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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

As we know, power transformers are the most critical asset of the transmission network. Although highly reliable, they still can fail prematurely or ultimately retire at the end of their service life. In today’s design practices, transformers are tailored to their specific application and therefore cannot replace each other unless identical. Additionally, they provide minimal support to the grid operation and therefore limit the grid flexibility and resiliency when facing severe conditions. In this presentation, we will introduce the concept of flexible power transformer and demonstrate how one single unit can serve as a spare to multiple units in a given fleet, allow to control the power flow between transformers or lines operating in parallel and ultimately be used to limit subsequent faults in transmission lines. We will also introduce the world’s first prototype in operation, a 60MVA, 165kV flexible autotransformer.

flexible power transformer, autotransformer, varia↗
DOE OSTI2020

Realization of an Asymmetric Non‐Aqueous Redox Flow Battery through Molecular Design to Minimize Active Species Crossover and Decomposition

Abstract This communication presents a mechanism‐based approach to identify organic electrolytes for non‐aqueous redox flow batteries (RFBs). Symmetrical flow cell cycling of a pyridinium anolyte and a cyclopropenium catholyte resulted in extensive capacity fade due to competing decomposition of the pyridinium species. Characterization of this decomposition pathway enabled the rational design of next‐generation anolyte/catholyte pairs with dramatically enhanced cycling performance. Three factors were identified as critical for slowing capacity fade: (1) separating the anolyte–catholyte in an asymmetric flow cell using an anion exchange membrane (AEM); (2) moving from monomeric to oligomeric electrolytes to limit crossover through the AEM; and (3) removing the basic carbonyl moiety from the anolyte to slow the protonation‐induced decomposition pathway. Ultimately, these modifications led to a novel anolyte–catholyte pair that can be cycled in an AEM‐separated asymmetric RFB for 96 h with >95 % capacity retention at an open circuit voltage of 1.57 V.

Shrestha, Anuska↗
DOE OSTI2025

Prediction of Specificity of α-Conotoxins to Subtypes of Human Nicotinic Acetylcholine Receptors with Semi-supervised Machine Learning

Conotoxins are a family of highly toxic neurotoxins composed of cysteine-rich peptides produced by marine cone snails. The most lethal cone snail species to humans is Conus geographus, with fatality rates of up to ∼65% from a single sting, which is caused mostly by the activity of α-conotoxins against human nicotinic acetylcholine receptors (nAChRs). While sequence-based machine learning (ML) classifiers have been trained to identify targets of conotoxins binding voltage-gated ion channels, no ML model has been built to predict the subtype-specific nAChR targets of α-conotoxins. Here, we trained an ML model in a semi-supervised manner to predict the specificity of α-conotoxin binding toward different human nAChR subtypes to overcome the challenge of limited data in subtype-specific nAChR targets of α-conotoxins and the issue that one α-conotoxin can bind multiple nAChR subtypes with high selectivity. We considered additional features of sequences of α-conotoxins in training our ML model, including the secondary structure propensities and electrostatic properties, which resulted in better prediction capability for the ML model. Notably, we identify that most α-conotoxins bind to α3β2, α1γδ, and α7 subtypes of human nAChRs. Our findings from this study provide a framework for predicting targets of various kinds of toxins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Physics-Based Model to Represent Membrane-Electrode Assemblies of Solid-Oxide Fuel Cells Based on Gadolinium-Doped Ceria

