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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Engineering-Scale Test of a Water-Lean Solvent for Post-Combustion Capture

EPRI, Pacific Northwest National Laboratory, RTI International, and their project collaborators developed an engineering-scale test of a new water-lean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (EEMPA or 2-EEMPA) as a post-combustion CO 2 capture solvent for power plant applications. This test was conducted using the Pilot Solvent Test Unit at the National Carbon Capture Center. The primary objective of this test was to collect long-term data operating EEMPA with both coal- and natural gas-representative flue gases at the approximately 0.5 MW e -equivalent scale (5–10 metric tons CO 2 /day captured). This report details the activities preparing for that test, data collected during the test campaign, and analyses and interpretations of that data.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Technoeconomic Assessment of Phosphoric Acid and Rare Earth Element Recovery from Phosphoric Acid Sludge

Sustainability faces many challenges, including the availability of materials necessary for technological advancement. Rare earth elements (REEs), for example, are key materials for several manufacturing industries that can unlock renewable energy and sustainable development. In this study, a decanter centrifuge has been employed to successfully separated phosphoric acid and REE-containing particles from phosphoric acid sludge with concentrations ranging from 1000 to 2200 ppm REEs. Operating efficiently with up to 35 wt.% solids, the centrifuge was demonstrated to achieve approximately 95% phosphoric acid recovery and 90% REE recovery in a single pass, eliminating the need for additional processing steps. This breakthrough supports a proposed rare earth oxide (REO) recovery process integrating phosphoric acid (PA), elemental phosphorus (P4), and REO into two potential pathways: PA-REO and PA-P4-REO. These processes aim to reintroduce recovered phosphoric acid into the main product to significantly increase output and revenue. Post-separation, phosphorus-rich particles can be converted to P4, while REE-containing solids undergo further treatment including acid leaching, extraction/stripping, precipitation, and calcination to produce a marketable REO material. Technoeconomic analysis indicates promising profitability, with the PA-REO process showing a delta net present value (ΔNPV) of USD 441.8 million over a 12-year period and expected return within a year of construction, while the PA-P4-REO process yields a ΔNPV of USD 178.7 million over a 12-year return period. Both pathways offer robust financial prospects and demonstrate the feasibility of commercial-scale REO recovery from phosphoric acid sludge, offering an economically feasible approach to produce REEs for future sustainable development challenges related to sustainability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Three and Two Phase Rotating Field Inductive Couplers for Wireless Power Transfer with One Phase per Layer Windings

Multiphase inductive wireless charging coils have been proposed recently to improve coupler surface power density, reduce component stress and size, and provide near-constant power delivery to charge mobile electric systems. Several aspects for the fundamental characterization of multiphase coils are explored up to six phases including approximate mutual inductance with size and turn variation, induced voltage, and output power estimation. The relative component stress and size of passive components for resonant operation are compared between the multiphase variants. A combination of an experimentally validated 3D electromagnetic finite element analysis (FEA) and power electronic co-simulations are used to validate the estimated quantities approximated with a mixture of analytical equations and an artificial neural network model for mutual inductance. A novel three-phase transmitter, two-phase receiver coil pair is also proposed for electric vehicle charging to reduce the number of connections and compensation complexity on the vehicle-side with improved power output compared to a two-phase configuration.

