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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗
NASA NTRS1993

Exercise countermeasures for bed-rest deconditioning

The purpose for this 30-day bed rest study was to investigate the effects of short-term, high intensity isotonic and isokinetic exercise training on maintenance of working capacity (peak oxygen uptake), muscular strength and endurance, and on orthostatic tolerance, posture and gait. Other data were collected on muscle atrophy, bone mineralization and density, endocrine analyses concerning vasoactivity and fluid-electrolyte balance, muscle intermediary metabolism, and on performance and mood of the subjects. It was concluded that: The subjects maintained a relatively stable mood, high morale, and high esprit de corps throughout the study. Performance improved in nearly all tests in almost all the subjects. Isotonic training, as opposed to isokinetic exercise training, was associated more with decreasing levels of psychological tension, concentration, and motivation; and improvement in the quality of sleep. Working capacity (peak oxygen uptake) was maintained during bed rest with isotonic exercise training; it was not maintained with isokinetic or no exercise training. In general, there was no significant decrease in strength or endurance of arm or leg muscles during bed rest, in spite of some reduction in muscle size (atrophy) of some leg muscles. There was no effect of isotonic exercise training on orthostasis, since tilt-table tolerance was reduced similarly in all three groups following bed rest. Bed rest resulted in significant decreases of postural stability and self-selected step length, stride length, and walking velocity, which were not influenced by either exercise training regimen. Most pre-bed rest responses were restored by the fourth day of recovery.

Greenleaf, John↗
DOE OSTI2025

Power Quality and Load Capacity Evaluations of an Electric Vehicle for Multi-Robot System Applications

This paper evaluates the capability of a fully electric pickup truck, using the Ford F-150 Lightning as an example, to provide power to the circuit of a multi-robot system. The case study was conducted on a simulated INL Autonomous Pit Exploration System (APES) designed for the inspection of nuclear waste tank pits. Through a series of controlled tests, the vehicle’s power delivery consistency, load-handling capability, and battery performance were assessed under various conditions. First of all, the load test demonstrated that the vehicle provided stable power with low distortion and no unexpected interruptions. Second, during the operational limit test, the 240V system sustained loads up to 7.4 kW before tripping, providing insights into its operational limits. Last but not least, during a simulated full-scale APES operation, the vehicle’s battery depleted by only 6% over an hour, indicating sufficient capacity for extended use while retaining reserve power for transportation needs. This study highlights the potential of electric vehicles as reliable power sources for field operations, contributing to the advancement of sustainable technologies by reducing reliance on traditional fossil fuel generators and promoting the integration of clean energy solutions in remote and challenging environments.

Electric vehicle↗
DOE OSTI2025

Laser ablation of high-loading Li-ion battery electrodes improves accessible capacity and cycle life for Behind-the-Meter Storage

Adoption of Behind-the-Meter Storage (BTMS) requires design of batteries that enable high safety, long cycle life, and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) with LiMn 2 O 4 (LMO) achieves targets related to safety and cycle life, but these materials' low energy densities contribute to higher cost at the system scale. Increasing electrode loading is a simple approach to improve energy density, but comes with a trade-off in electrode utilization due to long, tortuous Li + diffusion pathways. Here, laser ablation is used to microstructure (pattern) high-loading electrodes to enhance electrode performance through improved Li + diffusion pathways. Four cell types, comprising combinations of standard or patterned anode and cathode, were prepared to evaluate the effects of laser ablation at each electrode. A rate test shows that patterning electrodes enhances active material utilization at ≳1C rates. Patterning the cathode yields the most benefit, as cells with a patterned cathode demonstrate a ~20% higher accessible capacity than those without at 1.4C. Additionally, 1C capacity retention of cells with patterned cathode (91% through 3000 cycles) is significantly improved over cells with only the anode patterned (64%) and non-patterned electrodes (50%). Characterization of post-mortem cells before and after refreshing their electrolyte suggests that 1C capacity retention is improved by mitigation of electrode "dry-out". We hypothesize that the microstructure acts as a reservoir of additional electrolyte, or a path for gas to escape, so that active material remains wetted throughout long-term cycling, and/or the microstructure may reduce localized, gas-forming overpotentials in the high-loading electrode.