This paper reports a physics-based model that predicts membrane-electrode assembly (MEA) performance of solid-oxide fuel cells (SOFCs) with Ce 0.9 Gd 0.1 O 2− δ (GDC10) electrolyte membranes. The paper derives self-consistent thermodynamic and transport properties for GDC1o mobile charged defects (oxide vacancies and reduced-ceria small polarons) by fitting published measurements of oxygen non-stoichiometry and conductivity over ranges of temperature and O 2 partial pressures. The button-cell model is applied to evaluate how mixed ionic-electronic conductivity influences the performance of an SOFC MEA with a GDC10 electrolyte sandwiched between a porous, composite Ni-GDC10 anode and a porous, composite cathode of Sm 0.5 Sr 0.5 CoO 3− δ (i.e., SSC) and GDC10. SSC properties are also derived by fitting published conductivity and oxygen non-stoichiometry measurements. Mixed conductivity of GDC10 and competing charge transfer reactions at both electrodes reduce open circuit voltages due to leakage current and buildup of defect concentrations at electrode-electrolyte interfaces. To fit polarization data, the button-cell model includes heterogeneous reaction rates for defect incorporation on the GDC10 surface along with Butler–Volmer expressions derived for competing charge transfer reaction rates from rigorous analyses assuming rate-limiting, elementary charge transfer reactions for each electrode. The calibrated MEA model can support rigorous SOFC modeling with GDC10 electrolytes over the range of conditions within a fully operating cell.

Electrochemistry↗
DOE OSTI2022

Metallo-graphene nanocomposites and methods for using metallo-graphene nanocomposites for electromagnetic energy conversion

Nanocomposites in accordance with many embodiments of the invention can be capable of converting electromagnetic radiation to an electric signal, such as signals in the form of current or voltage. In some embodiments, metallic nanostructures are integrated with graphene material to form a metallo-graphene nanocomposite. Graphene is a material that has been explored for broadband and ultrafast photodetection applications because of its distinct optical and electronic characteristics. However, the low optical absorption and the short carrier lifetime of graphene can limit its use in many applications. Nanocomposites in accordance with various embodiments of the invention integrates metallic nanostructures, such as (but not limited to) plasmonic nanoantennas and metallic nanoparticles, with a graphene-based material to form metallo-graphene nanostructures that can offer high responsivity, ultrafast temporal responses, and broadband operation in a variety of optoelectronic applications.

Jarrahi, Mona↗
DOE OSTI2023

Data-Driven Affinely Adjustable Robust Volt/VAr Control

Recent years have seen the increasing proliferation of distributed energy resources with intermittent power outputs, posing new challenges to the voltage management in distribution networks. To this end, this paper proposes a data-driven affinely adjustable robust Volt/VAr control (AARVVC) scheme, which modulates the smart inverter’s reactive power in an affine function of its active power, based on the voltage sensitivities with respect to real/reactive power injections. To achieve a fast and accurate estimation of voltage sensitivities, we propose a data-driven method based on deep neural network (DNN), together with a rule-based bus-selection process using the bidirectional search method. Our method only uses the operating statuses of selected buses as inputs to DNN, thus significantly improving the training efficiency and reducing information redundancy. Finally, a distributed consensus-based solution, based on the alternating direction method of multipliers (ADMM), for the AARVVC is applied to decide the inverter’s reactive power adjustment rule with respect to its active power. Only limited information exchange is required between each local agent and the central agent to obtain the slope of the reactive power adjustment rule, and there is no need for the central agent to solve any (sub)optimization problems. Finally, numerical results on the modified IEEE-123 bus system validate the effectiveness and superiority of the proposed data-driven AARVVC method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

PowerNet: Multi-agent Deep Reinforcement Learning for Scalable Powergrid Control

This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-based secondary voltage control problem in distributed generators (DGs), which is first formulated as a cooperative multi-agent reinforcement learning (MARL) problem. We then propose a novel on-policy MARL algorithm, PowerNet, in which each agent (DG) learns a control policy based on (sub-)global reward but local states and encoded communication messages from its neighbors. Motivated by the fact that a local control from one agent has limited impact on agents distant from it, we exploit a novel spatial discount factor to reduce the effect from remote agents, to expedite the training process and improve scalability. Furthermore, a differentiable, learning-based communication protocol is employed to foster the collaborations among neighboring agents. In addition, to mitigate the effects of system uncertainty and random noise introduced during on-policy learning, we utilize an action smoothing factor to stabilize the policy execution. To facilitate training and evaluation, we develop PGSim, an efficient, high-fidelity powergrid simulation platform. Here, experimental results in two microgrid setups show that the developed PowerNet outperforms the conventional model-based control method, as well as several state-of-the-art MARL algorithms. The decentralized learning scheme and high sample efficiency also make it viable to large-scale power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Enhancing Acidic Oxygen Evolution Activity by Supporting Iridium Electrocatalysts on Tantalum Carbide

