, lead to a PCE/SF value equal to 0.297, placing such devices into the innermost circle of OPV materials, achieving one of the best compromises between efficiency and synthetic complexity and at the same time offering promising industrial perspectives.

14 SOLAR ENERGY↗
DOE OSTI2023

Integrated Micro‐Scale Concentrating Photovoltaics: A Scalable Path Toward High‐Efficiency, Low‐Cost Solar Power

The global energy market is seeing increases in the electricity demand of a couple of percentage points annually. The photovoltaic (PV) industry is also growing rapidly every year. One of the PV technologies is concentrator photovoltaics (CPV). CPV uses high‐efficiency multijunction solar cells and optics to concentrate sunlight, thereby significantly reducing the amount of semiconductor material needed. Yet, due to the high upfont manufacturing cost of CPV, it currently does not offer a competitive price against silicon PV. With this a new branch is introduced to the industry, micro‐CPV, which can be broadly explained as the miniaturization of the solar cells and optical components. The motivation for micro‐CPV is lowering the cost by decreasing the material volume and enabling new system architectures and high‐throughput manufacturing methods, while still maintaining high electrical efficiencies, taking advantage of a lower thermal load, shorter optical paths, lower resistive losses, and lower material volumes. Herein, a comprehensive review of the technological advances is presented, key synergies between micro‐CPV and other industries sharing similar challenges are identified, exemplified by micro‐light emitting diodes display manufacturing. New assembly process development in these industries will facilitate commercial adoption of micro‐CPV with continued miniaturization while driving down the cost.

Jost, Norman↗
DOE OSTI2023

Efficient Metal–Halide Perovskite Photovoltaic Cells Deposited via Vapor Transport Deposition

Photovoltaic cells based on metal-halide perovskites have exceeded the performance of other thin film technologies and rival the performance of devices based on archetypical silicon. Attractively, the perovskite active layer can be processed via a variety of solution- and vapor-based methods. Herein, emphasis is on the use of vapor transport codeposition (VTD) to process efficient n–i–p photovoltaic cells based on methylammonium lead iodide (MAPbI 3 ). VTD utilizes a hot-walled reactor operated under moderate vacuum in the range of 0.5–10 Torr. The organic and metal-halide precursors are heated with the resulting vapor transported by a N 2 carrier gas to a cooled substrate where they condense and react to form a perovskite film. The efficiency of photovoltaic devices based on VTD-processed MAPbI 3 is found to be highest in films with excess lead iodide content, with champion devices realizing exceeding 12%.

14 SOLAR ENERGY↗
DOE OSTI2020

Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey

Uncertainty quantification (UQ) includes the characterization, integration, and propagation of uncertainties that result from stochastic variations and a lack of knowledge or data in the natural world. Monte Carlo (MC) method is a sampling-based approach that has widely used for quantification and propagation of uncertainties. However, the standard MC method is often time-consuming if the simulation-based model is computationally intensive. This article gives an overview of modern MC methods to address the existing challenges of the standard MC in the context of UQ. Specifically, multilevel Monte Carlo (MLMC) extending the concept of control variates achieves a significant reduction of the computational cost by performing most evaluations with low accuracy and corresponding low cost, and relatively few evaluations at high accuracy and corresponding high cost. Multifidelity Monte Carlo (MFMC) accelerates the convergence of standard Monte Carlo by generalizing the control variates with different models having varying fidelities and varying computational costs. Multimodel Monte Carlo method (MMMC), having a different setting of MLMC and MFMC, aims to address the issue of UQ and propagation when data for characterizing probability distributions are limited. Multimodel inference combined with importance sampling is proposed for quantifying and efficiently propagating the uncertainties resulting from small data sets. All of these three modern MC methods achieve a significant improvement of computational efficiency for probabilistic UQ, particularly uncertainty propagation. Finally, an algorithm summary and the corresponding code implementation are provided for each of the modern MC methods. The extension and application of these methods are discussed in detail.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.

