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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Stratospheric Heterogeneous Chemistry and Microphysics: Model Development, Validation and Applications

The objectives of this project are to: define the chemical and physical processes leading to stratospheric ozone change that involve polar stratospheric clouds (PSCS) and the reactions occurring on the surfaces of PSC particles; study the formation processes, and the physical and chemical properties of PSCS, that are relevant to atmospheric chemistry and to the interpretation of field measurements taken during polar stratosphere missions; develop quantitative models describing PSC microphysics and heterogeneous chemical processes; assimilate laboratory and field data into these models; and calculate the extent of chemical processing on PSCs and the impact of specific microphysical processes on polar composition and ozone depletion. During the course of the project, a new coupled microphysics/physical-chemistry/ photochemistry model for stratospheric sulfate aerosols and nitric acid and ice PSCs was developed and applied to analyze data collected during NASA's Arctic Airborne Stratospheric Expedition-II (AASE-II) and other missions. In this model, detailed treatments of multicomponent sulfate aerosol physical chemistry, sulfate aerosol microphysics, polar stratospheric cloud microphysics, PSC ice surface chemistry, as well as homogeneous gas-phase chemistry were included for the first time. In recent studies focusing on AASE measurements, the PSC model was used to analyze specific measurements from an aircraft deployment of an aerosol impactor, FSSP, and NO(y) detector. The calculated results are in excellent agreement with observations for particle volumes as well as NO(y) concentrations, thus confirming the importance of supercooled sulfate/nitrate droplets in PSC formation. The same model has been applied to perform a statistical study of PSC properties in the Northern Hemisphere using several hundred high-latitude air parcel trajectories obtained from Goddard. The rates of ozone depletion along trajectories with different meteorological histories are presently being systematically evaluated to identify the principal relationships between ozone loss and aerosol state. Under this project, we formulated a detailed quantitative model that predicts the multicomponent composition of sulfate aerosols under stratospheric conditions, including sulfuric, nitric, hydrochloric, hydrofluoric and hydrobromic acids. This work defined for the first time the behavior of liquid ternary-system type-1b PSCS. The model also allows the compositions and reactivities of sulfate aerosols to be calculated over the entire range of environmental conditions encountered in the stratosphere (and has been incorporated into a trajectory/microphysics model-see above). Important conclusions that derived from this work over the last few years include the following: the HNO3 content of liquid-state aerosols dominate PSCs below about 195 K; the freezing of nitric acid ice from sulfate aerosol solutions is likely to occur within a few degrees K of the water vapor frost point; the uptake and reactions of HCl in liquid aerosols is a critical component of PSC heterogeneous chemistry. In a related application of this work, the inefficiency of chlorine injection into the stratosphere during major volcanic eruptions was explained on the basis of nucleation of sulfuric acid aerosols in rising volcanic plumes leading to the formation of supercooled water droplets on these aerosols, which efficiently scavenges HCl via precipitation.

Turco, Richard P.↗
DOE OSTI2023

Mass transfer in catalytic depolymerization: External effectiveness factors and serendipitous processivity in stagnant and stirred melts

Several heterogeneous catalysts are being developed to recycle plastics. Most operate in viscous polymer melts, where external mass transfer effects could limit the supply of co-reactants to active sites. External mass transfer can also impede the diffusion of long chain products away from the catalyst after each cut. Product egress limitations could potentially confer unintentional processivity to catalyst operation, i.e. a tendency for the catalyst to repeatedly cut the same chain after an initial encounter. We formulate reaction–diffusion equations to quantify mass transfer effects on the co-reactant transport to the catalyst and the degree of serendipitous processivity. Results are developed for catalysts in stagnant or stirred melts, with simple expressions involving Damkohler, Peclet, and Sherwood numbers, i.e. dimensionless combinations of rate constants, catalyst particle size, polymer diffusivities, and shear rates (where applicable). In conclusion, we estimate the impact of these effects for a spherical core–shell catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Rapid characterization of MSW and RDF feedstocks for waste-to-energy process using LIBS and ML techniques

