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At least 1,063 records · Page 59

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NASA NTRS2016

Solar Array at Very High Temperatures: Ground Tests

Solar array design for any spacecraft is determined by the orbit parameters. For example, operational voltage for spacecraft in Low Earth Orbit (LEO) is limited by significant differential charging due to interactions with low temperature plasma. In order to avoid arcing in LEO, solar array is designed to generate electrical power at comparatively low voltages (below 100 volts) or to operate at higher voltages with encapsulation of all suspected discharge locations. In Geosynchronous Orbit (GEO) differential charging is caused by energetic electrons that produce differential potential between the coverglass and the conductive spacecraft body in a kilovolt range. In such a case, the weakly conductive layer over coverglass, indium tin oxide (ITO) is one of the possible measures to eliminate dangerous discharges on array surface. Temperature variations for solar arrays in both orbits are measured and documented within the range of minus150 degrees Centigrade to plus 1100 degrees Centigrade. This wide interval of operational temperatures is regularly reproduced in ground tests with radiative heating and cooling inside a shroud with flowing liquid nitrogen. The requirements to solar array design and tests turn out to be more complicated when planned trajectory crosses these two orbits and goes closer to the Sun. The conductive layer over coverglass causes a sharp increase in parasitic current collected from LEO plasma, high temperature may cause cracks in encapsulating (Room Temperature Vulcanizing (RTV) material; radiative heating of a coupon in vacuum chamber becomes practically impossible above 1500 degrees Centigrade; conductivities of glass and adhesive go up with temperature that decrease array efficiency; and mechanical stresses grow up to critical magnitudes. A few test arrangements and respective results are presented in current paper. Coupons were tested against arcing in simulated LEO and GEO environments under elevated temperatures up to 2000 degrees Centigrade. The dependence of leakage current on temperature was measured, and electrostatic cleanness was verified for coupons with antireflection (AR) coating over the indium tin oxide (ITO) layer.

differential charging↗

NASA NTRS2015

North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends

The objective of this paper is to review statistical methods, dynamics, modeling efforts, and trends related to temperature extremes, with a focus upon extreme events of short duration that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). The statistics, dynamics, and modeling sections of this paper are written to be autonomous and so can be read separately. Methods to define extreme events statistics and to identify and connect LSMPs to extreme temperature events are presented. Recent advances in statistical techniques connect LSMPs to extreme temperatures through appropriately defined covariates that supplement more straightforward analyses. Various LSMPs, ranging from synoptic to planetary scale structures, are associated with extreme temperature events. Current knowledge about the synoptics and the dynamical mechanisms leading to the associated LSMPs is incomplete. Systematic studies of: the physics of LSMP life cycles, comprehensive model assessment of LSMP-extreme temperature event linkages, and LSMP properties are needed. Generally, climate models capture observed properties of heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreak frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Modeling studies have identified the impact of large-scale circulation anomalies and landatmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs to more specifically understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated. The paper concludes with unresolved issues and research questions.

Cold Spells↗

NASA NTRS2017

Rotational Raman-Based Temperature Measurements in a High-Velocity Turbulent Jet

Spontaneous rotational Raman scattering spectroscopy is used to acquire the first ever high quality, spatially-resolved measurements of the mean and root mean square (rms) temperature fluctuations in turbulent, high-velocity heated jets. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 50 mm diameter nozzle operating from subsonic to supersonic conditions over a wide range of temperatures and Mach numbers, in accordance with the Tanna matrix frequently used in jet noise studies. These data were acquired in the hostile, high noise (115 dB) environment of a large scale open air test facility at NASA Glenn Research Center (GRC). Temperature estimates were determined by performing nonlinear least squares fitting of the single shot spectra to the theoretical rotational Stokes spectra of N2 and O2, using a custom in-house code developed specifically for this investigation. The laser employed in this study was a high energy, long-pulsed, frequency doubled Nd:YAG laser. One thousand single-shot spectra were acquired at each spatial coordinate. Mean temperature and rms temperature variations were calculated at each measurement location. Excellent agreement between the averaged and single-shot temperatures was observed with an accuracy better than 2.5 percent for temperature, and rms variations in temperature between +/-2.2 percent at 296 K and +/-4.5 percent at 850 K. The results of this and planned follow-on studies will support NASA GRC's development of physics-based jet noise prediction, turbulence modeling and aeroacoustic source modeling codes.