Lewis, Donovin D. [University of Kentucky]↗
DOE OSTI2020

Multilevel Convergence Analysis of Multigrid-Reduction-in-Time

This study presents a multilevel convergence framework for multigrid-reduction-in-time (MGRIT) as a generalization of previous two-grid estimates. The framework provides a priori upper bounds on the convergence of MGRIT V- and F-cycles, with different relaxation schemes, by deriving the respective residual and error propagation operators. The residual and error operators are functions of the time-stepping operator, analyzed directly and bounded in the norm, both numerically and analytically. We present various upper bounds of different computational cost and varying sharpness. These upper bounds are complemented by proposing analytic formulae for the approximate convergence factor of V-cycle algorithms that take the number of fine grid time points, the temporal coarsening factors, and the eigenvalues of the time-stepping operator as parameters. The paper concludes with supporting numerical investigations of parabolic (anisotropic diffusion) and hyperbolic (wave equation) model problems. We assess the sharpness of the bounds and the quality of the approximate convergence factors. Observations from these numerical investigations demonstrate the value of the proposed multilevel convergence framework for estimating MGRIT convergence a priori and for the design of a convergent algorithm. We further highlight that observations in the literature are captured by the theory, including that two-level Parareal and multilevel MGRIT with F-relaxation do not yield scalable algorithms and the benefit of a stronger relaxation scheme. An important observation is that with increasing numbers of levels MGRIT convergence deteriorates for the hyperbolic model problem, while constant convergence factors can be achieved for the diffusion equation. The theory also indicates that L-stable Runge--Kutta schemes are more amendable to multilevel parallel-in-time integration with MGRIT than A-stable Runge--Kutta schemes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Advanced sorbents for modular oxygen production for REMS gasifiers

Under a DOE funded effort, Thermosolv LLC has been developing a sorbent-based oxygen production technology for gasification and oxy-combustion applications. The sorbents utilize oxygen-storage properties of certain perovskites to (1) selectively adsorb oxygen at moderate temperature from compressed air and (2) release the adsorbed oxygen into a vacuum or a sweep gas such as CO2 and/or steam. Through cyclic operations of multiple sorbent beds such a process can be made continuous. Pressure drop across the sorbent bed and other similar design considerations dictate that the sorbent be in the form of a high surface-area-to-volume pellet and yet still possess sufficient crush strength and integrity. Process efficiency is determined by the sorption and desorption kinetics and sorbent capacity. Typical process involves cycle times in the order of 100 seconds, a time too short to fully utilize the full volume of the sorbent and the sorption capacity of the sorbent pellets. As a part of this project, Thermosolv LLC undertook the development of oxygen sorbents as a high-surface area supported sorbent on a light-weight inert support to (1) reduce the cost, (2) increase the productivity, and (3) reduce the overall weight of the reactor. Using a previously developed perovskite (LSCF 1991) with its well-characterized performance, composite sorbent pellets each consisting of an inert core coated by a thin layer of the functional perovskite material were produced. Several low-density, inexpensive inert solids supports in the 1/8”-1/4” size were selected to keep the pressure drop across the sorbent bed in the acceptable range. A number of commercial technologies including spray coating, dip coating, incipient impregnation of porous substrate followed by thermal annealing at various temperatures and duration were employed and tested to produce robust composite supported sorbent pellets. A sense of optimum coating thickness was developed by testing sorbent pellets of various increasing diameter pellets. LSCF-1991extrudates ranging in size from 1/32” to 3/16” were tested in a TGA and in a fixed-bed pressure swing test set-up for sorption/desorption cycles of interest. The data show that for the operational conditions of interest the coating thickness for a supported sorbent pellet needs to be approximately 1/32” (about 0.8 mm). Subsequent work thereby concentrated on developing composite pellets of various substrates, shapes and sizes with coating layer of about this size range. Candidate support materials were chosen based on cost, inertness, mechanical strength, thermal expansion and chemical stability with sorbent material, and in a size range to give an acceptable pressure drop in fixed-bad reactor configurations. Coating application methods used for application of the sorbent onto the support included precipitation, spray coating and dip coating from sorbent slurries and sol gels. For all coated supports where we could successfully apply a uniform coating of desired thickness with an acceptable handling performance in terms of exfoliation, TGA-based cyclic sorption/desorption testing was performed to determine cycling capacity of oxygen. Among nearly twenty different support materials tested, best adhesion performance was obtained from stainless saddle supports. In the bench-scale fixed-bad tests stainless steel saddle support composite pellets with a coating thickness in the 0.6 mm or so range, the composite sorbent pellet performance approached up to 95% of that of the 2 mm parent material pellets. In a parallel approach to reducing the cost of the sorbent, alternate sorbent formulations replacing/reducing the amount of cobalt in the LSCF family were also investigated. Successful formulations that could match the performance of LSCF 1991 were identified based on TGA cyclic tests as LSCF 1919 and LSF 1910. In the range of operational envelop of cycle times and other relevant process operating conditions, the reduced Co formulations showed comparable performance in the bench-scale fixed-bad cyclic operations. As a part of this project, we also attempted substitution of La and Sr with Ca and Ba, and Co with Mn, Ni and Cu with little success, but the overall project goal of reducing sorbent cost in terms of raw material and manufacturing expenses was successful.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Volumetric recombination in EMC3-EIRENE: Implementation and first application to the pre-fusion power operation phase in ITER