The heterogeneity in the composition of municipal solid wastes (MSW) poses significant challenges in the production of biofuel and bioproducts. This research aims to enhance the accuracy and efficiency of waste analysis and characterization by introducing a fast characterization approach for MSW-derived refuse-derived fuels (RDF) by combining Laser-Induced Breakdown Spectroscopy (LIBS) with advanced machine learning (ML) techniques. The approach combines data pre-processing of LIBS spectra of RDF, and the development of ML models trained on domain and theory-based spectral features for predicting process parameters. These models are adept at predicting key process parameters like High Heating Value (HHV), carbon content, and volatile matter. This approach can achieve an average RRMSE of 2.13% and R 2 of 0.98 or higher for all considered parameters on testing data. This work demonstrates significant potential for improving waste sorting, processing efficiency, and environmental compliance over traditional labor- and time-intensive laboratory waste analysis and characterization.

09 BIOMASS FUELS↗
NASA NTRS2010

Stable Chlorine Isotope Study: Application to Early Solar System Materials

A significantly large mass fractionation between two stable chlorine isotopes is expected during planetary processes In addition, in view of the isotopic heterogeneity of other light elements, the chlorine isotopes can potentially be used as a tracer for the origins and evolutionary processes of early solar system materials. Due to analytical difficulties, however, current chlorine isotope studies on planetary materials are quite controversial among IRMS (gas source mass spectrometry) and/or TIMS (Thermal Ionization Mass Spectrometry) groups [i.e. 1-3]. Although a cross-calibration of IRMS and TIMS indicates that both techniques are sufficiently consistent with each other [4], some authors have claimed that the Cl-37/Cl-35 ratio of geological samples obtained by TIMS technique are, in general, misleadingly too high and variable compared to those of IRMS [3]. For example, almost no differences of Cl isotope composition were observed among mantle materials and carbonaceous meteorites by [3]. On the other hand, according to more recent IRMS work [2], significant Cl isotope variations are confirmed for mantle materials. Therefore, additional careful investigation of Cl isotope analyses are now required to confirm real chlorine isotope variations for planetary materials including carbonaceous chondrites [5]. A significantly large mass fractionation between two stable chlorine isotopes is expected during planetary processes In addition, in view of the isotopic heterogeneity of other light elements, the chlorine isotopes can potentially be used as a tracer for the origins and evolutionary processes of early solar system materials. Due to analytical difficulties, however, current chlorine isotope studies on planetary materials are quite controversial among IRMS (gas source mass spectrometry) and/or TIMS (Thermal Ionization Mass Spectrometry) groups [i.e. 1-3]. Although a cross-calibration of IRMS and TIMS indicates that both techniques are sufficiently consistent with each other [4], some authors have claimed that the 37Cl/35Cl ratio of geological samples obtained by TIMS technique are, in general, misleadingly too high and variable compared to those of IRMS [3]. For eample, almost no differences of Cl isotope composition were observed among mantle materials and carbonaceous meteorites by [3]. On the other hand, according to more recent IRMS work [2], significant Cl isotope variations are confirmed for mantle materials. Therefore, additional careful investigation of Cl isotope analyses are now required to confirm real chlorine isotope variations for planetary materials including carbonaceous chondrites [5]. In order to clarify the stable chlorine isotope features of early solar system materials, we have initiated development of the TIMS technique at NASA JSC applicable to analysis of small amounts of meteoritic and planetary materials. We report here the current status of chlorine isotope analysis at NASA JSC.