Young, Aaron↗
DOE OSTI2020

A high efficiency photon veto for the Light Dark Matter eXperiment

Fixed-target experiments using primary electron beams can be powerful discovery tools for light dark matter in the sub-GeV mass range. The Light Dark Matter eXperiment (LDMX) is designed to measure missing momentum in high-rate electron fixed-target reactions with beam energies of 4 GeV to 16 GeV. A prerequisite for achieving several important sensitivity milestones is the capability to efficiently reject backgrounds associated with few-GeV bremsstrahlung, by twelve orders of magnitude, while maintaining high efficiency for signal. The primary challenge arises from events with photo-nuclear reactions faking the missing-momentum property of a dark matter signal. We present a methodology developed for the LDMX detector concept that is capable of the required rejection. By employing a detailed Geant4-based model of the detector response, we demonstrate that the sampling calorimetry proposed for LDMX can achieve better than 10 -13 rejection of few-GeV photons. This suggests that the luminosity-limited sensitivity of LDMX can be realized at 4 GeV and higher beam energies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Visualization and efficient generation of constrained high-dimensional theoretical parameter spaces

We describe a set of novel methods for efficiently sampling high-dimensional parameter spaces of physical theories defined at high energies, but constrained by experimental measurements made at lower energies. Often, theoretical models such as supersymmetry are defined by many parameters, $\mathcal{O}$(10 – 100), expressed at high energies, while relevant experimental constraints are often defined at much lower energies, preventing them from directly ruling out portions of the space. Instead, the low-energy constraints define a complex, potentially non-contiguous subspace of the theory parameters. Naive scanning of the theory space for points which satisfy the low-energy constraints is hopelessly inefficient due to the high dimensionality, and the inverse problem is considered intractable. As a result, many theoretical spaces remain under-explored. We introduce a class of modified generative autoencoders, which attack this problem by mapping the high-dimensional parameter space to a structured low-dimensional latent space, allowing for easy visualization and efficient generation of theory points which satisfy experimental constraints. An extension without dimensional compression, which focuses on limiting potential information loss, is also introduced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Delayed leaf greening involves a major shift in the expression of cytosolic and mitochondrial ribosomes to plastid ribosomes in the highly phosphorus-use-efficient Hakea prostrata (Proteaceae)

Abstract Background and aims Hakea prostrata (Proteaceae) is a highly phosphorus-use-efficient plant native to southwest Australia. It maintains a high photosynthetic rate at low leaf phosphorus (P) and exhibits delayed leaf greening, a convergent adaptation that increases nutrient-use efficiency. This study aimed to provide broad physiological and gene expression profiles across leaf development, uncovering pathways leading from young leaves as nutrient sinks to mature leaves as low-nutrient, energy-transducing sources. Methods To explore gene expression underlying delayed greening, we analysed a de novo transcriptome for H. prostrata across five stages of leaf development. Photosynthesis and respiration rates, and foliar pigment, P and nitrogen (N) concentrations were determined, including the division of P into five biochemical fractions. Key results Transcripts encoding functions associated with leaf structure generally decreased in abundance across leaf development, concomitant with decreases in foliar concentrations of 85% for anthocyanins, 90% for P and 70% for N. The expression of genes associated with photosynthetic function increased during or after leaf expansion, in parallel with increases in photosynthetic pigments and activity, much later in leaf development than in species that do not have delayed greening. As leaves developed, transcript abundance for cytosolic and mitochondrial ribosomal proteins generally declined, whilst transcripts for chloroplast ribosomal proteins increased. Conclusions There was a much longer temporal separation of leaf cell growth from chloroplast development in H. prostrata than is found in species that lack delayed greening. Transcriptome-guided analysis of leaf development in H. prostrata provided insight into delayed greening as a nutrient-saving strategy in severely phosphorus-impoverished landscapes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo

Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.

Karamanis, Minas↗
DOE OSTI2020

ExaHDF5: Delivering Efficient Parallel I/O on Exascale Computing Systems

Scientific applications at exascale generate and analyze massive amounts of data. A critical requirement of these applications is the capability to access and manage this data efficiently on exascale systems. As such, parallel I/O, the key technology enables moving data between compute nodes and storage, faces monumental challenges from new applications, memory, and storage architectures considered in the designs of exascale systems. As the storage hierarchy is expanding to include node-local persistent memory, burst buffers, etc., as well as disk-based storage, data movement among these layers must be efficient. Parallel I/O libraries of the future should be capable of handling file sizes of many terabytes and beyond. In this paper, we describe new capabilities we have developed in Hierarchical Data Format version 5 (HDF5), the most popular parallel I/O library for scientific applications. HDF5 is one of the most used libraries at the leadership computing facilities for performing parallel I/O on existing HPC systems. The state-of-the-art features we describe include: Virtual Object Layer (VOL), Data Elevator, asynchronous I/O, full-featured single-writer and multiple-reader (Full SWMR), and parallel querying. In this paper, we introduce these features, their implementations, and the performance and feature benefits to applications and other libraries.

97 MATHEMATICS AND COMPUTING↗