An upgrade to the 3D plasma boundary model EMC3-EIRENE for detached divertor plasmas is introduced and evaluated. Stabilization of the iterative approximation of a self-consistent plasma–neutral gas solution is required at low divertor plasma temperatures, and this has been achieved by linearization of the energy loss term associated with the electron–neutral gas interaction. An implicit method for volumetric recombination has been implemented, which improves agreement with SOLPS-ITER results for the pre-fusion power operation phase in ITER. Resonant magnetic perturbations for control of edge localized modes are found to result in a partially detached divertor plasma with a significantly broader reduction of particle loads in the traditional strike zone, which is attributed to volumetric recombination. The additional non-axisymmetric far scrape-off layer strike points, on the other hand, remain attached at relatively high temperature so that volumetric recombination is not effective there.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Summary Paper: An Initial Heliostat Supply Chain Analysis

This paper summarizes the prior analysis, key findings, and recommendations from the published report titled “Initial Heliostat Supply Chain Analysis” [1]. Globally, the growing demand for concentrating solar power (CSP) technologies, primarily for electricity generation plants has been met with supply chains primarily composed of plentiful commodity materials such as steel, aluminum, and glass. Often the commodity materials can be sourced in the domestic market where power plant will be constructed. Although specialty components are required for CSP solar fields —including mirror panels used for heliostat applications—these specialty components constitute about 30-50% of total system installed costs [2]. Only a few companies and countries, including the United States, have developed the capacity to supply such specialty components. The U.S. heliostat supply chain at present is comprised of few companies (e.g., CSP developers), component suppliers, and is its infancy. By 2035, with current and aggressive solar photovoltaic (PV) capacity expansions, there is the potential for 500,000–1,500,000 direct and indirect jobs in the areas of manufacturing, installation and development, and operations and maintenance (O&M) [3]. Utilizing the CSP capacity estimations the recent NREL report [4], the construction of 39 gigawatts (GW) of CSP (assuming mainly power tower) in the U.S. could lead to approximately 195,000 manufacturing, construction, and O&M jobs. This does not include the longer-term jobs and economic impact (e.g., taxes from plant operations staff) from operating the plants once constructed. It is recommended that further CSP component and system supply chain analysis and modelling be undertaken.

Kurup, Parthiv (ORCID:0000000217356703)↗
DOE OSTI2024

Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators under Mesh Refinement

This paper analyzes a popular computational framework to solve infinite-dimensional Bayesian inverse problems, discretizing the prior and the forward model in a finite-dimensional weighted inner product space. We demonstrate the benefit of working on a weighted space by establishing operator-norm bounds for finite element and graph-based discretizations of Matérn-type priors and deconvolution forward models. For linear-Gaussian inverse problems, we develop a general theory to characterize the error in the approximation to the posterior. We also embed the computational framework into ensemble Kalman methods and MAP estimators for nonlinear inverse problems. Furthermore, our operator-norm bounds for prior discretizations guarantee the scalability and accuracy of these algorithms under mesh refinement.