Mala,ira. M/↗
DOE OSTI2022

Towards a robust out-of-the-box neural network model for genomic data

The accurate prediction of biological features from genomic data is paramount for precision medicine and sustainable agriculture. For decades, neural network models have been widely popular in fields like computer vision, astrophysics and targeted marketing given their prediction accuracy and their robust performance under big data settings. Yet neural network models have not made a successful transition into the medical and biological world due to the ubiquitous characteristics of biological data such as modest sample sizes, sparsity, and extreme heterogeneity. Here, we investigate the robustness, generalization potential and prediction accuracy of widely used convolutional neural network and natural language processing models with a variety of heterogeneous genomic datasets. Mainly, recurrent neural network models outperform convolutional neural network models in terms of prediction accuracy, overfitting and transferability across the datasets under study. While the perspective of a robust out-of-the-box neural network model is out of reach, we identify certain model characteristics that translate well across datasets and could serve as a baseline model for translational researchers.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Polymer-Oxygen Compatibility Testing: Effect of Oxygen Aging on Ignition and Combustion Properties

The oxygen compatibility of six polymers used in oxygen service was evaluated after exposure for 48 hours to oxygen pressures ranging from 350 to 6200 kPa (50 to 900 psia), and temperatures ranging from 50 to 250 C (122 to 302 F). Three elastomers were tested: CR rubber (C873-70), FKM fluorocarbon rubber (Viton A), and MPQ silicone rubber (MIL-ZZ-765, Class 2); and three thermoplastics were tested: polyhexamethylene adipamide (Zytel 42), polytetrafluoroethylene (Teflon TFE), and polychlorotrifluoroethylene (Neoflon CTFE M400H). Post-aging changes in mass, dimensions, tensile strength, elongation at break, and durometer hardness were determined. Also, the compression set was determined for the three elastomers. Results show that the properties under investigation were more sensitive to oxygen pressure at low to moderate temperatures, and more sensitive to temperature at low to moderate oxygen pressures. Inspection of the results also suggested that both chain scissioning and cross-linking processes were operative, consistent with heterogeneous oxidation. Attempts are underway to verify conclusively the occurrence of heterogeneous oxidation using a simple modulus profiling technique. Finally, the effect of aging at 620 kpa (90 psia) and 121 C (250 F) on ignition and combustion resistance was determined. As expected, aged polymers were less ignitable and combustible (had higher AlTs and lower heats of combustion). Special attention was given to Neoflon CTFE. More specifically, the effect of process history (compression versus extrusion molding) and percent crystallinity (quick- versus slow-quenched) on the AIT, heat of combustion, and impact sensitivity of Neoflon CTFE was investigated. Results show the AIT, heat of combustion, and impact sensitivity to be essentially independent of Neoflon CTFE process history and structure.

Waller, Jess M.↗
DOE OSTI2024

Phase Transitions in Organic and Organic/Inorganic Aerosol Particles

The phase state of aerosol particles can impact numerous atmospheric processes, including new particle growth, heterogeneous chemistry, cloud condensation nucleus formation, and ice nucleation. In this article, the phase transitions of inorganic, organic, and organic/inorganic aerosol particles are discussed, with particular focus on liquid-liquid phase separation (LLPS). The physical chemistry that determines whether LLPS occurs, at what relative humidity it occurs, and the resultant particle morphology is explained using both theoretical and experimental methods. The known impacts of LLPS on aerosol processes in the atmosphere are discussed. Finally, potential evidence for LLPS from field and chamber studies is presented. By understanding the physical chemistry of the phase transitions of aerosol particles, we will acquire a better understanding of aerosol processes, which in turn impact human health and climate.

Chemistry↗
DOE OSTI2020

Large-scale integration of artificial atoms in hybrid photonic circuits

A central challenge in developing quantum computers and long-range quantum networks is the distribution of entanglement across many individually controllable qubits. Colour centres in diamond have emerged as leading solid-state ‘artificial atom’ qubits because they enable on-demand remote entanglement, coherent control of over ten ancillae qubits with minute-long coherence times and memory-enhanced quantum communication. A critical next step is to integrate large numbers of artificial atoms with photonic architectures to enable large-scale quantum information processing systems. So far, these efforts have been stymied by qubit inhomogeneities, low device yield and complex device requirements. Here we introduce a process for the high-yield heterogeneous integration of ‘quantum microchiplets’—diamond waveguide arrays containing highly coherent colour centres—on a photonic integrated circuit (PIC). We use this process to realize a 128-channel, defect-free array of germanium-vacancy and silicon-vacancy colour centres in an aluminium nitride PIC. Photoluminescence spectroscopy reveals long-term, stable and narrow average optical linewidths of 54 megahertz (146 megahertz) for germanium-vacancy (silicon-vacancy) emitters, close to the lifetime-limited linewidth of 32 megahertz (93 megahertz). We show that inhomogeneities of individual colour centre optical transitions can be compensated in situ by integrated tuning over 50 gigahertz without linewidth degradation. The ability to assemble large numbers of nearly indistinguishable and tunable artificial atoms into phase-stable PICs marks a key step towards multiplexed quantum repeaters and general-purpose quantum processors

