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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data

Abstract. Tikhonov regularization is a tool for reducing noise amplification during data inversion. This work introduces RegularizationTools.jl, a general-purpose software package for applying Tikhonov regularization to data. The package implements well-established numerical algorithms and is suitable for systems of up to ∼ 1000 equations. Included is an abstraction to systematically categorize specific inversion configurations and their associated hyperparameters. A generic interface translates arbitrary linear forward models defined by a computer function into the corresponding design matrix. This obviates the need to explicitly write out and discretize the Fredholm integral equation, thus facilitating fast prototyping of new regularization schemes associated with measurement techniques. Example applications include the inversion involving data from scanning mobility particle sizers (SMPSs) and humidified tandem differential mobility analyzers (HTDMAs). Inversion of SMPS size distributions reported in this work builds upon the freely available software DifferentialMobilityAnalyzers.jl. The speed of inversion is improved by a factor of ∼ 200, now requiring between 2 and 5 ms per SMPS scan when using 120 size bins. Previously reported occasional failure to converge to a valid solution is reduced by switching from the L-curve method to generalized cross-validation as the metric to search for the optimal regularization parameter. Higher-order inversions resulting in smooth, denoised reconstructions of size distributions are now included in DifferentialMobilityAnalyzers.jl. This work also demonstrates that an SMPS-style matrix-based inversion can be applied to find the growth factor frequency distribution from raw HTDMA data while also accounting for multiply charged particles. The outcome of the aerosol-related inversion methods is showcased by inverting multi-week SMPS and HTDMA datasets from ground-based observations, including SMPS data obtained at Bodega Marine Laboratory during the CalWater 2/ACAPEX campaign and co-located SMPS and HTDMA data collected at the US Department of Energy observatory located at the Southern Great Plains site in Oklahoma, USA. Results show that the proposed approaches are suitable for unsupervised, nonparametric inversion of large-scale datasets as well as inversion in real time during data acquisition on low-cost reduced-instruction-set architectures used in single-board computers. The included software implementation of Tikhonov regularization is freely available, general, and domain-independent and thus can be applied to many other inverse problems arising in atmospheric measurement techniques and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of Rooftop Solar Potential in Chernihiv and Lviv, Ukraine, and Efficacy of High-Resolution 3D Data Digital Twins [Slides]

NREL evaluated rooftop solar photovoltaic (PV) siting opportunities in the cities of Chernihiv and Lviv, Ukraine, leveraging very-high-resolution 3D elevation data to calculate technical potential. The study assessed total rooftop solar capacity and annual energy production. In Chernihiv and Lviv, 116,503 buildings were analyzed for their rooftop solar potential. The buildings in the study areas include a mixture of residential, commercial, and industrial buildings, characterized by diverse roof shapes and sizes. The total estimated rooftop solar capacity is 332 MWDC in Chernihiv and 873 MWDC in Lviv with annual energy production up to 376.2 GWhDC in Chernihiv and 995.5 GWhDC in Lviv. This accounting provides a clear estimate of the potential rooftop solar installations that could be realized under optimal conditions, considering both technical constraints and the geographic distribution of available rooftop space. Related to Russia's invasion of Ukraine, NREL estimates loss from buildings damaged or destroyed of 2,754 buildings, 20.15 MWDC of capacity, and 22,869 MWhDC of annual energy production in Chernihiv as well as a loss of 1,316 buildings, 34.49 MWDC of capacity, and 39,369 MWhDC of annual energy production in Lviv. The study also assessed the feasibility of adapting this methodology on a national scale using either simulated digital surface models (DSMs) or a digital twin approach. While the very-high-resolution DSM provided more precise results, the simulated DSM demonstrated reasonable accuracy for broader applications in modeling aggregated distributed solar supply. The feasibility of using a digital twin for Ukraine's national rooftop solar potential is considered promising, with certain limitations in areas with highly variable building stock and heavy war damage.

14 SOLAR ENERGY↗
DOE OSTI2021

Roles of interaction between components in CZZA/HZSM-5 catalyst for dimethyl ether synthesis via CO 2 hydrogenation

The roles of interaction between two catalyst components in CuO–ZnO–ZrO 2 –Al 2 O 3 (CZZA)/HZSM-5 bifunctional catalyst for dimethyl ether (DME) synthesis via carbon dioxide hydrogenation were investigated. It was found that CZZA catalyst showed excellent stability during methanol (MeOH) synthesis for 100 h, while there was a severe loss of catalytic activity in the bifunctional catalyst for DME synthesis. So, the effects of different degrees of intimacy of two catalyst components were studied for DME synthesis, including mixed and separated modes. For the mixed mode, the particle size of catalysts and the amount of reaction intermediates were proven to influence the catalyst deactivation. For the separated mode, the catalysts showed rapid deactivation within a short time. Various characterizations indicated that the remarkable deactivation of separated mode was mainly caused by the decrease of copper active centers (e.g., sintering and oxidation) and blockage of acid sites via increased coke deposition on HZSM-5.

