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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Framework for assessment of magnetic equilibrium controller performance on the MAST upgrade spherical tokamak

Here, in this work we present the assessment framework for magnetic equilibrium controllers on MAST Upgrade spherical tokamak (MAST-U) spherical tokamak. Such controllers are essential for the MAST-U since exhaust physics and core-edge integration studies require advanced divertor plasma configurations. The developed framework is based on the TokSys suite of plasma control codes, which was adapted and upgraded for MAST-U. However, extra capabilities were added on top of TokSys to support the development of new control algorithms, deployment of controllers to the plasma control system (PCS) and evaluation of their performance. The controller assessment was realized via closed-loop integrated control simulations with the actual MAST-U PCS and different physics-based plasma models. Since all components of the assessment chain were experimentally validated, these simulations provide qualified controllers applicable for direct use in the experiment. This resulted in the successful experimental demonstration of advanced plasma shape control on MAST-U with minimal on-machine development time. A similar methodology would be beneficial to other tokamaks, both existing and future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Rewiring the unfolded protein response for plant growth recovery after stress

The unfolded protein response (UPR) is a highly coordinated signaling network that alleviates endoplasmic reticulum (ER) stress, a condition induced by diverse environmental challenges in plants. Over the past two decades, substantial progress has been made in elucidating the genetic and molecular mechanisms of ER stress sensing and signal transduction in plants, largely through studies in the model plant Arabidopsis thaliana . These advances have established the UPR as a central regulator of proteostasis and underscored its broader relevance to plant growth and development and crop productivity under stress conditions. Despite this progress, critical knowledge gaps remain, particularly concerning the downstream biological processes required for growth recovery once ER stress has subsided and how these processes are coordinated by UPR regulators. Recent systems-level and integrative studies have begun to reveal critical roles of UPR signaling in pathways governing growth re-establishment and homeostasis of nutrient allocation and energy metabolism. In this review, we highlight recent findings on the functional roles of the plant UPR in recovery from ER stress, with a focus on mechanisms mediated by UPR regulators and downstream biological pathways that enable the transition from stress mitigation to growth restoration. Although this research area is still emerging, accumulating evidence supports a model in which the UPR functions as a dynamic regulatory network that actively coordinates post-stress physiological recovery to support plant fitness.

ER stress↗
DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗
DOE OSTI2024

Large-scale Multiphysics Simulations of Small Modular Reactors Operating in Natural Circulation

Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. In conclusion, the results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.

ECP↗
DOE OSTI2026

Thermophysical Properties of Liquid Tritium: A Path Integral Monte Carlo Study

Here, we present worm-algorithm, path integral Monte Carlo simulations of bulk liquid tritium. The simulations are benchmarked against empirically known thermophysical properties of liquid deuterium and liquid tritium. Results for the pair correlation function, chemical potential, isothermal compressibility, isochoric heat capacity, and single-particle momentum distributions are reported. Given the benchmark comparisons, our predictions of liquid tritium properties are expected to be accurate to within a few percent. Our simulations unambiguously demonstrate the significance of nuclear quantum effects to the properties of liquid tritium. In particular, under saturated vapor pressure, the average molecular kinetic energy of the liquid is found to be more than 60% higher than the value expected from the classical equipartition theorem.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Platinum Surface Water Orientation Dictates Hydrogen Evolution Reaction Kinetics in Alkaline Media