25 ENERGY STORAGE↗
DOE OSTI2022

Influence of Metal Identity on Light-Induced Switchable Adsorption in Azobenzene-Based Metal–Organic Frameworks

Energy-efficient capture and release of small gas molecules, particularly carbon dioxide (CO 2 ) and methane (CH 4 ), are of significant interest in academia and industry. Porous materials such as metal–organic frameworks (MOFs) have been extensively studied, as their ultrahigh porosities and tunability enable significant amounts of gas to be adsorbed while also allowing specific applications to be targeted. However, because of the microporous nature of MOFs, the gas adsorption performance is dominated by high uptake capacity at low pressures, limiting their application. Hence, methods involving stimuli-responsive materials, particularly light-induced switchable adsorption (LISA), offer a unique alternative to thermal methods. Here, we report the mechanism of a well-known LISA system, the azobenzene-based material PCN-250, for CO 2 and CH 4 adsorption. There is a noticeable difference in the LISA effect dependent on the metal cluster involved, with the most significant being PCN-250-Al, where the adsorption can change by 83.1% CH 4 and 56.1% CO 2 at 298 K and 1 bar and inducing volumetric storage changes of 36.2 and 33.9 cm 3 /cm 3 at 298 K between 5 and 85 bar (CH 4 ) and 2 and 9 bar (CO 2 ), respectively. Using UV light in both single-crystal X-ray diffraction and gas adsorption testing, we show that upon photoirradiation, the framework undergoes a “localized heating” phenomenon comparable to an increase of 130 K for PCN-250-Fe and improves the working capacity. Furthermore, this process functions because of the constrained nature of the ligand, preventing the typical trans-to-cis isomerization observed in free azobenzene. In addition, we observed that the degree of localized heating is highly dependent on the metal cluster involved, with the series of isostructural PCN-250 systems showing variable performance based upon the degree of interaction between the ligand and the metal center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Prediction of Weather Impacted Airport Capacity using Ensemble Learning

Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.

Weather impact↗
DOE OSTI2024

Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System Under Deep Climate Uncertainty

Climate change threatens the resource adequacy of future power systems. Existing research and practice lack frameworks for identifying decarbonization pathways that are robust to climate-related uncertainty. We create such an analytical framework, then use it to assess the robustness of alternative pathways to achieving 60% emissions reductions from 2022 levels by 2040 for the Western U.S. power system. Our framework integrates power system planning and resource adequacy models with 100 climate realizations from a large climate ensemble. Climate realizations drive electricity demand; thermal plant availability; and wind, solar, and hydropower generation. Among five initial decarbonization pathways, all exhibit modest to significant resource adequacy failures under climate realizations in 2040, but certain pathways experience significantly less resource adequacy failures at little additional cost relative to other pathways. By identifying and planning for an extreme climate realization that drives the largest resource adequacy failures across our pathways, we produce a new decarbonization pathway that has no resource adequacy failures under any climate realizations. This new pathway is roughly 5% more expensive than other pathways due to greater capacity investment, and shifts investment from wind to solar and natural gas generators. Our analysis suggests modest increases in investment costs can add significant robustness against climate change in decarbonizing power systems. Our framework can help power system planners adapt to climate change by stress testing future plans to potential climate realizations, and offers a unique bridge between energy system and climate modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2012

Analog Design for Digital Deployment of a Serious Leadership Game

This paper presents the design, development, and user testing of a leadership development simulation. The authors share lessons learned from using a design process for a board game to allow for quick and inexpensive revision cycles during the development of a serious leadership development game. The goal of this leadership simulation is to accelerate the development of leadership capacity in high-potential mid-level managers (GS-15 level) in a federal government agency. Simulation design included a mixed-method needs analysis, using both quantitative and qualitative approaches to determine organizational leadership needs. Eight design iterations were conducted, including three user testing phases. Three re-design iterations followed initial development, enabling game testing as part of comprehensive instructional events. Subsequent design, development and testing processes targeted digital application to a computer- and tablet-based environment. Recommendations include pros and cons of development and learner testing of an initial analog simulation prior to full digital simulation development.