Randy J Locke↗

NASA NTRS2016

Normalized Temperature Contrast Processing in Infrared Flash Thermography

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

Koshti, Ajay M.↗

NASA NTRS2017

Rotational Raman-Based Temperature Measurements in a High-Velocity Turbulent Jet

Randy J Locke↗

NASA NTRS2020

Temperature-Dependent Changes in the Normal Albedo of the Lunar Surface at 1064 nm

Over the extreme temperature variations experienced in a single lunar day (∆T≈300 K), particular minerals common to the lunar surface show spectral changes at near-infrared wavelengths in laboratory settings (Singer and Roush, 1985; Roush and Singer, 1986, 1987). Variations in temperature can cause variations in the size and shape of crystallographic sites, which control the position, shape, and depth of crystal field absorptions. At an observation wavelength of 1064 nm, the Lunar Orbiter Laser Altimeter (LOLA) should be highly sensitive to temperature-dependent changes of orthopyroxene. Here we analyze temperature-dependent spectral changes of the lunar surface as measured from orbit by LOLA. We couple LOLA measurements of normal albedo with measurements of surface temperature from the Diviner Lunar Radiometer Experiment, analyzing the maria and highlands terranes between ±50° in 1°x1° spatial bins. We provide the first evidence of temperature-dependent spectral changes on the lunar surface from orbital observations, finding that the majority of the lunar surface between 50°N and 50°S demonstrates a small, yet measurable, negative change in normal albedo at 1064 nm with temperature (-∆R/∆T). The measurable effect is on the order of a few percent change in reflectance per ~80 K, indicating temperature changes do not have a large effect on measurements of albedo at the sensitivity of the LOLA instrument. Stronger -∆R/∆T values tend to be associated with the maria, and regions with elevated orthopyroxene levels. Our results suggest that single-wavelength lasers may be powerful tools for understanding the distribution of particular minerals on the lunar surface.

Ariel N Deutsch↗

NASA NTRS2020

An Algorithm to Derive Temperature and Humidity Profile Changes Using Spatially and Temporally Averaged Spectral Radiance Differences

A linear inversion algorithm to derive changes of surface skin temperature and atmospheric temperature and specific humidity vertical profiles using spatially and temporally averaged spectral radiance differences is developed. The algorithm uses spectral radiative kernels, which is the top-of-atmosphere spectral radiance change caused by perturbations of skin temperature and air temperature and specific humidity in the atmosphere, and is an improved version of the algorithm used in earlier studies. Two improvements are the inclusion of the residual and cloud spectral kernels in the form of eigenvectors of principal components. Three and six eigenvectors are used for, respectively, the residual and cloud spectral kernels. An underlying assumption is that the spectral shape of the principal components is constant and their magnitude varies temporally and spatially. The algorithm is tested using synthetic spectral radiances with the spectral range of the Atmospheric Infrared Sounder averaged over 16 days and over a 10° × 10° grid box. Changes of skin temperature, air temperature, and specific humidity vertical profiles are derived from the difference of nadir-view all-sky spectral radiances. The root-mean-square difference of retrieved and true skin temperature differences is 0.59 K. The median of absolute errors in the air temperature change is less than 0.5 K above 925 hPa. The median of absolute errors in the relative specific humidity changes is less than 10% above 825 hPa.

Fang Pan↗

NASA NTRS2020

Select Electronic Parts Operation at Extreme Low Temperature

The purpose of the study presented in this paper is to extend the test period of a selected set of electronics parts at cryogenic condition to dwell period of about 24 hours to demonstrate extreme cold operational capability of these components. The parts tested are tantalum polymer, BX and P90 type ceramic capacitors, thick film resistors, analog multiplexers, a digital inverter, and a D-flip-flop. These parts were tested to assist identifying candidate components that can be used for development of a cold capable telemetry board. There are several past investigations that have shown that COTS (commercial-off-the-shelf) capacitors and resistors tested at cryogenic temperatures and frequencies up to 10MHz did not exhibit significant changes in capacitance and resistance values. Also, there are several test results for active parts. These past tests collected measurements during a temperature sweep from room temperature down to cryogenic temperature with very short dwell time at cryogenic temperature, and back to room temperature. This study extends the operational dwell time to at least 24 hours and returning to room temperature operation without significant degradation in performance, thus, demonstrating the potential for longer dwell time in actual operation in these extreme cold temperatures and a method for identifying the cold operability.