For a high-performance proton exchange membrane water electrolyzer (PEMWE), acidic oxygen evolution reaction (OER) electrocatalysts require highly dispersed iridium oxide (IrO x ) nanoparticles. Although carbon-based materials have been explored as promising supports for IrO x nanoparticles, their limited stability under harsh oxidative and acidic PEMWE conditions remains a significant challenge. Here, in this study, we report the synthesis and in situ characterization of active and durable IrOx electrocatalysts supported on electrochemically stable and electrically conducting tantalum carbide (TaC). When applied in a PEMWE, the IrO x /TaC electrocatalyst achieves a cell voltage of 1.71 V at 1.0 A cm –2 , outperforming the commercial IrO 2 catalyst (1.82 V at 1.0 A cm –2 ). Furthermore, the IrO x /TaC catalyst maintains a stable operation for 200 h at 0.5 A cm –2 with a low degradation rate of 36 μV h –1 . Density functional theory calculations further confirm that Ir–O–Ta bond formation at the IrO x /TaC interface reduces the overpotential of the OER compared to IrO 2 . This study underscores the pivotal role of supporting IrO x over stable and conducting metal carbides, providing guidance for the design of advanced acidic OER catalysts.

58 GEOSCIENCES↗
DOE OSTI2023

Hierarchical Control and Stability Analysis for a Nonisolated Grid-Tied DC Energy Router Integrating Energy Storage and Partial Distributed Generation

This article proposes a nonisolated dc converter-based energy router (dc-ER) and its operating strategy. Here, the intent is to integrate energy storage (ES), distributed generation (DG), local load, and dc power grid in an autonomous and more efficient way. The ES/DG power ports are coupled with each other in partial-type connections, which obtains higher voltage supply gain and direct input–output power transmission. High-voltage supply gain allows a wide solar power tracking range and the possibility of optimal battery charging/discharging. Direct input–output power transmission improves the energy conversion efficiency. In this article, the operating modes of dc-ER are first analyzed, followed by the optimal hardware design counting the DG current ripple minimization and the limitation caused by the power flow direction. Second, the mathematical model of dc-ER is deduced. The hierarchical control is then proposed to manage port energy in a flexible manner. The stability is analyzed by using impedance modeling. Finally, experimental and simulation results verify the superiorities of the proposed topology in terms of flexible operating mode transition and high-power conversion efficiency.

25 ENERGY STORAGE↗
DOE OSTI2023

Learning Distribution Grid Topologies: A Tutorial

Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes, contrasts, and establishes useful links between recent works on topology identification and detection schemes that have been proposed for power distribution grids. The primary focus is to highlight methods that overcome the limited availability of measurement devices in distribution grids, while enhancing topology estimates using conservation laws of power-flow physics and structural properties of feeders. Grid data from phasor measurement units or smart meters can be collected either passively in the traditional way, or actively, upon actuating grid resources and measuring the feeder's voltage response. Analytical claims on feeder identifiability and detectability are reviewed under disparate meter placement scenarios. Such topology learning claims can be attained exactly or approximately so via algorithmic solutions with various levels of computational complexity, ranging from least-squares fits to convex optimization problems, and from polynomial-time searches over graphs to mixed-integer programs. Although the emphasis is on radial single-phase feeders, extensions to meshed and/or multiphase circuits are sometimes possible and discussed. Here this tutorial aspires to provide researchers and engineers with knowledge of the current state-of-the-art in tractable distribution grid learning and insights into future directions of work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

InP- and GaAs-Based 0.6 eV GaInAs Devices for Thermophotovoltaics and Laser Power Conversion