36 MATERIALS SCIENCE↗
NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗
DOE OSTI2021

Phase transitions in Schloegl's second model for autocatalysis on a Bethe lattice

Schloegl's second model (also known as the quadratic contact process) on a lattice involves spontaneous particle annihilation at rate p and autocatalytic particle creation at empty sites with n ≥ 2 occupied neighbors. The particle creation rate for exactly n occupied neighbors is selected here as n(n - 1)/[z(z - 1)] for lattice coordination number z. We analyze this model on a Bethe lattice. Precise behavior for stochastic models on regular periodic infinite lattices is usually surmised from kinetic Monte Carlo simulation on a finite lattice with periodic boundary conditions. However, the persistence of boundary effects for a Bethe lattice complicates this process, e.g., by inducing spatially heterogenous states. This motivates the exploration of various boundary conditions and unconventional simulation ensembles on the Bethe lattice to predict behavior for infinite size. Here, we focus on z = 3, and predict a discontinuous transition to the vacuum state on the infinite lattice when p exceeds a threshold value of around 0.053.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Solubility-limited depolymerization kinetics in the glycolysis of carbonyl-containing polymers

Chemical recycling of condensation polymers is often rationalized on the basis of the intrinsic reactivity of ester and carbonate functional groups. However, under heterogeneous conditions relevant to plastic waste processing and environmental degradation, bulk depolymerization rates often diverge from trends predicted by homogeneous chemistry. Here, we investigate how polymer–solvent compatibility, catalyst strength, and phase behavior govern the heterogeneous glycolysis of carbonyl-containing polymers. Using poly(ethylene terephthalate) (PET), glycol-modified PET (PETG), and bisphenol-A polycarbonate (PC) as model systems, we examine depolymerization kinetics at 180 °C with ethylene glycol and bisphenol A as diols under both amphoteric organosalt (TBD : MSA) and strong base (TBD) catalysis. Despite substantial differences in crystallinity and glycol uptake, PET and PETG depolymerize at comparable rates under organosalt catalysis, while PC depolymerizes significantly more slowly under identical conditions. Time-resolved molecular weight analysis and thermal characterization demonstrate that these rate differences do not arise from crystallinity, swelling, or inherent carbonyl reactivity, but instead reflect solubility-limited kinetics that constrain the transition from heterogeneous to homogeneous reaction regimes. When polymer solubility is low, depolymerization remains heterogeneous and slow; when solubility is enhanced—either through increased polymer–diol compatibility or stronger base catalysis—rapid homogeneous depolymerization is observed, reversing apparent reactivity trends. These results establish solubility and phase behavior as primary determinants of depolymerization kinetics in heterogeneous polymer recycling systems. By demonstrating how catalyst selection and solvent compatibility can expose or overcome solubility limitations, this work provides mechanistic insight to design more energy-efficient and selective chemical recycling processes. More broadly, these findings suggest that polymers with limited solvent or water compatibility may resist chemical degradation in the environment, favoring fragmentation and persistence as micro- and nanoplastics. Understanding solubility-controlled depolymerization offers a pathway toward more sustainable polymer design and end-of-life chemical recovery.