Ashtijou, Mohammad↗

NASA NTRS2024

Core Body Temperature Predictions Using Metabolic Energy Expenditure and Heart Rate During Simulated Extravehicular Activity

Long duration spaceflight missions will require crew to become more autonomous in conducting extravehicular activities (EVA) without direct communication with Mission Control for biomedical support. To enable such autonomy, we are developing a Crew State and Risk Model (CSRM) as a collection of key physiology domains that drive EVA crew capabilities and workloads. One model component of CSRM is human thermal regulation. In this paper, customized development of a baseline model to predict core body temperature is presented using physiology inputs of heart rate and metabolic rate. The model development dataset included a baseline study where participants (n=6, equal male and female) performed a 5-hour EVA in a two-part session while wearing a hybrid space suit simulator (HS3). The first session included an end-to-end EVA traversing 1500 meters to a geology site and traversing back to a habitat conducting geology, payload relocation, and maintenance operations every 500 meters. The second session included standalone tasks of a 2000-meter traverse followed by geology tasks. Thermal measures of core body temperature, local skin temperature, liquid cooling garment temperature, heart rate, and metabolic rate were collected through the test duration. Multiple regression was used to build a linear equation to predict core body temperature from inputs of heart rate and metabolic rate. Heat storage was calculated via predicted core body temperature plus LCG and skin temperatures. The model was tested against a dataset from a pressurized suited test (n=6, equal male and female) in the NASA Active Response Gravity Offload System (ARGOS) conducting similar end-to-end EVA and standalone tasks. Predicted error of the model against the raw test cases was 0.2±0.15 °C. The baseline prediction of core body temperature using heart rates and metabolic rates allows for simple real-time tracking from data collected in-flight to monitor crew consumables and thermal flight limits during EVA.

Bradley Hoffmann↗

NASA NTRS2021

Global Intercomparison of hyper-resolution ECOSTRESS coastal sea surface temperature measurements from the Space Station with VIIRS-N20

The ECOSTRESS multi-channel thermal radiometer on the Space Station has an unprecedented spatial resolution of 70 m and a return time of hours to 5 days. It resolves details of oceanographic features not detectable in imagery from MODIS or VIIRS, and has open-ocean coverage, unlike Landsat. We calibrated two years of ECOSTRESS sea surface temperature observations with L2 data from VIIRS-N20 (2019–2020) worldwide but especially focused on important upwelling systems currently undergoing climate change forcing. Unlike operational SST products from VIIRS-N20, the ECOSTRESS surface temperature algorithm does not use a regression approach to determine temperature, but solves a set of simultaneous equations based on first principles for both surface temperature and emissivity. We compared ECOSTRESS ocean temperatures to well-calibrated clear sky satellite measurements from VIIRS-N20. Data comparisons were constrained to those within 90 min of one another using co-located clear sky VIIRS and ECOSTRESS pixels. ECOSTRESS ocean temperatures have a consistent 1.01 ◦C negative bias relative to VIIRS-N20, although deviation in brightness temperatures within the 10.49 and 12.01 µm bands were much smaller. As an alternative, we compared the performance of NOAA, NASA, and U.S. Navy operational split-window SST regression algorithms taking into consideration the statistical limitations imposed by intrinsic SST spatial autocorrelation and applying corrections on brightness temperatures. We conclude that standard bias-correction methods using already validated and well-known algorithms can be applied to ECOSTRESS SST data, yielding highly accurate products of ultra-high spatial resolution for studies of biological and physical oceanography in a time when these are needed to properly evaluate regional and even local impacts of climate change.