The fundamental understanding of sluggish hydrogen evolution reaction (HER) kinetics on a platinum (Pt) surface in alkaline media is a topic of considerable debate. Herein, we combine cyclic voltammetry (CV) and electrical transport spectroscopy (ETS) approaches to probe the Pt surface at different pH values and develop molecular-level insights into the pH-dependent HER kinetics in alkaline media. The change in HER Tafel slope from ~110 mV/decade in pH 7–10 to ~53 mV/decade in pH 11–13 suggests considerably enhanced kinetics at higher pH. The ETS studies reveal a similar pH-dependent switch in the ETS conductance signal at around pH 10, suggesting a notable change of surface adsorbates. Fixed-potential calculations and chemical bonding analysis suggest that this switch is attributed to a change in interfacial water orientation, shifting from primarily an O-down configuration below pH 10 to a H-down configuration above pH 10. This reorientation weakens the O–H bond in the interfacial water molecules and modifies the reaction pathway, leading to considerably accelerated HER kinetics at higher pH. Finally, our integrated studies provide an unprecedented molecular-level understanding of the nontrivial pH-dependent HER kinetics in alkaline media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Carbon Capture from ArcelorMittal Hot Briquetted Iron Plant Using Air Liquide Cryocap™ FG Technology – FEED Study

The process of steel production is energy and carbon intensive with global average energy consumption of 5.5 MWh/tonne of steel and CO2 emission intensity of 1.83 tonne CO2/tonne of steel. The steel making process has inherent CO2 emissions from mineral conversion and is considered major contributors to the global carbon emissions. The steel industry is responsible for 8% of global carbon emissions. The main objective of this research project is to execute and complete a front-end engineering and design (FEED) study for a commercial-scale, carbon capture project that separates 95% of the total CO2 emissions at the ArcelorMittal’s Hot Briquetted Iron (HBI) plant in Portland, TX (Figure 1). The HBI is an ore-based metallic that is used as high-grade feedstock for high-quality steel via an Electric Arc Furnace (EAF) route. The HBI plant produces 2.0 million metric tonnes of high-quality HBI and emits approximately 1 million tonnes CO2/yr. The capture system is a Pressure Swing Adsorption (PSA) system assisted Cryocap™ FG technology (Figure 2). The captured CO2 will be pipeline grade and will be geologically stored in a facility within 10 miles of the CO2 source. The Host Site location in Corpus Christi, TX, is near hydrocarbon processing facilities and near Environmental Justice (EJ) and Qualified Opportunity Zone (QOZ) communities. Due to the location of the Host Site, the retrofit project offers the ability to demonstrate how a workforce focused on the fossil energy sector can be redirected to the clean- energy sector. The Air Liquide Cryocap™ capture technology is a proven technology and has been extensively examined for large industrial applications. It has been shown to be applicable to a variety of industrial applications including the steel industry. Cryocap™ FG (specific setup for Flue Gas application) consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The scope of this study incorporates completing FEED study of the CO2 capture system which includes point-source CO2 capture and balance-of-plant; Business Case Analysis (BCA) outlining the current and projected volumes of the steel plant’s point sources of CO2 and the potential utilization of tax credits, including its projected revenue and duration; Life Cycle Analysis (LCA); Environmental Justice Analysis; Economic Revitalization and Job Creation Outcomes Analysis; and Workforce Readiness Plan. The plant design work was divided into two components: Inside Battery Limits (ISBL) and Outside Battery Limits (OSBL). The ISBL focuses on the capture system, while the OSBL focuses on the utility feeds and ducting from the plant to the capture system. Various design and engineering deliverables will be developed to define commodity quantities, equipment specifications, and labour effort required to execute the project. These FEED study deliverables will be prepared with the intent to develop an overall project capital cost estimate consistent with an AACE Class 3 estimate. The modular approach for the Cryocap™ FG that is being designed for this study integrates compression, PSA, and cryogenic “bricks” to achieve the desired CO2 capture rates. This carbon capture system integrates easily with the existing plant, thus reducing project costs and risks. It is also capable of managing impurities such as nitrogen oxides (NOx), sulfur oxides (SOx), mercury, hydrocarbons, and particulate matter. The capture system has a smaller footprint than amine-based systems. The two-step process uses PSA to preconcentrate the CO2 in the feedstream and then uses the cryogenic portion to purify and compress the resulting high purity CO2 product. This combination of purification and compression (i.e., process intensification) significantly reduces the CAPEX associated with use of a separate compressor commonly utilized for amine solvent-based systems. Successful completion of the FEED study will provide DOE with a detailed understanding of the costs for scaling up this proven capture technology for commercial applications at industrial facilities.