Watson-Sanders, Shelby [Department of Chemistry, U↗
DOE OSTI2024

X-ray chemical imaging for assessing redox microsites within soils and sediments

Redox reactions underlie several biogeochemical processes and are typically spatiotemporally heterogeneous in soils and sediments. However, redox heterogeneity has yet to be incorporated into mainstream conceptualizations and modeling of soil biogeochemistry. Anoxic microsites, a defining feature of soil redox heterogeneity, are non-majority oxygen depleted zones in otherwise oxic environments. Neglecting to account for anoxic microsites can generate major uncertainties in quantitative assessments of greenhouse gas emissions, C sequestration, as well as nutrient and contaminant cycling at the ecosystem to global scales. However, only a few studies have observed/characterized anoxic microsites in undisturbed soils, primarily, because soil is opaque and microsites require µm-cm scale resolution over cm-m scales. Consequently, our current understanding of microsite characteristics does not support model parameterization. To resolve this knowledge gap, we demonstrate through this proof-of-concept study that X-ray fluorescence (XRF) 2D mapping can reliably detect, quantify, and provide basic redox characterization of anoxic microsites using solid phase “forensic” evidence. First, we tested and developed a systematic data processing approach to eliminate false positive redox microsites, i.e., artefacts, detected from synchrotron-based multiple-energy XRF 2D mapping of Fe (as a proxy of redox-sensitive elements) in Fe-“rich” sediment cores with artificially injected microsites. Then, spatial distribution of Fe II and Fe III species from full, natural soil core slices (over cm-m lengths/widths) were mapped at 1–100 µm resolution. These investigations revealed direct evidence of anoxic microsites in predominantly oxic soils such as from an oak savanna and toeslope soil of a mountainous watershed, where anaerobicity would typically not be expected. We also revealed preferential spatial distribution of redox microsites inside aggregates from oak savanna soils. We anticipate that this approach will advance our understanding of soil biogeochemistry and help resolve “anomalous” occurrences of reduced products in nominally oxic soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Improving GCM Predictability of Mixed-Phase Clouds and Aerosol Interactions at High Latitudes with ARM Observations

The overachieving goal of this project is to improve the predictability of mixed-phase clouds and aerosol interactions in the Community Atmosphere Model version 6 (CAM6) through comparison with the ARM observations. There are three main objectives of the proposed study: (1) Improve the representation of ice microphysical processes in mixed-phase clouds; (2) Test the performance of ice microphysics in CESM-CAM6 with the ARM observations in northern and southern high latitudes; and (3) Examine mixed-phase cloud microphysics-aerosol-turbulence-radiation interactions in CESM-CAM6. In this project, we have (1) Improved the representation of ice microphysical processes in mixed-phase clouds in CESM-CAM6 by implementing the marine organic aerosol (MOA) and treating the ice nucleating particles (INPs) from MOA and its impacts on mixed-phase clouds. We improved the treatment of ice depositional growth through the Wegener–Bergeron–Findeisen (WBF) process by considering the subgrid heterogeneous distributions between liquid droplets and ice crystals in mixed-phase clouds; (2) Tested the performance of ice microphysics in CESM-CAM6 with the ARM observations at high latitudes. We compared the simulated INP concentrations with the ARM observations, e.g., from M-PACE, ISDAC, INPOP, and other data (Mace Head, Zeppelin, CAPRICORN). We examined the impact of improved WBF treatment on model simulated Arctic mixed-phase clouds observed in the M-PACE field campaign. Seasonal variations of modeled mixed-phase cloud properties (LWO, IWP) are compared with the ground-based remote sensing retrievals at the ARM’s NSA $Utqia\dot{g}vik$ site; and (3) Examined mixed-phase cloud microphysics-aerosol-dynamics-radiation interactions in CESM-CAM6 that include the impacts of MOA INPs, and impacts of different model parameterizations (CLUBB versus UW turbulence & shallow convection schemes, MG2 versus MG1) on high-latitude mixed-phase cloud properties. Aerosol indirect effects of MOA through the liquid phase (droplet activation) and ice phase processes (e.g., the glaciation indirect effect) were investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Are System Baselines within OT Environments Feasible?

Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications.Baseline behaviors may vary based on operational context.Expected operations during a maintenance window, for example, may be different from normal operations.Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming.ICS processes generate artifacts expressed across heterogeneous data sources such as network and device logs. There needs to be a corpus of data in order to develop and compare methods that evaluate the feasibility, performance, and generality of approaches to construct baselines for ICS events. Standalone repositories of network packet captures are insufficient to develop methods to classify or recognize operational events expressed across multiple data sources. Moreover, static data corpora do not enable researchers to compare the impact of changing the underlying system for which a baseline is being constructed and this limits the ability to evaluate the performance of system baselines given system changes (e.g. patches, configuration, maintenance events). In order to address these limitations within the community, this talk intends to promote discussion about the state of the practice of constructing baselines. In this manner, we can continue to understand requirements within industry that are not being met by current approaches to baseline construction. This talk builds on two previous talks on the topic of system baselines for OT environments. First, Weaver co-presented at the RSA Conference ICS Sandbox with Dan Gunter. The talk confirmed the need within industry to construct baselines across multiple types of data sources relative to the semantics of specific business processes. Second, Weaver presented at IEEE Security and Privacy Workshop on Language-Theoretic Security.

02 PETROLEUM↗
DOE OSTI2026

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗
DOE OSTI2022

In situ study on medium-range order evolution during the polyamorphous phase transition in a Pd-Ni-P nanostructured glass

Engineering multiscale structural hierarchies in glassy alloys enable a broad spectrum of potential applications. Metallic glasses were born in hierarchical structures from atomic-to-nanometer scales. However, the frozen-in structures in traditional metallic glasses prepared by rapid quenching techniques are challenging to tailor. Here, we show that a Pd 40 Ni 40 P 20 bulk nanostructured glass of polyamorphous interfacial structures was prepared by inert-gas condensation with a laser evaporation source, and its multiscale structures could be engineered. In-situ scattering experiment results reveal polyamorphous phase transitions occurred in the interfacial regions, which are accompanied by the evolution of medium-range order and the nanoscale heterogeneous structures during the condensation process of glassy nanoparticles under high pressure and the following heating process. Moreover, changes in the cluster connectivity resulting from repacking of the local ordering induced by pressure and temperature could be observed. The thermophysical and mechanical properties, including boson peaks, hardness, and elasticity modulus, could be changed as a function of heat-treatment parameters. In conclusion, our findings would shed light on the synthesis of bulk nanostructured glassy alloys with tailorable thermodynamic and dynamical behavior as well as mechanical properties based on the understanding of metastability for polyamorphous interfacial phases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cycles-L: A Coupled, 3-D, Land Surface, Hydrologic, and Agroecosystem Landscape Model

Managing landscapes to increase agricultural productivity and environmental stewardship can be informed by spatially-distributed models that operate at spatial and temporal scales that are intervention-relevant. This paper presents Cycles-L, a landscape-scale agroecosystem and hydrologic modeling system, using as a test case a watershed in Pennsylvania. Cycles-L emerges from melding the landscape and hydrology structure of Flux-PIHM, a 3-D land surface hydrologic model, with the agroecosystem processes in the Cycles model. Consequently, Cycles-L can simulate processes affected by topography, soil heterogeneity, and management practices, owing to its physically-based hydrology that can simulate horizontal and vertical transport of solutes with water. The model was tested at a 730-ha experimental watershed within the Mahantango Creek watershed. Cycles-L simulated well stream water and mineral nitrogen discharge (Nash-Sutcliffe coefficient 0.55 and 0.60, respectively) and grain yield (root mean square error 1.2 Mg ha -1 ). Cycles-L outputs are as good or better than those obtained with the uncoupled Flux-PIHM (water discharge) and Cycles (grain yield) models. Modeled spatial patterns of nitrogen fluxes like denitrification illustrate the combined control of crop management and topography. For example, denitrification is almost twice as high when simulated with Cycles-L than when simulated with Cycles 1-D. Due to its spatial and temporal resolution, Cycles-L fills a gap in the availability of models that operate at a scale relevant to evaluate interventions in the landscape. Cycles-L can become a central component in tools for climate change scenario analysis, precision agriculture, precision conservation, and artificial intelligence-based decision support systems.

54 ENVIRONMENTAL SCIENCES↗