Maxwell, Nicholas↗
NASA NTRS1994

Design and testing of a model CELSS chamber robot

A robot system for use in an enclosed environment was designed and tested. The conceptual design will be used to assist in research performed by the Controlled Ecological Life Support System (CELSS) project. Design specifications include maximum load capacity, operation at specified environmental conditions, low maintenance, and safety. The robot system must not be hazardous to the sealed environment, and be capable of stowing and deploying within a minimum area of the CELSS chamber facility. This design consists of a telescoping robot arm that slides vertically on a shaft positioned in the center of the CELSS chamber. The telescoping robot arm consists of a series of links which can be fully extended to a length equal to the radius of the working envelope of the CELSS chamber. The vertical motion of the robot arm is achieved through the use of a combination ball screw/ball spline actuator system. The robot arm rotates cylindrically about the vertical axis through use of a turntable bearing attached to a central mounting structure fitted to the actuator shaft. The shaft is installed in an overhead rail system allowing the entire structure to be stowed and deployed within the CELSS chamber. The overhead rail system is located above the chamber's upper lamps and extends to the center of the CELSS chamber. The mounting interface of the actuator shaft and rail system allows the entire actuator shaft to be detached and removed from the CELSS chamber. When the actuator shaft is deployed, it is held fixed at the bottom of the chamber by placing a square knob on the bottom of the shaft into a recessed square fitting in the bottom of the chamber floor. A support boot ensures the rigidity of the shaft. Three student teams combined into one group designed a model of the CELSS chamber robot that they could build. They investigated materials, availability, and strength in their design. After the model arm and stand were built, the class performed pre-tests on the entire system. A stability pre-test was used to determine whether the model robot arm would tip over on the stand when it was fully extended. Results showed the stand tipped when 50 Newtons were applied horizontally to the top of the vertical shaft while the arm was fully extended. This proved that it was stable. Another pre-test was the actuator slip test used to determine if there is an adequate coefficient of friction between the actuator drive wheels and drive cable to enable the actuator to fully extend and retract the arm. This pre-test revealed that the coefficient of friction was not large enough to prevent slippage. Sandpaper was glued to the drive wheel and this eliminated the slippage problem. The class preformed a fit test in the CELSS chamber to ensure that the completed robot arm is capable of reaching the entire working envelope. The robot was centered in the chamber and the arm was fully extended to the sides of the chamber. The arm was also able to retract to clear the drain pipes separating the upper and lower plant trays.

Davis, Mark↗
DOE OSTI2025

Interface-engineered (AlMnCoNiZn) 3 O 4 @PPy nanocomposites for superior lithium storage: Mechanism and performance

The practical application of graphite anodes in lithium-ion batteries (LIBs) is constrained by low specific capacity (372 mAh g -1 ) and sluggish kinetics. Here, to address these limitations, our present study focuses on high-entropy oxides (HEOs), which offer high theoretical capacity and structural stability. We synthesized spinel-structured (AlMnCoNiZn) 3 O 4 nanoparticles via a solution combustion method and fabricated an (AlMnCoNiZn) 3 O 4 @polypyrrole (PPy) nanocomposite through in-situ polymerization. Our electrochemical tests demonstrate that the PPy modification significantly enhances performance. While the pristine (AlMnCoNiZn) 3 O 4 delivered 445 mAh g −1 after 100 cycles at 100 mA g −1 and 350 mAh g −1 after 1000 cycles at 1000 mA g −1 , the (AlMnCoNiZn) 3 O 4 @PPy composite achieved 695 mAh g −1 after 100 cycles and maintained 675 mAh g −1 after 1000 cycles. Furthermore, the composite improved rate capacity at 1000 mA g −1 from 211 mAh g −1 to 403 mAh g −1 . This work highlights how conductive and flexible polymer modifications can dramatically improve the electrochemical properties of HEOs. The developed (AlMnCoNiZn) 3 O 4 @PPy composite provides a promising direction for designing advanced anodes to meet next-generation energy storage demands.