42 ENGINEERING↗
DOE OSTI2025

SICAS, a new integrated divertor-SOL-pedestal-core framework for self-consistent modeling of ion and impurity transport in fusion devices

We present a new framework for core-edge integration studies named SICAS (SOLPS-ITER coupled to ASTRA-STRAHL) which enables high fidelity simulations of the core, edge, and divertor regions encompassing the transport of ions as well as the impurities through the entire plasma domain. SICAS handles the exchanging of the particle and power fluxes as well as transport coefficients to ensure consistency through the codes. An overlapping region is defined from the inside of the separatrix of the plasma to the SOLPS-ITER core boundary allowing for matching profiles and fluxes between the two codes for a self-consistent approach. The results presented here demonstrated the flexibility of SICAS to simulate different configurations, scenarios, divertor geometries, and plasma species with good agreement with DIII-D experimental data. This tool opens new possibilities in integrated modeling of fusion devices integrating all relevant phenomena in the core and the divertor plasmas. These capabilities are required for the interpretation of current experiments as well as the design of new devices.

core-edge integration↗
DOE OSTI2024

OSW Consortium 2 - Validated National Offshore Wind Resource Dataset with Uncertainty Quantification (CRADA Report)

This research has led to the development of the 2023 National Offshore Wind data set (NOW-23), which offers the latest wind resource information for offshore regions in the United States. NOW-23 supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published a decade ago and is currently a primary resource for wind resource assessments and grid integration studies in the contiguous United States. By incorporating advancements in the Weather Research and Forecasting (WRF) model, NOW-23 delivers an updated and cutting-edge product to stakeholders. As part of this project, we also developed a summary of the uncertainty quantification in NOW-23, along with NOW-WAKES, a 1-year post-construction data set that quantifies expected offshore wake effects in the US Mid-Atlantic lease areas. Stakeholders can access the NOW-23 data set at https://doi.org/10.25984/1821404.

17 WIND ENERGY↗
DOE OSTI2026

Personal and environmental predictors of polycyclic aromatic hydrocarbon exposure identified through repeated silicone wristband sampling

This study integrates quantitative data on personal exposure to polycyclic aromatic hydrocarbons (PAHs) in 162 silicone wristbands with demographics, behavioral information, and housing characteristics to explore contributions to residential exposure in a superfund-adjacent community over the course of a year. Forty-six residents completed questionnaires and wore silicone wristbands as personal passive samplers for seven consecutive days on up to four separate occasions in alternating months between November 2022 and June 2023. It was hypothesized that individual behaviors and housing characteristics are sources of dependence and correlation between personal PAH exposures. 50 PAHs were detected at least once, 17 of which were alkylated PAHs. Exposure to PAHs of similar molecular weight was often correlated, notably between naphthalenes (2-rings) and higher molecular weight PAHs (3 or more rings). Generalized linear mixed models identified flooring type, participant age, and sampling month as important predictors of increased PAH exposure, and flooring type, and use of wood stoves or heavy machinery as predictors of increased naphthalene exposure relative to higher molecular weight PAHs. Individual chemical models based on concentration data and detection frequencies corroborated these findings across multiple PAHs. We demonstrate that personal exposure is not static and the degree of variability in personal exposure is individual. Hence, identification of influential exposure factors through repeated measures of chemical exposure and characterization of variability in personal exposure as performed in this study, is important in the development of exposure mitigation strategies.