Emerging applications such as thermal energy grid storage, waste heat recovery and portable power generation require efficient thermophotovoltaic (TPV) converters tuned to temperatures near 1000 Degrees Celsius or below. Metamorphic GaInAs with larger lattice constants than InP present a promising option for these needs. The ability to grow these devices on GaAs substrates instead of more expensive InP would enhance the scalability of these devices. In this talk, we present inverted metamorphic Ga0.3In0.7As photovoltaic converters with sub-0.60 eV bandgaps grown on InP and GaAs substrates. These devices are realized using InAsP or GaInP/InAsP compositionally graded buffers which exhibit threading dislocation densities of 1.3 +/- 0.6 x 106 cm-2 and 8.9 +/- 1.7 x 106 cm-2 on InP and GaAs, respectively. Despite this difference in defect density, the devices generate similar open-circuit voltages of 0.386 V and 0.383 V, respectively, under irradiance producing a short-circuit current density of -10 A/cm2, with bandgap-voltage offsets of 0.20 and 0.21 V. We estimate their thermophotovoltaic efficiency using these measurements coupled with broadband reflectance measurments. The InP-based cell is estimated to yield 1.09 W/cm2 at 1100 Degrees Celsius vs. 0.92 W/cm2 for the GaAs-based cell, with TPV efficiencies of 16.8 vs. 9.2%. Both devices are limited by sub-bandgap absorption, which we assess largely occurs in the graded buffers. We estimate that the 1100 Degrees Celsius thermophotovoltaic efficiencies would increase to 24.0% and 20.7% in structures with the graded buffer removed, if previously demonstrated reflectance is achieved. These devices also have application as laser power converters in the 2.0-2.3 um atmospheric window. We estimate efficiencies of 36.8% and 32.5% under 2.0 um monochromatic irradiance of 1.86 W/cm2 and 2.81 W/cm2, respectively.

ENGINEERING,MATERIALS SCIENCE,SOLAR ENERGY↗
DOE OSTI2023

A pulsed current-mode class-D low-voltage high-bandwidth power amplifier for portable NMR systems

Low-field NMR has seen growing interest in recent years, especially for portable applications. The lower homogeneity magnets used for portable applications require short RF pulses to ensure enough transmit bandwidth to excite the sample volume and also support short echo periods. Furthermore, the preferred use of a high-Q coil to improve signal-to-noise ratio (SNR) prolongs the pulse transients. Thus, at such low Larmor frequencies, the excitation pulse transients become comparable or longer than the pulse length, such that the transmit bandwidth begins to limit measurement SNR. This paper describes the design of a pulsed current-mode class-D power (PCMCD) transmitter that addresses this issue by generating high power in a tuned sample coil while maintaining short transients, thus resulting in high output bandwidth. The transmitter also uses a charge recycling mechanism to maximize power efficiency for RF train excitation, which also results in faster pulse repetition rate and reduces allowable echo time. In this work, experimental results from a small form-factor PCMCD transmitter are presented. This design generates a peak RF power of 240 W into a 9.16 µH coil at 4 MHz while operating off a single 12 V power supply. NMR measurement results using the transmitter are also described, showing minimum achievable echo time of 70 µs and 25 µs depending on the transmitter mode of operation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Planarization of p -GaN surfaces on MOCVD grown V-defect engineered GaN-based LEDs

The large polarization barriers between the quantum wells and quantum barriers in long-wavelength GaN-based light-emitting diodes (LEDs) inhibit their performance by requiring excess driving voltages to reach standard operating current densities. Lateral injection of carriers directly into quantum wells is required to circumvent this issue. V-defects are naturally occurring inverted hexagonal defects with semipolar {$10\bar{1}1$}-plane sidewalls generated on surface depressions from threading dislocations. LEDs engineered to intentionally generate V-defects below the active region of the LED can achieve lateral carrier injection through the V-defect sidewalls and have already been able to demonstrate world record wall-plug efficiencies for LEDs in the green-red wavelengths. V-defects can be enlarged during kinetically limited growth where the growth rate of the c-plane GaN is faster than that of their sidewalls, leaving them unfilled. We report on the metal organic chemical vapor deposition growth conditions required to fill in V-defects with p-GaN during epitaxial growth of the LED post the active region. Circular transmission length measurements of Pd/Au contacts processed on p-GaN surfaces with various amounts of unfilled V-defects showed no significant difference in their sheet resistance and specific contact resistance. J–V measurements of LEDs grown with varying unfilled V-defect densities showed no significant difference in the forward bias regime. However, in the reverse bias regime, catastrophic breakdown occurred at markedly lower voltages for samples with larger unfilled V-defect densities. This suggests that unfilled V-defects may act as hotspots for device failure, and planarizing LED surfaces may help prevent early degradation of LED devices.

