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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Efficient Quantum Gate Discovery with Optimal Control

Optimal control theory provides a framework for numerical discovery of device controls that implement quantum logic gates, but common objective functions used for optimization often assign arbitrarily high costs to otherwise useful controls. We propose a framework for designing objective functions that permit novel gate designs such as echo pulses or locally-equivalent gates. We use numerical simulations to demonstrate the efficacy of the new objective functions by designing microwave-only pulses that act as entangling gates for superconducting transmon architectures. We observe that the proposed objective functions lead to higher fidelity controls in fewer optimization iterations than obtainable by traditional objective functions.

Kairys, Paul↗
DOE OSTI2025

Skipper-CCD Quantum Efficiency Analysis

Scientific skipper-CCDs with single-electron resolution present dozens of possibilities for detecting dark matter candidates. Fermilab's Cosmic Physics Center contributes to the DarkNESS mission, which aims to place a skipper multi-chip module in a 6U CubeSat designed for low earth orbit. The DarkNESS nanosat will have the capability to search for 1-10keV band X-rays that may originate from DM decays. One of the challenges of detection in space is the large amount of cosmic radiation contributing to sensor noise. To mitigate this, an aluminum shield is proposed to be placed on the sensor. This project aims to test and characterize the energy resolution with a shield of various thicknesses (0-100nm) using a single CCD and an iron-55 x-ray source. ROOT analysis was used to parse data from several runs into sections based on shield thickness, create strategic data cuts, and characterize Fano plus signal shot noise in the sensor.

Wells, Megan E. [U. Illinois, Chicago]↗
DOE OSTI2021

Improved forward voltage and external quantum efficiency scaling in multi-active region III-nitride LEDs

Ultra-low voltage drop tunnel junctions (TJs) were utilized to enable multi-active region blue light emitting diodes (LEDs) with up to three active regions in a single device. The multi-active region blue LEDs were grown monolithically by metal-organic chemical vapor deposition (MOCVD) without growth interruption. This is the first demonstration of a MOCVD grown triple-junction LED. Optimized TJ design enabled near-ideal voltage and EQE scaling close to the number of junctions. Furthermore, this work demonstrates that with proper TJ design, improvements in wall-plug efficiency at high output power operation are possible by cascading multiple III-nitride based LEDs.

42 ENGINEERING↗
DOE OSTI2025

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient ultrafast quantum well IR photodetectors

This project, titled “Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors”, was funded by the U.S. Department of Energy to explore a new class of materials that could make future light-sensing technologies, such as infrared (IR) cameras and detectors more efficient, affordable, and widely available. The research focused on special layered materials called 2D halide perovskites, which are made up of alternating organic and inorganic layers only a few atoms thick. These materials can be tuned at the atomic level to absorb and emit light in precise ways, making them very attractive for use in optoelectronic devices. The main goal of the project was to understand how these perovskite materials absorb light and move electrical charges at very small scales. However, this is not an easy task. These materials often contain a mixture of different structures in the same film, and traditional tools like regular absorption or photoluminescence spectroscopy are not good at telling those structures apart. To solve this, the research team, led by Professor Luisa Whittaker-Brooks at the University of Utah developed a powerful method called electroabsorption spectroscopy. This technique uses electric fields to highlight the unique “fingerprints” of different excitons, which are tiny packets of energy formed when light hits the material. By using this method, the team could separate overlapping signals and learn exactly how the materials respond to light under different conditions, including changes in temperature, thickness, and chemical makeup.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Doped GaInAs/GaP Quantum Well Superlattice Solar Cells With 27.5% Efficiency

Quantum wells can extend the absorption range of a solar cell and are typically placed in the intrinsic region of the device to enable efficient carrier collection via drift. Thick intrinsic regions are needed for significant absorption in the low bandgap quantum wells, resulting in a large depletion region recombination and ultimately a solar cell with a low fill factor (FF). However, in quantum well superlattice solar cells where tunneling plays a dominant role in carrier transport, collection by carrier diffusion may be possible, relieving the requirement for quantum wells to be placed in the intrinsic region. Here, we investigate doping in stress-balanced quantum well superlattice solar cells using thin 2 nm GaP barriers. Doping reduces J02 depletion region recombination and improves the solar cell FF up to 86.7%, but very high doping eventually reduces the carrier collection, leading to a tradeoff in efficiency. Finally, we show that the barrier thickness also plays an important role in carrier collection, and we demonstrate high efficiency 27.5% single-junction devices with a doped superlattice.