Bayesian inverse problem↗
DOE OSTI2022

Machine Learning Derived Dynamic Operating Reserve Requirements in High-Renewable Power Systems

Accurately forecasting wind and solar power output poses challenges for deeply decarbonized electricity systems. Grid operators must commit resources to provide reserves to ensure reliable operations in the face of forecast errors, a process which can increase fuel consumption and emissions. We apply neural network-based machine learning to expand the usefulness of median point forecast data by creating probabilistic distributions of short-term uncertainty in demand, wind, and solar forecasts that adapt to prevailing grid conditions. Machine learning derived estimates of forecast errors compare favorably to estimates based on incumbent methods. Reserves derived from machine learning are usually smaller than values derived using incumbent methods, which enables fuel savings during most hours. Machine learning reserves are generally larger than incumbent reserves during times of higher forecast error, potentially improving system reliability. Performance is tested using multi-stage production simulation modeling of the California Independent System Operator (CAISO) system. Machine learning reserves provide production cost and greenhouse gas (GHG) emission reductions of approximately 0.3% relative to historical 2019 requirements. Savings in the 2030 timeframe are highly dependent on battery storage capacity. At lower levels of battery capacity, savings of 0.4% from machine learning reserves are shown. Significant quantities of battery storage are expected to be added to meet California's resource adequacy needs and GHG reduction targets. Addition of these batteries saturate reserve needs and results in minimal within-hour balancing costs in 2030.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Fixed-point quantum circuits for quantum field theories

Renormalization group ideas and effective operators are introduced to efficiently prepare ground states of massive lattice field theories on digital quantum devices. This is accomplished with a systematic approximation through localized unitaries that removes an exponentially costly barrier in the spatial volume of the quantum simulation. With these methods, classically computed ground states in a spatial volume L, containing a few Compton wavelengths, can be used to determine operators for preparing the ground state toward the thermodynamic limit with a precision improving as e –mL on beyond-classical quantum registers. Here, due to the exponential spatial decay of correlations in massive theories and the double exponential suppression of digitization artifacts in the number of qubits representing the scalar field, the derived fixed-point quantum circuits are expected to be relevant for simulations of quantum field theories throughout the evolution from small-scale near-term quantum devices to large-scale fault-tolerant quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Harvesting the low-hanging fruit of high energy savings -- Virtual Occupancy using Wi-Fi Data

Approximately 20% of primary energy consumed in the U.S. is attributed to HVAC use. Ideally, HVAC operation would be driven by actual building occupancy, but lack of reliable occupancy information often results in the use of conservative static schedules. This disparity is even more pronounced in a college campus, where the function of each space differs by building (classrooms, offices, libraries) and the class schedules change frequently -- every semester, day of week, and hour. While several research papers propose the use of counts of the Wi-Fi connections (e.g., phones, computers) as a proxy for occupancy, few real-world implementations exist. This paper describes the development and deployment of an open-source Wi-Fi-to-Occupancy software library in 65 buildings of a college campus, and the planned integration with the building energy management and control system at the building scale. Over a year of Wi-Fi data was gathered into distinct academic periods, including fall and spring semester, academic breaks, and summer sessions. Patterns such as students moving between classrooms, closing laptops before exams, etc., can be visualized from the data. Approximating occupancy from Wi-Fi data presents challenges which we address in this project -- for example, identifying static devices, or estimating the ratio of devices per person. Utilizing real-time occupancy data to inform optimal HVAC schedules and ventilation rates creates the potential to identify and reduce energy waste. Other potential applications include forecasting occupancy, and using Wi-Fi data to predict peak demands. Finally, the paper discusses how to easily scale these tools to other buildings.