Chemical vapor deposition↗
DOE OSTI2024

Pure edge-dislocation half-loops in low-temperature Ga⁢N for V-defect formation

Lateral injection of carriers through semipolar crystallographic planes into c-plane QWs is one of the new frontiers in III-N light-emitting diodes (LEDs), especially for long wavelengths. Strategic use of V-defects has proven to be the most promising method for lateral injection, and creating optimal V-defect structure and density is an important research area for reducing forward voltage and increasing wall plug efficiency. Here, in this article, we present a novel method for forming V-defects in nominally unstressed low-temperature Ga⁢N through the generation of pure edge-dislocation half-loops. We present a detailed material science analysis of the loops via scattering-contrast electron microscopy. The loops have pure-edge character with Burgers vector 1/3 ⁢⟨$11\bar{2}0$⟩, and form in a sessile orientation on {$11\bar{2}0$} a-planes. The two arms of the loops are inclined such that the extra half-planes face down toward the growth substrate. The dislocation loops can be used to intentionally form V-defects through conditions of kinetically limited growth: these conditions also favor nucleation of V-defects at ∼100% of other threading dislocations in the Ga⁢N templates. Patterned sapphire substrates (PSS) are one of the most important substrates for III-N LED growth because of their superior light extraction. However, due to its low threading dislocation density, PSS have not been used extensively for V-defect LEDs. This work provides a pathway for improved control of V-defect formation and density on LEDs grown on sapphire with the goal of enabling uniform lateral injection in these V-defect engineered LEDs with low forward voltage, including PSS for high light extraction.