Nicolas Weidberg↗

DOE OSTI2020

Development and Test of High Temperature Surface Acoustic Wave Gas Sensors

The demand for sensors in hostile environments, such as power plant environments, aerospace environments, oil and gas extraction, and high-temperature metallurgy environments, has risen over the past decades in a continuous attempt to increase process control, improve energy and process efficiency in production, reduce operational and maintenance costs, increase safety, and perform condition-based maintenance in equipment and structures operating in high-temperature harsh-environment conditions. The increased reliability, improved performance, and development of new sensors and networks with a multitude of components, especially wireless networks, are the target for operation in harsh environments. Gas sensors, in particular H2 sensors, operating above 200 C are required in the instrumentation, process control and general safety of a number of industries including coal, natural gas, and nuclear power generation facilities, the aerospace and automotive industries, metallurgical production and defense-related applications. The surface acoustic wave (SAW) platform is a particularly promising option for high-temperature, harsh-environment gas sensing applications since the platform exhibits advantages, such as battery-free and wireless operation, small size, possibility for scale production using well-developed technologies from the semiconductor industry, and low cost of installation and operation. In this work, one-port SAW resonators (SAWRs) operating along five different orientations on a commercially available langasite (LGS) wafer employing Pt-Al2O3 electrodes and reflectors were designed, fabricated, and used as high-temperature H2 sensors. Two of the selected orientations were predicted and confirmed to have temperature-compensated operation above 150 C. A gas sensor test setup was developed, capable of gas cycling between N2, O2 and N2/H2 mixtures under extended high-temperature periods (up to 650 C for over 20 hours). Thin film Pt-Al2O3 was used as the electrode material for the transducers and reflectors capable of high-temperature operation, and also as H2 sensing film. In addition, yttria-stabilized zirconia (YSZ) thin films with Pt decoration were tested as sensing films aimed to enhance the SAWR sensor response to H2. The SAW devices were monitored in excess of 1700 hours in real-time during gas cycling sequences up to 600 C, leading to the following findings: i) the Pt-Al2O3 electrodes performed better for H2 sensing than the Pt-decorated YSZ sensing film, showing as much as 50% higher frequency variation response in the 200 C to 400 C range; ii) different crystallographic orientations operating on the same LGS wafer experienced different responses to H2 exposures up to 500 C; iii) the surface oxidation state of the SAWR sensors was shown to have an important impact on subsequent H2 exposure responses. In addition, a sensor system employing two LGS SAWRs, aligned along two different orientations, has been developed to simultaneously determine H2 presence and temperature. Finally, wireless interrogation of a SAWR sensor was successful within the gas cycling test fixture, and successful wireless H2 detection was achieved above 400 C.

Ayes Moncada, Armando↗

DOE OSTI2023

Temperature Rise on Liner Surfaces of Fuel Cell Electric Vehicle Tanks during Fueling Process

Herein, the temperature of the inner tank walls, or plastic liners, of composite pressure tanks in fuel cell electric vehicles during fueling using three‐dimensional computational fluid dynamics (CFD) models is evaluated. The liner materials are limited to 85.0 °C to prevent thermal stress causing material failure that would result in a hydrogen leak. Therefore, the temperature of hydrogen gas must be limited to below 85.0 °C during the fueling process as dictated by the current fueling protocol. However, there are limited experimental or simulation data confirming that the temperature changes do not exceed the threshold. Herein, the liner temperatures with CFD tank models for two sizes of type IV tanks representative of the upper and lower system bounds that are close to the SAE J2601 fueling protocol (36.0 and 244.0 L) are evaluated. First, each model's reliability is validated with experimental data and then analyzed, and the data are used to evaluate the maximum hydrogen and liner temperatures under real‐world fueling conditions. The evaluation shows that the maximum liner surface temperature of each tank model is at least 7 °C lower than that of the hydrogen. Additionally, there is at least 12 °C difference found between the upper limit and actual liner temperatures.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Effects of cryogenic temperature and grain size on fatigue-crack propagation in the medium-entropy CrCoNi alloy

CrCoNi-based high-entropy alloys have demonstrated outstanding mechanical properties, particularly at cryogenic temperatures. Here we investigate the fatigue-crack propagation properties of the equiatomic, single-phase, face-centered cubic, medium-entropy alloy (MEA), CrCoNi, that displays exceptional strength, ductility and toughness, all of which are enhanced at cryogenic temperatures. Fatigue-crack growth is examined, at a load ratio of 0.1 over a wide range of growth rates, from ~10 –11 to >10 –7 m/cycle, at room (293 K) and cryogenic (198 K, 77 K) temperatures for two grain sizes (~7 and 68 µm), with emphasis on near-threshold behavior. We find that the ΔK th fatigue thresholds are increased with decreasing temperature and increasing grain size: from 5.7 MPa√m at 293 K to 8 MPa√m at 77 K in the fine-grained alloy, and from 9.4 MPa√m at 293 K to 13.7 MPa√m at 77 K in the coarse-grained alloy. Mechanistically, transgranular cracking at 293 K transitions to a mixture of intergranular and transgranular at cryogenic temperatures, where the increased propensity of nano-twins appears to inhibit growth rates by deflecting the crack path. However, the main factor affecting near-threshold behavior is roughness-induced crack closure from interference between the crack flanks, which is enhanced by the rougher fracture surfaces at low temperatures, particularly in the coarser-grained microstructure. Here, fatigue-crack propagation behavior in CrCoNi is comparable to nickel-based superalloys but is superior to that of the high-entropy CrMnFeCoNi (Cantor) alloy and many high-strength steels, making the CrCoNi alloy an excellent candidate material for safety-critical applications, particularly involving low temperatures.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Machine learning based simultaneous control of air handling unit discharge air and condenser water temperatures set-point for minimized cooling energy in an office building

