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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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Optimal fingerprinting is applied to estimate the amount of time it would take to detect warming by increased concentrations of carbon dioxide in monthly averages of temperature profiles over the Indian Ocean.
Photonic integrated circuits incorporating intersubband transitions are ideal for mid-infrared and terahertz nanophotonics. However, the design of epitaxies has long been inhibited by two factors: the modest predictivity of ab initio theory and the absence of absolute intersubband gain and loss measurements under operating conditions. Existing measurements either yield inaccurate gain profiles or do not accurately assess dependence on frequency, bias, and temperature. Here, we present a delay-resolved absolute-referencing method for accurate gain evaluation without these limitations, addressing a long-standing challenge. By creating a photonic circuit that allows broadband pulses to traverse different lengths of a gain medium, we measure the absolute transmission of intersubband structures. Gain profiles match theoretical predictions at lower temperatures, with gain and dispersion clamping after lasing, and faster-than-expected degradation occurs at higher temperatures. Our approach provides a precise experimental evaluation of temperature-dependent gain performance and gives insight into optimizing temperature performance and frequency comb designs.
Typical calibration for catalyst thermal management for compression-ignition engines involves delaying the post-injection into the expansion stroke. Reduced work extraction due to the late heat release event is used to increase the exhaust gas temperature to shorten the time associated with reaching optimal temperatures for aftertreatment systems. Shorter catalyst heat-up time can simultaneously reduce tail-pipe emissions and the typical fuel penalties associated with this mode of operation. In this study, the effects of volatility, reactivity, and oxygen content of the fuel on combustion stability and emissions were studied in a light-duty single-cylinder research engine. Blends of iso-octane/ n-heptane and farnesane/ 2,2,4,4,6,8,8-heptamethylnonane were used to study the impacts of volatility and reactivity. At constant reactivity, little to no variation in combustion performance was observed due to differences in volatility. On the other hand, increased reactivity improved combustion stability and efficiency at late injection timings (+24 CAD). The combined effect of increase in chemical reactivity and oxygen content was analysed by comparing the baseline #2 diesel operation with two blends of mono-ethers and #2 diesel to achieve cetane numbers (CNs) of 45 and 55, and a pure blend of mono-ether components with CN > 100. Fuels with higher reactivity and oxygen content were found to reduce engine-out hydrocarbon and carbon mono-oxide emissions while also achieving stable combustion at post-injection timings later than those achievable with diesel fuel. The pure ether-blend had the latest achievable post-injection timing (≥+26 CAD) while still maintaining stable combustion. At similar combustion stability, the pure ether blend was found to have 2.8% higher combustion efficiency and 4.3% higher thermal efficiency than the baseline diesel. The ether-diesel blends at CN45 and CN55 were found to have 1.8% higher combustion efficiency than baseline diesel. The results demonstrate that fuels with increased reactivity can increase combustion efficiency, reducing carbon monoxide and hydrocarbon emissions, while maintaining similar exhaust temperature and combustion stability compared to baseline diesel. Further greenhouse gas benefits can also be realized as the mono-ether bioblendstocks show potential for >50% reduction in greenhouse gas emissions relative to diesel fuel based on their production method.
Optimal temperature control design using IBM 7094 digital computer program for thermal environment simulation of stabilized multisurfaced earth- orbiting spacecraft structure
Thermochromic variable emittance coatings (VECs) allow for passive, dynamic thermal management of space vehicles due to their temperature dependent optical properties. Ideally, a thermochromic material should exhibit low mid-IR emissivity for lower temperatures and switch to high mid-IR emissivity for higher temperatures; one promising material that demonstrates these characteristics is Lanthanum Strontium Manganite (LSM). The transition temperatures of LSM are dependent on the Lanthanum-to-Strontium ratio x, La1-xSrxMnO3. La0.8Sr0.2MnO3, which has an emittance of 0.5 for < 270 K, then a linear increase in emittance to 0.8 over an increase of 70 K where it will saturate at ~340K, is commonly utilized but this is tunable by changing the Sr concentration. The tunability of the transition temperature range of LSM motivates a need to understand the optimal thermal transition range for human spacecraft. Additionally, LSM has high solar absorptance and to combat this issue the VEC will be micropatterned on top of a highly solar reflective layer of Barium Sulfate (BaSO4). Consequently, this work will elucidate the tradeoffs between solar absorptance and variable emittance for this technology since the micropattern adversely couples the solar absorptance to the mid-IR emittance. This work develops a computational model using Thermal Desktop to study the utility of VECs on human spacecraft, such as Orion, subjected to mission phases such as lunar transit and Gateway docking. The model considers both external heat loads, from solar irradiation and planetary IR, as well as vehicle heat loads, from avionics and crew, as an input into the body mounted thermochromic radiators. There are several design targets for VECs, i.e. achieving the largest change in emittance, finding the optimal temperature range for the transition, and achieving the highest emittance in the high temperature phase. This work prioritizes these design targets for LSM to achieve the optimal heat rejection for a human spacecraft. The VECs are compared with static emittance coatings and the efficiency gains are quantified. Thermochromic VECs will ultimately lead to simplifications of active cooling systems which synergistically correlates to mass reduction and less energy consumption for space vehicles.