Anodes material↗
DOE OSTI2025

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗
NASA NTRS2023

An Accelerated Life Testing Dataset for Lithium-Ion Batteries With Constant and Variable Loading Conditions

The dataset repository is organized into three main folders, each containing one group of life cycled battery packs. Within each folder individual battery packs own their dedicated csv file for continuous data logging, which are named with their respective battery pack number. The folders are named: - regular_alt_batteries: Containing one csv file for each battery pack cycled at the same load level or load range throughout lifetime - recommissioned_batteries: Containing one csv file for each battery pack cycled at different load levels at varying life stages - second_life_batteries: Containing one csv file for each second life battery pack cycled at constant current througout the second life

Li-ion Battery↗
DOE OSTI2022

A Fiber-Based 3D Lithium Host for Lean Electrolyte Lithium Metal Batteries

3D hosts are promising to extend the cycle life of lithium metal anodes but have rarely been implemented with lean electrolytes thus impacting the practical cell energy density. To overcome this challenge, a 3D host that is lightweight and easy to fabricate with optimum pore size that enables full utilization of its pore volume, essential for lean electrolyte operations, is reported. The host is fabricated by casting a VGCF (vapor-grown carbon fiber)-based slurry loaded with a sparingly soluble rubidium nitrate salt as an additive. The network of fibers generates uniform pores of ≈3 µm in diameter with a porosity of 80%, while the nitrate additive enhances lithiophilicity. This 3D host delivers an average coulombic efficiency of 99.36% at 1 mA cm -2 and 1 mAh cm -2 for over 860 cycles in half-cell tests. Full cells containing an anode with 1.35-fold excess lithium paired with LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes exhibit capacity retention of 80% over 176 cycles at C/2 under a lean electrolyte condition of 3 g Ah -1 . This work provides a facile and scalable method to advance 3D lithium hosts closer to practical lithium-metal batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impact of storage and blending of algae and forest product residue on fuel blendstock production

Seasonal impacts on the production of algae biomass require blending with other feedstocks such as wood to maintain consistent annual conversion capacity. Idaho National Laboratory (INL) has developed a long-term storage strategy for algae biomass using ensiling, or anaerobic wet storage, that was tested for blends of algae and wood to stabilize the feedstock supply for processing to fuels. Additionally, blending biomass (algae and wood) leverages existing biomass storage approaches commonly used by the feed and forage industry. Earlier research also has demonstrated positive results that indicate ensiling is more effective and economical in normalizing biomass feedstock supply prior to conversions such as HTL (hydrothermal liquefaction) than preserving biomass by drying. By assessing impacts beginning with upstream logistic operations and proceeding through each conversion step, this work focuses on conversion of ensiled and blended biomass to fungible liquid transportation fuel blendstocks. This is accomplished by conversion of the blended biomass (62% Chlorella sp. blended with 38% loblolly pine forest product residues [FPR]) to bio-crude through HTL and subsequent upgrading through HT (hydrotreating) with a commercial refinery catalyst analogous to a refinery process to produce hydrocarbon fuel. In this work, results indicate that carbon retention and quality are preserved in both the bio-crude and upgraded fuel from the ensiled blend, indicating the potential of this approach for managing seasonal variations in algae biomass productivity.

09 BIOMASS FUELS↗
DOE OSTI2023

Metal hydride composition-derived parameters as machine learning features for material design and H 2 storage

Though hydrogen is a promising energy carrier for a green future, many challenges persist. One is the difficulty in engineering storage solutions, with metal hydrides being a leading contender among solid-state strategies. To facilitate efficient searching of candidate materials, ridge regression, simple decision trees, random forest ensembles, and gradient boosting ensembles were employed to predict the energy of formation, with the random forest ensemble resulting in the lowest test set error. First, two public databases, Materials Project and HydPark, were searched for metal hydrides. Feature engineering was performed before the models were developed, resulting in electronegativity, density, atomic density, d-character, f-character, band gap, hydrogen weight fraction, magnetization, temperature, and pressure being retained. The models were then benchmarked by the lowest test error before a random forest ensemble was used to populate entries missing energy of formation. Furthermore, all were then scored by hydrogen storage capacity and energy of formation suitability. Readily available features including several derived from only the chemical formula which were found to be highly predictive. and so are promising for high-throughput screening of arbitrary novel hydride formulations and blends for thermodynamic feasibility.