Bonner, Emily↗
DOE OSTI2024

The 2023 National Offshore Wind data set (NOW-23)

Abstract. This article introduces the 2023 National Offshore Wind data set (NOW-23), which offers the latest wind resource information for offshore regions in the United States. NOW-23 supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published a decade ago and is currently a primary resource for wind resource assessments and grid integration studies in the contiguous United States. By incorporating advancements in the Weather Research and Forecasting (WRF) model, NOW-23 delivers an updated and cutting-edge product to stakeholders. In this article, we present the new data set which underwent regional tuning and performance validation against available observations and has data available from 2000 through, depending on the region, 2019–2022. We also provide a summary of the uncertainty quantification in NOW-23, along with NOW-WAKES, a 1-year post-construction data set that quantifies expected offshore wake effects in the US Mid-Atlantic lease areas. Stakeholders can access the NOW-23 data set at https://doi.org/10.25984/1821404 (Bodini et al., 2020).

17 WIND ENERGY↗
DOE OSTI2025

Sustainable aviation fuel from ethanol: Techno-economic analysis and life cycle analysis

Sustainable aviation fuel (SAF) is crucial for improving energy security, enhancing domestic production, and reducing carbon emissions in the aviation sector. Among various SAF production technologies, the ethanol-to-jet (ETJ) pathway is a promising option due to its economic viability and technological maturity. This study integrates a techno-economic analysis (TEA) and a life cycle analysis (LCA) to evaluate emissions reduction strategies for SAF production via the ETJ pathway, considering use of ethanol derived from both corn grain and corn stover. Conventional corn grain-derived ETJ fuel reduces greenhouse gas (GHG) emissions by 22 % compared to fossil jet fuel, with potential reductions of 26 %–96 % when incorporating renewable energy sources, with a 6 %–32 % increase in the minimum fuel selling price (MFSP). Corn stover-derived ETJ achieves a 77 % GHG reduction but with higher MFSPs compared to corn grain ETJ. Carbon capture and storage (CCS without considering the cost for piping and sequestration, only compression) reduces the emissions of corn grain-derived ETJ by up to 32 gCO 2 e/MJ and enables negative emissions for corn stover-derived ETJ, with MFSP increases ranging from 1 % to 22 %. While carbon capture and utilization (CCU) increase ethanol yield by 47 %, it raises MFSPs by 54 % due to high electricity demand. Sustainable farming practices provide only limited carbon intensity (CI) reductions individually but do offer cumulative benefits when combined. These findings highlight the trade-offs between cost and environmental impact, providing insights to optimize SAF production strategies and support aviation sector goals for emissions reduction.

09 BIOMASS FUELS↗
DOE OSTI2022

Accelerating Catalyst Development for Biofuel Production through Multiscale Catalytic Fast Pyrolysis of Biomass over Mo2C

Advanced catalytic materials play an enabling role in producing renewable fuels and chemicals from biomass, thereby helping meet the global climate-change goals set forth by the Intergovernmental Panel on Climate Change. Herein, we present a multiscale approach to accelerate the catalyst-process development cycle for catalytic fast pyrolysis (CFP) of biomass over Mo2C. Mo2C has been shown to possess co-localized acidic and metallic sites and exhibit high activity for deoxygenation of biomass pyrolysis model compounds. However, critical knowledge gaps remain regarding the effectiveness of this catalyst for CFP of whole biomass. We address these knowledge gaps and demonstrate that Mo2C is effective at deoxygenating biomass-pyrolysis products in the presence of H2 but that it undergoes rapid selective and non-selective deactivation. The knowledge gaps addressed from this integrated study, targeting appropriate experiments across scales and feed types, enabled identification of critical modifications for advancing the CFP catalyst-process development cycle.

biofuels↗
DOE OSTI2025

Evidence for metal sources, fluid-mixing processes, and S isotope recycling within the feeder zone of an Irish type Zn-Pb deposit