42 ENGINEERING↗
DOE OSTI2026

Bifunctional Electrocatalysts with High-Entropy Alloys: Bridging Hydrogen Evolution and Oxygen Reduction

High-entropy alloys (HEAs) have emerged as a promising class of bifunctional electrocatalysts capable of simultaneously driving the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) with high activity and durability. Their near-equiatomic multicomponent compositions give rise to unique physicochemical characteristics, including lattice distortion, sluggish diffusion, high-entropy stabilization, and pronounced electronic heterogeneity, that collectively generate diverse and synergistic active sites inaccessible in conventional alloys. This review summarizes recent progress in HEA-based bifunctional electrocatalysis, with a focus on the fundamental mechanisms governing HER and ORR activity, stability, and selectivity. We discuss advances in synthesis strategies, ranging from confined growth and step-alloying to scalable continuous-flow methods, that enable precise control over composition, size, and surface structure. Complementary computational and data-driven approaches, including density functional theory, machine-learning-assisted screening, and descriptor development, are highlighted as essential tools for navigating the vast HEA design space and establishing structure−property relationships. Particular attention is paid to adsorption-energy distributions, multisite cooperativity, and environmental effects under realistic electrochemical conditions. Finally, we outline current challenges and future opportunities for integrating mechanistic understanding with AI-guided, closed-loop design frameworks to accelerate the discovery of next-generation HEA bifunctional electrocatalysts for sustainable energy conversion.

Alloys↗
DOE OSTI2020

A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications

Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the number of reaction intermediates can be very large, and the cost of calculating the adsorption energies by DFT for all surface intermediates even for one active site model can become prohibitive. In this paper, we have identified appropriate descriptors and machine learning models that can be used to predict a significant part of these adsorption energies given data on the rest of them. Furthermore, our investigations also included the case when the species data used to train the predictive model are of different size relative to the species the model tries to predict—this is an extrapolation in the data space which is typically difficult with regular machine learning models. Due to the relative size of the available data sets, we have attempted to extrapolate from the larger species to the smaller ones in the current work. Here, we have developed a neural network based predictive model that combines an established additive atomic contribution based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Electrothermal mineralization of per- and polyfluoroalkyl substances for soil remediation

Abstract Per- and polyfluoroalkyl substances (PFAS) are persistent and bioaccumulative pollutants that can easily accumulate in soil, posing a threat to environment and human health. Current PFAS degradation processes often suffer from low efficiency, high energy and water consumption, or lack of generality. Here, we develop a rapid electrothermal mineralization (REM) process to remediate PFAS-contaminated soil. With environmentally compatible biochar as the conductive additive, the soil temperature increases to >1000 °C within seconds by current pulse input, converting PFAS to calcium fluoride with inherent calcium compounds in soil. This process is applicable for remediating various PFAS contaminants in soil, with high removal efficiencies ( >99%) and mineralization ratios ( >90%). While retaining soil particle size, composition, water infiltration rate, and cation exchange capacity, REM facilitates an increase of exchangeable nutrient supply and arthropod survival in soil, rendering it superior to the time-consuming calcination approach that severely degrades soil properties. REM is scaled up to remediate soil at two kilograms per batch and promising for large-scale, on-site soil remediation. Life-cycle assessment and techno-economic analysis demonstrate REM as an environmentally friendly and economic process, with a significant reduction of energy consumption, greenhouse gas emission, water consumption, and operation cost, when compared to existing soil remediation practices.

Science & Technology - Other Topics↗
DOE OSTI2024

Recommendations for an Applicant to Calculate Activity Data for Greenhouse Gases Estimates