In this study, an artificial intelligence based real-time prediction and control model to optimize condenser water temperature and discharge air temperature (DAT) set-points in water-cooled air handling unit (AHU) system has been developed. EnergyPlus-MATLAB co-simulation has been conducted to analyze the developed model's effectiveness. Here, to develop artificial neural networks (ANN) model, embedded neural network objects in MATLAB was utilized. The developed model could decide an optimal temperature set-points based on outdoor air wet-bulb temperature to reflect the Korean climate context. As a result, the developed ANN prediction model showed the predictive performance of Cv(RMSE) of approximately 21%. Compared to the conventional fixed temperature algorithm, which fixes AHU DAT at 14°C and condenser water temperature at 32°C, the ANN based optimized control showed a 22% total cooling energy reduction. These results show that significant energy savings can be achieved by simultaneously controlling condenser water temperature and AHU DAT set-points considering Korean climatic characteristics using AI technologies such as ANN models.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Deep Learning Advances Arctic River Water Temperature Predictions

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0°C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation—factors associated with energy balance—were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Sound Speed as a Candidate for Internal Temperature Monitoring During Solid Phase Processing of Materials

Internal temperature is an important parameter for understanding the solid phase processing (SPP) of materials and improving feedback control of these processes. Friction stir processes, shear assisted processing and extrusion (ShAPE ™ ), and ultrahigh velocity (UHV) cold spray are examples of such processes. Simple thermal models based on temperatures measured at the boundary of the deforming body cannot capture the dynamic nature of temperature generation within the deforming solid. One possibly way of understanding internal temperature is by measuring sound speed, which varies as a function of temperature for materials and directing ultrasonic wave propagation through selected material volumes of interest. In this project, longitudinal wave speed is estimated for aluminum 6061. Piezoelectric materials bonded to a specimen provided data from which longitudinal wave speed was estimated. A discussion evaluated the linear relationship of wave speed versus temperature and postulated how wave speed measurements could be used to estimate the internal temperature of selected material volumes for feedback during SPP of materials. Instrumentation, data and analysis, and a discussion are reviewed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Superior High-Temperature Strength in a Supersaturated Refractory High-Entropy Alloy

Refractory high-entropy alloys (RHEA) show promising applications at high temperatures. However, achieving high strengths at elevated temperatures above 1,173K is still challenging due to heat softening. Using intrinsic material characteristics as the alloy-design principles, a single-phase body-centered-cubic (BCC) CrMoNbV RHEA with high-temperature strengths (beyond 1,000 MPa at 1,273 K) is designed, superior to other reported RHEAs as well as conventional superalloys. The origin of the high-temperature strength is revealed by in-situ neutron scattering, transmission-electron microscopy, and first-principles calculations. The CrMoNbV’s elevated-temperature strength retention up to 1,273 K arises from its large atomic-size and elastic-modulus mismatches, the insensitive temperature dependence of elastic constants, and the dominance of non-screw character dislocations caused by the strong solute pinning, which makes the solid-solution strengthening pronounced. The alloy-design principles and the insights in this study pave the way to design RHEAs with outstanding high-temperature strength.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A Fast‐Charging and High‐Temperature All‐Organic Rechargeable Potassium Battery

Abstract Developing fast‐charging, high‐temperature, and sustainable batteries is critical for the large‐scale deployment of energy storage devices in electric vehicles, grid‐scale electrical energy storage, and high temperature regions. Here, a transition metal‐free all‐organic rechargeable potassium battery (RPB) based on abundant and sustainable organic electrode materials (OEMs) and potassium resources for fast‐charging and high‐temperature applications is demonstrated. N‐doped graphene and a 2.8 m potassium hexafluorophosphate (KPF 6 ) in diethylene glycol dimethyl ether (DEGDME) electrolyte are employed to mitigate the dissolution of OEMs, enhance the electrode conductivity, accommodate large volume change, and form stable solid electrolyte interphase in the all‐organic RPB. At room temperature, the RPB delivers a high specific capacity of 188.1 mAh g −1 at 50 mA g −1 and superior cycle life of 6000 and 50000 cycles at 1 and 5 A g −1 , respectively, demonstrating an ultra‐stable and fast‐charging all‐organic battery. The impressive performance at room temperature is extended to high temperatures, where the high‐mass‐loading (6.5 mg cm −2 ) all‐organic RPB exhibits high‐rate capability up to 2 A g −1 and a long lifetime of 500 cycles at 70–100 °C, demonstrating a superb fast‐charging and high‐temperature battery. The cell configuration demonstrated in this work shows great promise for practical applications of sustainable batteries at extreme conditions.

25 ENERGY STORAGE↗