The origin and evolution of fluids in Irish-type Zn-Pb deposits remains debated, particularly regarding the mobility of metals such as Cu and Ni, sources of sulphur, and the role of fluid mixing and replacement. The Lisheen Zn-Pb deposit, Ireland, offers a well-defined natural laboratory to investigate these questions. While most studies have focused on the Waulsortian Limestone Formation, the primary sulphide host, less is known about mineralisation in underlying units, such as the Lisduff Oolite Member (LOM). The LOM displays enrichment in Cu and Ni and displays intense replacement textures compared to other hosts at Lisheen, making it an ideal target for studying metal mobility and sulphur recycling in carbonate-hosted systems. Through characterising and studying LOM-hosted sulphides, valuable insights into mineralisation processes, especially related to Cu-Ni metals, can be defined. This study integrates petrography, EMPA, and in situ sulphur isotope (δ 34 S) analysis to investigate sulphide paragenesis, mineral chemistry, and fluid evolution across LOM ore zones. Results reveal a multistage mineralising system involving extensive replacement of early pyrite (Py0, δ 34 S = −28.4 to −21.9 ‰) by sphalerite and galena, with zoned pyrite (Py1) enriched in As-Cu-Ni-Tl. The δ 34 S values and trace element trends indicate mixing between hydrothermal and bacteriogenic sulphur-rich fluids, with evidence for sulphur recycling during replacement. Pyrite textures and compositions capture this evolving fluid regime, with trace element enrichment linked to paragenetic stage. The steel ore region, adjacent to major fault intersections, records intense hydrothermal fluid interaction, hosting Ni- and As-rich phases such as nickeline, gersdorffite, and arsenopyrite. These findings highlight the importance of structural controls and fluid mixing in metal transport and deposition, positioning the LOM as a key stratigraphic unit for understanding ore-forming processes in Irish-type systems. These results have implications for targeting similar carbonate-hosted systems globally, especially where deeper or structurally complex ore zones remain underexplored.

58 - GEOSCIENCES↗
DOE OSTI2026

Conserving asphalt resources: Rethinking rejuvenator performance evaluation through peptizing efficiency

Timely rejuvenation and restoration of asphalt are essential conservation practices that help preserve and extend the service life of roads, bridges, driveways, and parking lots. The performance of asphalt rejuvenators is often assessed based on their diffusion rates and softening power, yet these metrics alone fail to capture true rejuvenation potential. Here, this study integrates density functional theory (DFT) modeling with experimental analysis to show that rejuvenation effectiveness is primarily governed by molecular interactions with oxidized asphaltene nanoaggregates. DFT results revealed that amide- and unsaturated-chain compounds, such as hexadecanamide, oleic acid, and 9,17-octadecadienal, act cooperatively to disrupt π–π stacking and exfoliate asphaltene layers, reducing binding strength and enhancing dispersion. Unlike bulky, rigid molecules that remain trapped, these components remain mobile and repeatedly interact with multiple aggregation sites. Experimental validation using rheometry and FTIR confirmed that such molecularly compatible rejuvenators restore the binder flexibility and polydispersity, even when diffusion is relatively slow. Building on this mechanistic foundation, six rejuvenators (A2, A5, A7, A8, A9, and A10) were evaluated using a three-metric performance framework encompassing cracking resistance (Glover–Rowe parameter), UV stability, and surface hydrophobicity. Among the six rejuvenators evaluated, A9 exhibited the highest overall performance, reducing the Glover–Rowe cracking parameter by 85% (from 351 kPa to 53 kPa), demonstrating the greatest resistance to UV-induced aging with a stability index of 4.17 h·kPa⁻¹, and increasing surface hydrophobicity to a contact angle of 103.6°. Its superior performance is primarily attributed to its amide- and unsaturated-chain components, which act cooperatively to disrupt π–π stacking interactions and exfoliate asphaltene layers, thereby promoting molecular deagglomeration and enhancing long-term durability. These results shift the criteria for selecting rejuvenators: effective candidates must pair the electronic capability to unlock aged asphaltenes with sufficient structural stability to resist secondary aging and restore hydrophobicity. Restoring hydrophobicity is critical, as aging reduces the asphalt’s water repellency and increases water diffusion, which in turn accelerates moisture-related damage; consequently, a high-performing rejuvenator must effectively restore the binder’s hydrophobic characteristic. Collectively, these findings provide a framework for the rational design of next-generation of bio-based rejuvenators that enhance pavement longevity and promote long-term sustainability.