13 HYDRO ENERGY↗
DOE OSTI2022

Neural network accelerator for quantum control

Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely excluding them from use outside of the simulation. Existing hardware solutions structured as lookup tables are imprecise and costly. By designing a machine learning model to approximate the results of traditional tools, a more efficient method can be produced. Such a model can then be synthesized into a hardware accelerator for use in quantum systems. In this study, we demonstrate a machine learning algorithm for predicting optimal pulse parameters. This algorithm is lightweight enough to fit on a low-resource FPGA and perform inference with a latency of 175 ns and pipeline interval of 5 ns with > 0.99 gate fidelity. In the long term, such an accelerator could be used near quantum computing hardware where traditional computers cannot operate, enabling quantum control at a reasonable cost at low latencies without incurring large data bandwidths outside of the cryogenic environment.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Field Programmable Gate Arrays for Enhancing the Speed and Energy Efficiency of Quantum Dynamics Simulations

We present the first application of field programmable gate arrays (FPGAs) as new, customizable hardware architectures for carrying out fast and energy-efficient quantum dynamics simulations of large chemical/material systems. Instead of tailoring the software to fixed hardware, which is the typical case for writing quantum chemistry code for central processing units (CPUs) and graphics processing units (GPUs), FPGAs allow us to directly customize the underlying hardware (even at the level of specific electrical signals in the circuit) to give a truly optimized computational performance for quantum dynamics calculations. By offloading the most intensive and repetitive calculations onto an FPGA, we show that the computational performance of our real-time electron dynamics calculations can even exceed that of optimized commercial mathematical libraries running on high-performance GPUs. In addition to this impressive computational speedup, we show that FPGAs are immensely energy-efficient and consume 4 times less energy than modern GPU or CPU architectures. These energy savings are a practical and important metric for supercomputing centers (many of which exceed over $1 million in power costs alone), as exascale computing capabilities become more widespread and commonplace. Taken together, the implementation techniques and performance metrics of our study demonstrate that FPGAs could play a promising role in upcoming quantum chemistry and materials science applications, particularly for the acceleration and energy-efficient execution of quantum dynamics calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pt Particle Size Affects Both the Charge Separation and Water Reduction Efficiencies of CdS–Pt Nanorod Photocatalysts for Light Driven H 2 Generation

Decreasing the metal catalyst size into nanoclusters or even single atom is an emerging direction of developing more efficient and cost-effective photocatalytic systems. Because the catalyst particle size affects both the catalyst activity and light driven charge separation efficiency, their effects on the overall photocatalytic efficiency are still poorly understood. Herein, using a well-defined semiconductor–metal heterostructure with Pt nanoparticle catalysts selectively grown on the apexes of CdS nanorods (NRs), we study the effect of the Pt catalyst size on light driven H 2 generation quantum efficiency (QE H 2 ). With the increase of the Pt catalyst size from 0.7 ± 0.3 to 3.0 ± 0.8 nm, the QEH 2 of CdS–Pt increases from 0.5 ± 0.2% to 38.3 ± 5.1%, by nearly 2 orders of magnitude. Transient absorption spectroscopy measurement reveals that the electron transfer rate from the CdS NR to the Pt tip increases with the Pt diameter following a scaling law of d 5.6 , giving rise to the increase of electron transfer efficiency at larger Pt sizes. Additionally, the observed trend can be understood by a simplified kinetic model that assumes the overall efficiency is the product of the quantum efficiencies of charge separation (including hole transfer, electron transfer, and hole scavenging) and water reduction steps, and for CdS–Pt NRs, the quantum efficiencies of electron transfer and water reduction steps increase with the Pt sizes. Our findings suggest the importance of improving the quantum efficiencies of both charge separation and catalysis in designing efficient semiconductor–metal hybrid photocatalysts, especially in the regime of small metal particle sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