Films of BCSCO superconductor of the type Bi2CaSr2Cu2Ox have been grown by liquid phase epitaxy method (LPE), using a partially closed growth chamber. The films were grown on (001) and (110) NdGaO3 substrates by slow cooling process in an optimized temperature range below the peritectic melting point (880 C) of Bi2CaSr2Cu2O8. Optimization of parameters, such as seed rotation, soak of initial growth temperature and growth period results in the formation of 2122 phase BCSCO films. The films grown at rotation rates of less than 30 and more than 70 rpm are observed to be associated with the second phase of Sr-Ca-Cu-O system. Higher growth temperatures (is greater than 860 C) also encourage to the formation of this phase. X-Ray Diffraction (XRD) measurements show that the films grown on (110) NdGaO3 have a preferred (11 n)-orientation. It is pertinent to mention here that in our earlier results published elsewhere we obtained c-axis oriented Bi2CaSr2Cu2O8 phase films on (001) NdGaO3 substrate. Critical current density is found to be higher for the films grown on (110) than (001) NdGaO3 substrate orientation. The best values of zero resistance (T(sub co)) and critical current density obtained are 87 K and 105 A/sq cm, respectively.
Films of BCSCO superconductor of the type Bi2CaSr2Cu2O(x), have been grown by liquid phase epitaxy method (LPE), using a partially closed growth chamber. The films were grown on (001) and (110) NdGaO3 substrates by slow cooling process in an optimized temperature range below the peritectic melting point (880 C) of Bi2CaSr2Cu2O8. Optimization of parameters, such as seed rotation, soak of initial growth temperature and growth period results in the formation of 2122 phase BCSCO films. The films grown at rotation rates of less than 30 and more than 70 rpm are observed to be associated with the second phase of Sr-Ca-Cu-O system. Higher growth temperatures (greater than 860 C) also encourage to the formation of this phase. XRD measurements show that the films grown on (110) NdGaO3 have a preferred (11n)-orientation. It is pertinent to mention here that in our earlier results published elsewhere we obtained c-axis oriented Bi2CaSr2Cu2O8 phase films on (001) NdGaO3 substrate. Critical current density is found to be higher for the films grown on (110) than (001) NdGaO3 substrate orientation. The best values, zero resistance (T(sab co)) and critical current density obtained are 87 K and 10(exp 5) A/sq cm respectively.
Thermophiles and hyperthermophiles are those organisms which grow at high temperature (> 40°C). The unusual properties of these organisms have received interest in multiple fields of biological research, and have found applications in biotechnology, especially in industrial processes. However, there are few listings of thermophilic and hyperthermophilic organisms and their relevant environmental and physiological data. Such repositories can be used to standardize definitions of thermophile and hyperthermophile limits and tolerances and would mitigate the need for extracting organism data from diverse literature sources across multiple, sometimes loosely related, research fields. Therefore, we have developed ThermoBase, a web-based and freely available database which currently houses comprehensive descriptions for 1238 thermophilic or hyperthermophilic organisms. ThermoBase reports taxonomic, metabolic, environmental, experimental, and physiological information in addition to literature resources. This includes parameters such as coupling ions for chemiosmosis, optimal pH and range, optimal temperature and range, optimal pressure, and optimal salinity. The database interface allows for search features and sorting of parameters. As such, it is the goal of ThermoBase to facilitate and expedite hypothesis generation, literature research, and understanding relating to thermophiles and hyperthermophiles within the scientific community in an accessible and centralized repository. ThermoBase is freely available online at the Astrobiology Habitable Environments Database (AHED; https://ahed.nasa.gov), at the Database Center for Life Science (TogoDB; http://togodb.org/db/thermobase), and in the S1 File.