25 ENERGY STORAGE↗
DOE OSTI2025

Evaluation of a high-throughput method for processing sponge-stick samples to detect viable, non-spore-forming biothreat agents

After a bioterrorism incident, surface sampling is often used to determine the extent of contamination and exposure, guiding decontamination efforts and decisions for re-occupancy of affected sites. The sponge-stick (SS) is a preferred and commonly used device for sample collection to detect both spore-forming and non-spore-forming biothreat agents from non-porous surfaces. Here, in this study, a recently developed high-throughput method (HTM) for processing SS samples to detect viable Bacillus anthracis spores was adapted for detection of non-spore-forming biothreat agents, Yersinia pestis and Francisella tularensis. The scalable HTM was used to process up to 20 SS samples simultaneously, compared to the current stomacher-based method which processes one SS at a time. Comparisons of the HTM and the stomacher-based method were statistically indistinguishable for most experiments (P > 0.05) with HTM recoveries of 37–60 % for Y. pestis inoculated at 102–103 cells/SS and held 48 h at 4 °C to mimic sample transport/storage. The HTM was integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis to detect viable Y. pestis in the presence of particulate contamination (Arizona Test Dust, ATD). This approach detected Y. pestis inoculated at 20 cells/SS and ATD did not impact detection (P > 0.05). F. tularensis showed significantly lower recoveries between no-hold time and 48-h hold time (4 °C, P < 0.05) using the HTM, which further testing showed could be due to toxicity of the neutralizing buffer used for SS pre-wetting. With modifications, this method could enhance throughput capacity while maintaining similar recovery efficiencies to current methods for other non-spore-forming bacterial pathogens.

Biological and medical sciences↗
DOE OSTI2020

Adhesive Polymers as Efficient Binders for High-Capacity Silicon Electrodes

The major cause for capacity fading of silicon nanoparticle (SiNP)-based electrodes is the immense pressure applied toward the conductive networks during the charge/discharge process. While numerous efforts have been devoted to investigating different types of polymer binders, the rational design of an adhesive binder with pressure sensitivity has rarely been reported. Herein, a series of pressure-sensitive adhesives (PSAs) synthesized via copolymerization of 2-ethylhexyl acrylate (2-EHA) and acrylic acid (AA) are evaluated as polymer binders for SiNP-based electrodes. The balance between the density of interaction groups and viscoelastic properties is systematically investigated for efficient binding performance. The SiNP-based electrode using PSA with 20 mol % of 2-EHA (Si-PSA-20%) exhibits excellent electrochemical performance, achieving a capacity retention of 83% at the 100th cycle compared with 54% for Si-PAA after activation. Si-PSA-20% also delivers a superior cycling performance at a high current density (1731 mAh g –1 after 350 cycles vs 719 mAh g –1 after 150 cycles for Si-PAA, 1.8 A g –1 ) and at high mass loading of active materials (capacity retention of 74 vs 38% for Si-PAA after 100 cycles, SiNP content ~1.2 mg cm –2 ). Atomic force microscopy (AFM), peel tests, and Car–Parrinello molecular dynamics (CPMD) simulations are employed to understand their binder performance. The novel design and systematical investigation of PSAs as binders will definitely be appealing for not only the Si electrode but also for other high-energy-density electrode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spin State Modulation via Magnetic Fields in Fe Single Atom Catalysts for High-Performance Aqueous Zinc–Sulfur Batteries

Aqueous zinc–sulfur battery has garnered significant attention as a high-energy, low-cost, and safe energy storage system. However, the multielectron transfer kinetics of sulfur cathodes are relatively slow, presenting challenges such as limited sulfur utilization and lower discharge voltage, which significantly hinder their practical applications. Here, in this study, we explored a comprehensive design approach for high-performance, long-cycle aqueous zinc–sulfur batteries. The simultaneous introduction of ZnI 2 and Fe single atoms (Fe-SAs) as catalytically active agents decouples the redox reactions, effectively facilitating ZnS oxidation and S reduction separately. The application of an external magnetic field regulates the spin state of Fe-SAs, further enhancing their catalytic activity and electron transfer capability. Electrochemical tests demonstrate that the S@Fe-NC HS/ZnI 2 cathode assembled under a magnetic field exhibits excellent rate performance, achieving an impressive specific capacity of 1399 mAh g –1 at a high current density of 5 A g –1 and good cycling stability over 300 cycles, representing the highest reported high-current discharge capacity to date. This study provides a comprehensive design framework for optimizing zinc–sulfur (Zn–S) battery performance and elucidates the influence of magnetic field-induced spin state modulation on catalytic behavior.

36 MATERIALS SCIENCE↗