Pritoni, Marco↗
DOE OSTI2022

Automating Component-Level Stress Measurements for Inverter Reliability Estimation

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous operating modes which induce new stresses on the power electronics components. In this work, an experimental and theoretical framework is introduced which couples laboratory-measured component stress with advanced inverter functionality and derives a reduction in useful lifetime based on an applicable reliability model. Multiple DER devices were instrumented to calculate the additional component stress under multiple reactive power setpoints to estimate associated DER lifetime reductions. A clear increase in switch loss was demonstrated as a function of irradiance level and power factor. This is replicated in the system-level efficiency measurements, although magnitudes were different—suggesting other loss mechanisms exist. Using an approximate Arrhenius thermal model for the switches, the experimental data indicate a lifetime reduction of 1.5% when operating the inverter at 0.85 PF—compared to unity PF—assuming the DER failure mechanism thermally driven within the H-bridge. If other failure mechanisms are discovered for a set of power electronics devices, this testing and calculation framework can easily be tailored to those failure mechanisms.

Flicker, Jack (ORCID:0000000212232154)↗
DOE OSTI2022

On the operational characteristics and economic value of pumped thermal energy storage

Pumped thermal energy storage (PTES) systems use an electrically-driven heat pump to store electricity in the form of thermal energy, and subsequently dispatch the stored thermal energy to generate electricity using a thermodynamic heat engine. Optimal day-ahead operational scheduling and annual value of a PTES system based on Joule-Brayton thermodynamic cycles and two-tank molten salt hot thermal storage is evaluated in this work. Production cost models, which simultaneously optimize commitment and dispatch schedules for an entire set of generators to minimize the cost of satisfying electricity demand, are employed to determine system-optimal operation and day-ahead energy value of the PTES system within each of six hypothetical near-future grid scenarios intended to approximately represent the U.S. Western Interconnection or the Texas Interconnection. Sensitivity to grid scenario (including the contribution of variable renewable energy sources), thermal storage capacity, relative heat pump and heat engine capacities, and startup/shutdown cycling costs are evaluated. PTES energy value and heat engine annual capacity factor increase strongly as the contribution of variable renewable resources increases, heat pump capacity increases relative to heat engine capacity, or PTES cycling costs decrease. Grid scenarios in which the contribution of variable renewable energy is dominated by solar photovoltaics (PV) vs. wind produce inherently different PTES operational patterns. Annual PTES energy value within PV-dominated scenarios increased with storage capacity only up to approximately seven hours of full-load discharge capacity, whereas that within wind-dominated scenarios exhibited a continual increase with storage duration up to at least 16 hours.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

High-Sensitivity rf Detection Using an Optically Pumped Comagnetometer Based on Natural-Abundance Rubidium with Active Ambient-Field Cancellation

To detect a specific radio-frequency (rf) magnetic field, rf optically pumped magnetometers (OPMs) require a static magnetic field to set the Larmor frequency of the atoms equal to the frequency of interest. However, unshielded and variable magnetic field environments (e.g., an rf OPM on a moving platform) pose a problem for rf OPM operation. Here, we demonstrate the use of a natural-abundance rubidium vapor to make a comagnetometer to address this challenge. Our implementation builds upon the simultaneous application of several OPM techniques within the same vapor cell. First, we use a modified implementation of an OPM variometer based on 87 Rb to detect and actively cancel unwanted external fields at frequencies ≲60 Hz using active feedback to a set of field control coils. In this experiment, we exploit this stabilized field environment to implement a high-sensitivity rf magnetometer using 85 Rb. Using this approach, we demonstrate the ability to measure rf fields with a sensitivity of approximately 9 fT Hz -1/2 inside a magnetic shield in the presence of an applied field of approximately 20 μT along three mutually orthogonal directions. This demonstration opens up a path toward completely unshielded operation of a high-sensitivity rf OPM.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Advanced Finite-Volume Numerics and Source Term Assumptions for Kernel and G-Equation Modelling of Propane/Air Flames