Both natural biomaterials and synthetic materials benefit from complex energy landscapes that provide the foundation for structure–function relationships and environmental sensitivity. Understanding these nonequilibrium dynamics is important for the development of design principles to harness this behavior. Using a model system of poly(ethylene glycol) methacrylate-based thermoresponsive lower critical solution temperature (LCST) copolymers, we explored the impact of composition and stimulus path on nonequilibrium thermal hysteretic behavior. Through turbidimetry analysis of nonsuperimposable heat–cool cycles, we observe that LCST copolymers show clear hysteresis that varies as a function of pendent side chain length and hydrophobicity. Hysteresis is further impacted by the temperature ramp rate, as insoluble states can be kinetically trapped under optimized temperature protocols. As a result, this systematic study brings to light fundamental principles that can enable the harnessing of out-of-equilibrium effects in synthetic soft materials.
Nitrogen-doped zinc selenide telluride (N:ZnSe x Te 1−x ) is of interest because it is one of the widest-gap II–VI semiconductors that can still be doped p-type with reasonably high hole concentrations. We sputter deposit N:ZnSe x Te 1−x films, varying Se/(Se + Te), or x, from 0 to 0.7, N 2 flow rate from 0.25 to 0.75 sccm, and substrate temperature from 250 to 370 °C. Increasing x from 0 to 0.39 at the optimal temperature of 370 °C and N 2 flow rate of 0.5 sccm leads to 1.3 atomic % nitrogen incorporation and wurtzite phase stabilization. Such doping and alloying increases hole concentration from 3 × 10 18 cm −3 to 3 × 10 19 cm −3 , although mobility drops from 0.4 to 0.02 cm 2 V −1 s −1 . Our sputtered N:ZnSe 0.38 Te 0.62 has an absorption onset 0.1 eV greater than the ZnTe value of 1.87 eV. Increasing x from 0 to 0.51 enhances transmittance by moving absorption onset from 1.87 to 2.11 eV with diminished band gap bowing likely due to disorder, and increases the work function from 5.12 to 5.42 eV. This combination of tunable properties makes sputtered N:ZnSe x Te 1−x desirable for transparent p-type contacts in polycrystalline Cd(Se,Te) optoelectronic devices.
Abstract. One notable observation of enzymatic chemical reactions is that, for a given abundance of enzymes and substrates, temperature increases cause reaction rates to first increase consistent with the Arrhenius relationship, then plateau, and finally fall off quickly to zero at high temperatures. While many mathematical functions have been used to describe this pattern, we here propose a chemical kinetics theory which successfully replicates this observation and provides insights into the processes responsible for these dynamics. The chemical kinetics theory combines the law of mass action, von Smoluchowski's diffusion-limited chemical reaction theory, and Eyring's transition state theory. This new theory reveals that the thermally reversible enzyme denaturation ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution explains the plateau and subsequent decrease in chemical reaction rates with increasing temperature. The temperature-dependent affinity parameter (K) that relates enzymes and substrates through their binding also affects the shape of the emergent temperature response. We demonstrate that with an increase in substrate availability, K shifts the optimal temperature, where reaction rates plateau, towards higher values. Further, we show that the chemical kinetics theory accurately represents 12 sets of published enzyme assay data and includes the popular mechanistic model by Ratkowsky et al. (2005) as a special case. Given its good performance and solid theoretical underpinning, we believe this new theory will facilitate the construction of more mechanistic-based environmental biogeochemical models.
Hydrogen is pivotal in the transition to sustainable energy systems, playing major roles in power generation and industrial applications. Metal–organic frameworks (MOFs) have emerged as promising mediums for efficient hydrogen storage. However, identifying potential candidates for deployment is challenging due to the vast number of currently available synthesized MOFs. This study integrates molecular simulations, machine learning, and techno-economic analysis to evaluate the performance of MOFs across broad operation conditions for hydrogen storage applications. While previous screenings of MOF databases have predominantly emphasized high hydrogen capacities under cryogenic conditions, this study reveals that optimal temperatures and pressures for cost minimization depend on the raw price of the MOF. Specifically, when MOFs are priced at $15/kg, among the 9720 MOFs tested, 9692 MOFs achieve the lowest cost at temperatures between 170 K and 250 K and a pressure of 150 bar. Under these optimal conditions, 362 MOFs deliver a lower levelized cost of storage than 350 bar compressed gas hydrogen storage. Furthermore, this study reveals key material properties that result in low system cost, such as high surface areas (>3000 m2/g), large void fractions (>0.78), and large pore volumes (>1.1 cm3/g).