Aging↗
DOE OSTI2025

Crystallization Mechanisms of Poly(vinylidene Fluoride- co -chlorotrifluoroethylene): Nucleation Transitions, Growth Kinetics, and Microstructure Evolution

The crystallization kinetics of FK-800, a commercial semicrystalline copolymer of chlorotrifluoroethylene and vinylidene fluoride (poly(CTFE-co-VDF)), dictate its microstructure and functional performance. Crystallization occurs between the glass transition (T g ≈ 31 °C) and melting point (T m ≈ 110 °C), with grain boundaries playing a key role in applications such as memristors, where they regulate filament growth. This study integrates in situ atomic force microscopy (AFM), grazing-incidence wide-angle X-ray scattering (GIWAXS), and differential scanning calorimetry (DSC) to characterize nucleation, growth, and morphology across the full crystallization window. Hot-stage AFM reveals a transition from homogeneous to heterogeneous nucleation near 45 °C and a shift from reaction-limited to diffusion-limited growth above 60 °C. Kinetics are analyzed using Lauritzen–Hoffman, Turnbull–Fisher, and Avrami models to extract surface free energies and activation barriers. A multiscale modeling framework is developed in which nucleation densities and growth rates measured by AFM are used to reconstruct Avrami kinetics, which are then validated against coverage data, and extrapolated to predict bulk crystallization behavior observed by DSC. GIWAXS confirms a primarily flat-on chain orientation at all temperatures, linking orientation to domain morphology. This integrative approach quantitatively connects nanoscale crystallization dynamics with macroscopic phase evolution, establishing a quantitative framework for modeling crystallization across time, temperature, and length scales.

Crystallization↗
DOE OSTI2023

Impedance-Based Detection of NO 2 Using Ni-MOF-74: Influence of Competitive Gas Adsorption

Chemically robust, low-power sensors are needed for the direct electrical detection of toxic gases. Metal–organic frameworks (MOFs) offer exceptional chemical and structural tunability to meet this challenge, though further understanding is needed regarding how coadsorbed gases influence or interfere with the electrical response. To probe the influence of competitive gases on trace NO 2 detection in a simulated flue gas stream, a combined structure–property study integrating synchrotron powder diffraction and pair distribution function analyses was undertaken, to elucidate how structural changes associated with gas binding inside Ni-MOF-74 pores correlate with the electrical response from Ni-MOF-74-based sensors. Data were evaluated for 16 gas combinations of N 2 , NO 2 , SO 2 , CO 2 , and H 2 O at 50 °C. Fourier difference maps from a rigid-body Rietveld analysis showed that additional electron density localized around the Ni-MOF-74 lattice correlated with large decreases in Ni-MOF-74 film resistance of up to a factor of 6 × 10 3 , observed only when NO 2 was present. These changes in resistance were significantly amplified by the presence of competing gases, except for CO 2 . Without NO 2 , H 2 O rapidly (<120 s) produced small (1–3×) decreases in resistance, though this effect could be differentiated from the slower adsorption of NO 2 by the evaluation of the MOF’s capacitance. Furthermore, samples exposed to H 2 O displayed a significant shift in lattice parameters toward a larger lattice and more diffuse charge density in the MOF pore. Evaluating the Ni-MOF-74 impedance in real time, NO 2 adsorption was associated with two electrically distinct processes, the faster of which was inhibited by competitive adsorption of CO 2 . Together, this work points to the unique interaction of NO 2 and other specific gases (e.g., H 2 O, SO 2 ) with the MOF’s surface, leading to orders of magnitude decrease in MOF resistance and enhanced NO2 detection. Finally, understanding and leveraging these coadsorbed gases will further improve the gas detection properties of MOF materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