Here G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device. We tested the explicit (sub-cycled) vs. implicit formulation for the standard transport operators (advection, diffusion, compressibility). In addition to the accurate flame swept-volume method for chemistry and species source term, we developed a more accurate estimator for the burnt/unburnt split cell composition. Then, we developed a signed-distance-function (SDF) based method which provides a more stable reinitialization of the level-set field at every time-step. We found that simplifying assumptions common to several G-Equation implementations, for straightforward terms such as compressibility and advection, lead to large errors in predicting the propagation of even laminar flames, with deviations up to ~300% in simulated vs. formulated flame speed. Conversely, the enhanced numerics enabled through the SDF field reinitialization and improved chemistry source term improve simulation stability and smooth flame propagation even with significantly larger solver time-steps.

42 ENGINEERING↗
DOE OSTI2021

Optimization models for integrated biorefinery operations

Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.

09 BIOMASS FUELS↗
DOE OSTI2022

Quantum Simulation of Molecular Electronic States with a Transcorrelated Hamiltonian: Higher Accuracy with Fewer Qubits

Simulation of electronic structure is one of the most promising applications on noisy intermediate-scale quantum (NISQ) era devices. However, NISQ devices suffer from a number of challenges like limited qubit connectivity, short coherence times, and sizable gate error rates. Thus, desired quantum algorithms should require shallow circuit depths and low qubit counts to take advantage of these devices. Here, we attempt to reduce quantum resource requirements for molecular simulations on a quantum computer while maintaining the desired accuracy with the help of classical quantum chemical theories of canonical transformation and explicit correlation. In this work, compact ab initio Hamiltonians are generated classically, in the second quantized form, through an approximate similarity transformation of the Hamiltonian with (a) an explicitly correlated two-body unitary operator with generalized pair excitations that remove the Coulombic electron–electron singularities from the Hamiltonian and (b) a unitary one-body operator to efficiently capture the orbital relaxation effects required for accurate description of the excited states. The resulting transcorrelated Hamiltonians are able to describe both the ground and the excited states of molecular systems in a balanced manner. Using the variational quantum eigensolver (VQE) method based on the unitary coupled cluster with singles and doubles (UCCSD) ansatz and only a minimal basis set (ANO-RCC-MB), we demonstrate that the transcorrelated Hamiltonians can produce ground state energies comparable to the reference CCSD energies with the much larger cc-pVTZ basis set. This leads to a reduction in the number of required CNOT gates by more than 3 orders of magnitude for the chemical species studied in this work. Furthermore, using the quantum equation of motion (qEOM) formalism in conjunction with the transcorrelated Hamiltonian, we are able to reduce the deviations in the excitation energies from the reference EOM-CCSD/cc-pVTZ values by an order of magnitude. In conclusion, the transcorrelated Hamiltonians developed here are Hermitian and contain only one- and two-body interaction terms and thus can be easily combined with any quantum algorithm for accurate electronic structure simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Thermal Properties of Polymer Hole-Transport Layers Influence the Efficiency Roll-off and Stability of Perovskite Light-Emitting Diodes

While the performance of metal halide perovskite light-emitting diodes (PeLEDs) has rapidly improved in recent years, their stability remains a bottleneck to commercial realization. Here, we show that the thermal stability of polymer hole-transport layers (HTLs) used in PeLEDs represents an important factor influencing the external quantum efficiency (EQE) roll-off and device lifetime. We demonstrate a reduced EQE roll-off, a higher breakdown current density of approximately 6 A cm -2 , a maximum radiance of 760 W sr -1 m -2 , and a longer device lifetime for PeLEDs using polymer HTLs with high glass-transition temperatures. Furthermore, for devices driven by nanosecond electrical pulses, a record high radiance of 1.23 MW sr -1 m -2 and an EQE of approximately 1.92% at 14.6 kA cm -2 are achieved. Thermally stable polymer HTLs enable stable operation of PeLEDs that can sustain more than 11.7 million electrical pulses at 1 kA cm -2 before device failure.

14 SOLAR ENERGY↗