LEDs↗
DOE OSTI2025

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

GE Research and its partner Prolec GE have designed, built and deployed in the field the world’s first flexible power transformer. The flexible power transformer is a transmission class 3-phase autotransformer configurable in impedance and in voltage which allows it to serve as a universal spare for multiple units in a given fleet. However, the key innovation in this new concept is the online adjustable leakage impedance which allows the transformer to change its impedance without interrupting the transmission line operation. The flexible power transformer can be designed with up to three low voltage transmission class ratings and up to 12 impedance values changeable both online and offline. This report provides an overview of the design, manufacturing, testing, and commissioning of the 165kV, 60MVA prototype built including the results of the field performance validation tests. The prototype was specified in collaboration with Cooperative Energy, the utility host. It was designed and tested in the factory according to IEEE standard C57.12.00 and followed all protocols for transportation, installation, and commissioning of a power transformer. In addition to the prototype, a flexible protection system capable of automatically adjusting its settings upon the transformer impedance was also developed and deployed in the for testing and validation. On September 3, 2021 the prototype was energized in Cooperative Energy’s substation in Columbia, Mississippi to become the world’s first flexible power transformer in operation. Its performances and impact on the grid operation were demonstrated through different field tests. Results obtained confirm that the impedance of the flexible transformer can be varied under load through its full range, from 4.3% to 9.3%, without adverse impacts on the line operation, the protection system, the transformer stability and health condition. Results also proved that the flexible transformer is very effective in controlling power transfer through the line or load sharing between units operating in parallel. Indeed, it was proven that higher impedances decrease the thruput power of the transformer while lower impedances increase it. Up to 26MW was controllable on a line loading of 45MVA. It was also possible to demonstrate that the variation of the transformer impedance has no effect on the circulating current between units in parallel, except a minor transient during the impedance change. It was also proven that the flexible protection relay can update its protection settings automatically when the impedance change was detected. The prototype has operated continuously for more than 12 months now with a peak load exceeding 50MVA corresponding to >80% of its ONAN power rating. No alarm, trip or sign of failure has been reported by the utility. In addition to the development and deployment of the flexible transformer prototype, investigations were carried out on new nanodielectric fluids to replace the mineral oil used in power transformers with the goal of reducing their footprint and weight. The key parameters that were targeted for improvement included the breakdown voltage to reduce clearances between windings and tank hence the footprint; viscosity and thermal conductivity to increase the cooling efficiency and therefore to reduce the winding material. Several nanodielectric mixtures with mineral oil including with alumina (Al2O3), titania (TiO2) and Borum Nitrate (BN) with different surfactants have been analyzed and tested. Unfortunately, despite encouraging results no nanofluid candidate has been found viable to replace mineral oil. With the formulations tested, breakdown voltages are generally similar to mineral oil at lower particle contents and worse at higher particle contents. Viscosity appreciably increased at particles concertation over 2 wt% and thermal conductivity increased slightly at 5wt% and appears to be 10-15% higher at 10 wt% particle content. It is recommended to continue investigations to find solutions that can help increase the power density of future flexible power transformers. Flexible power transformers can significantly help the future power grid by providing more flexibility and resiliency. Indeed, by providing voltage and impedance flexibility, flexible power transformers reduce the need for multiple spares, hence inventory costs for utilities. With their online controllable impedance, they can provide support to the grid and help manage short-circuit currents, power flow, line congestion, and grid stability which will become more important with higher penetrations of intermittent renewable resources. During the field validation tests, it was demonstrated that up to 26MW was controllable on a line loading of 45MVA when the transformer impedance was varied from its minimum to its maximum range. Also, with the impedance range, the short-circuit currents could be reduced by up to 38% at the load side of the transformer. With its controllable impedance, flexible transformers can be used in future strategies of grid resilience to help better prepare the grid to face forecasted severe events including storms, heat waves and contingencies. The flexible power transformers can also find role in other applications including high voltage transmission cables such as offshore wind farms where solutions for energizing the cables and managing the reactive power are of critical importance. The designed flexible power transformer is now fully validated and ready for commercialization. Further analysis on the benefits of flexible power transformers for grid stability and short-circuit management including current limiting capability, reclosure and line restoration, control of inrush current, sizing of flexible AC components (FACTS) would help its rapid adoption by the industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Sub‐0.6 eV Inverted Metamorphic GaInAs Cells Grown on Inp and GaAs Substrates for Thermophotovoltaics and Laser Power Conversion

Abstract Inverted metamorphic Ga 0.3 In 0.7 As photovoltaic converters with sub‐0.60 eV bandgaps grown on InP and GaAs are presented. Threading dislocation densities are 1.3 ± 0.6 × 10 6 and 8.9 ± 1.7 × 10 6 cm −2 on InP and GaAs, respectively. The devices generate open‐circuit voltages of 0.386 and 0.383 V, respectively, under irradiance producing a short‐circuit current density of ≈10 A cm −2 , yielding bandgap‐voltage offsets of 0.20 and 0.21 V. Power and broadband reflectance measurements are used to estimate thermophotovoltaic (TPV) efficiency. The InP‐based cell is estimated to yield 1.09 W cm −2 at 1100 °C versus 0.92 W cm −2 for the GaAs‐based cell, with efficiencies of 16.8 versus 9.2%. The efficiencies of both devices are limited by sub‐bandgap absorption, with power weighted sub‐bandgap reflectances of 81% and 58%, respectively, the majority of which is assumed to occur in the graded buffers. The 1100 °C TPV efficiencies are estimated to increase to 24.0% and 20.7% in structures with the graded buffer removed, if previously demonstrated reflectance is achieved. These devices also have application to laser power conversion in the 2.0–2.3 µm atmospheric window. Peak laser power converter efficiencies of 36.8% and 32.5% are estimated under 2.0 µm irradiances of 1.86 and 2.81 W cm −2 , respectively.

14 SOLAR ENERGY↗