Two of the main conditions for plant growth and development on the Martian surface are irradiation (optimal range from 80 W/sq m to 180 W/sq m of photosynthetically active radiation) and temperature (optimal range from 20 C to 27 C). The only known natural source of energy on Mars is sunlight, with a general intensity of 589 +/- 142 W/sq m (Martian Solar Constant). Comparisons of plant growth requirements with conditions on the Martian surface are presented in Table 1, while some basic considerations for implementing plant growth in a Martian DG are presented in Table 2. The general scenario and approximate schedule of startup and development of operations in DG are shown in Table 3.
This is code to reproduce and build on OOD detection from the paper "Out of Distribution Detection with Neural Network Anchoring". Our goal here is to exploit heteroscedastic temperature scaling as a calibration strategy for out of distribution (OOD) detection. Heteroscedasticity here refers to the fact that the optimal temperature parameter for each sample can be different, as opposed to conventional approaches that use the same value for the entire distribution. To enable this, we propose a new training strategy called anchoring that can estimate appropriate temperature values for each sample, leading to state-of-the-art OOD detection performance across several benchmarks. Using NTK theory, we show that this temperature function estimate is closely linked to the epistemic uncertainty of the classifier, which explains its behavior. In contrast to some of the best-performing OOD detection approaches, our method does not require exposure to additional outlier datasets, custom calibration objectives, or model ensembling. Through empirical studies with different OOD detection settings - far OOD, near OOD, and semantically coherent OOD - we establish a highly effective OOD detection approach.
Buildings make up a large portion of energy consumption in the U.S. today. Understanding their energy consumption patterns can improve their efficiency, but requires detailed models that rely on incomplete or unknown information. Previous work has shown that artificial intelligence (AI) can be used to predict missing information and even suggest upgrades to improve building efficiency. However, building upgrades may require undesirable upfront costs. Oppositely, advanced control could improve building efficiency with negligible upfront cost. To explore the tradeoffs between these two approaches, in this work we propose a workflow to compute optimal temperature setpoint schedules to minimize energy consumption and operational cost. Results show that modifying the temperature setpoints in a building using model predictive control (MPC) can effectively reduce its energy consumption and operational cost. This optimal operation cannot fully meet a desired goal. However, we show that by considering MPC in addition to component upgrades, a desired goal can be met with significantly less upfront costs.
Spatially detailed satellite data of mean color, sea ice concentration, surface temperature, clouds, and wind have been analyzed to quantify and study the large scale regional and temporal variability of phytoplankton blooms in the Arctic and peripheral seas from 1998 to 2002. In the Arctic basin, phytoplankton chlorophyll displays a large symmetry with the Eastern Arctic having about fivefold higher concentrations than those of the Western Arctic. Large monthly and yearly variability is also observed in the peripheral seas with the largest blooms occurring in the Bering Sea, Sea of Okhotsk, and the Barents Sea during spring. There is large interannual and seasonal variability in biomass with average chlorophyll concentrations in 2002 and 2001 being higher than earlier years in spring and summer. The seasonality in the latitudinal distribution of blooms is also very different such that the North Atlantic is usually most expansive in spring while the North Pacific is more extensive in autumn. Environmental factors that influence phytoplankton growth were examined, and results show relatively high negative correlation with sea ice retreat and strong positive correlation with temperature in early spring. Plankton growth, as indicated by biomass accumulation, in the Arctic and subarctic increases up to a threshold surface temperature of about 276-277 degree K (3-4 degree C) beyond which the concentrations start to decrease suggesting an optimal temperature or nutrient depletion. The correlation with clouds is significant in some areas but negligible in other areas, while the correlations with wind speed and its components are generally weak. The effects of clouds and winds are less predictable with weekly climatologies because of unknown effects of averaging variable and intermittent physical forcing (e.g. over storm event scales with mixing and upwelling of nutrients) and the time scales of acclimation by the phytoplankton.
Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT ) genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC 50 (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.
Optimization for selection of optical coating patterns of external surfaces of spacecraft for temperature control