In 2009, the U.S. Nuclear Regulatory Commission (NRC) directed the NRC staff to address climate change issues and consider the impacts of the emissions of carbon dioxide (CO 2 ) and other greenhouse gases (GHGs) in its environmental reviews for major licensing actions (NRC 2009b). To implement this direction from the Commission, the staff issued guidance in 2011 and updated guidance in 2014 in Attachment 1 to Interim Staff Guidance COL/ESP-ISG-026 (NRC 2011; NRC 2014). This guidance provides a simpler method than the method described in RG 4.2 Rev. 3, that an applicant can use to meet the plant parameter envelope (PPE) value from the Generic Environmental Impact Statement for Licensing of New Nuclear Reactors (NR GEIS). NRC staff estimated the 97-year lifecycle GHG emissions from a reference 1000 megawatt electrical (MWe) light-water reactor (LWR) for various activities associated with construction, operation (including uranium fuel cycle), and decommissioning of nuclear power plants and presented the results in Appendix H of the NR GEIS. Appendix H of the NR GEIS includes estimates of direct emissions from construction equipment and emergency diesel engines in a nuclear facility and indirect emissions from workforce vehicular traffic, fuel transportation and the uranium fuel cycle. The NR GEIS Section 3.3 extended the estimates in Appendix H for the installation of two 1000 MWe nuclear reactors on the same site. Scaling factors were used to extrapolate the GHG emissions of a reference 1000 MWe reactor to a two-unit nuclear reactor plant (each reactor unit generating 1000 MWe). GHG emission estimates for building, operation, decommissioning and safe storage (SAFSTOR) for a two-unit nuclear reactor plant would be based on the plant’s physical size, and therefore estimates for these source categories were assumed to be twice the value of the reference 1000 MWe reactor. However, GHG emissions from the fuel cycle (including fuel transportation) were scaled upward by a factor of 3, based on plant efficiencies greater than the 80 percent assumption in Appendix H. Table 1 below shows the PPE emissions for two 1000 MWe nuclear reactors as provided in NR GEIS. The total GHG emissions for two 1000 MWe reactors were calculated as 2,534,000 metric tons (MT) of CO 2 equivalent (CO 2 (e)) based on a 97 year GHG life cycle period. The GHG emissions lifetime of 97 years for a reference nuclear reactor includes a 7-year building phase, 40 years of operation, 10 years of active decommissioning, and 40 years of SAFSTOR operations (NRC 2024). Construction equipment and vehicular traffic from workers commute would contribute to the GHG emissions during a 7-year building phase. Uranium fuel cycle, vehicular traffic, fuel and waste transportation, and testing of standby diesel generators would contribute to GHG emissions during the 40-year operations phase. While NRC’s regulations allow up to 60 years of reactor facility decommissioning, Appendix H estimated that most of the GHGs would occur over an estimated 10-year period during which to the licensee would engage in significant demolition and earth-moving activities, as discussed in Supplement 1 to NUREG-0586 (NRC 2002). Vehicular traffic by the workforce during a 40-year SAFSTOR period would additionally contribute GHG emissions. The carbon footprint for a 40-year SAFSTOR period was separately analyzed from the decommissioning activities as provided in Table YYYY-2 of the staff issued guidance in 2011 (NRC 2011).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Substituent size versus metal binding of inhibitors with variants of influenza endonuclease

The influenza virus causes a significant burden of illness each year. Although vaccination is the most effective method to prevent seasonal influenza infection, viral escape mechanisms make vaccine composition difficult to predict. Antivirals are crucial for decreasing rates of morbidity and mortality from influenza viral infection. The newest anti-influenza drugs target the RNA-dependent RNA polymerase acidic N-terminal (PA N ) endonuclease, a critical component of influenza viral replication machinery. This study examines the structure of inhibitors of PAN that utilize a hydroxypyridinone-based metal-binding pharmacophore (MBP). Specifically, this report explores how the size of substituent groups impacts the binding conformation and affinity of a series of compounds against both wild-type (WT) and resistance mutant strains, I38T and E23K. Co-crystal structures revealed that the distance between compounds and enzyme residue 38 was conserved to maintain strong interactions, resulting in deviations from ideal coordination geometries at the active site metal centers. This suggests the interactions with residue 38 with each compound is important and can impact inhibitor potency as a consequence of distortions in the metal binding geometry of the compounds.

Endonuclease↗
DOE OSTI2021

Self-Assembled Thermoresponsive Molecular Brushes as Nanoreactors for Asymmetric Aldol Addition in Water

The manipulation and tunability of self-assembled block copolymers through external stimuli presents an attractive strategy to develop smart polymer-based nanoreactors as supports for non-orthogonal tandem catalysis. We report on thermoresponsive core-shell micelles based on poly[norbornene-poly(2-methyl-2-oxazoline-block-2-propyl-2-oxazoline)]-graft-poly[norbornene L-proline] (P[NB-P(MeOx-b-PropOx)]-graft-P[NB-L-proline]) as catalyst supports for L-proline. These molecular brushes exhibit large differences in lower critical solution temperature behavior and nanostructure size in water depending on the chain-lengths and proline connectivity. L-Proline-mediated aldol reactions expose the efficiency by which the molecular brushes self-assemble into micelles. Molecular brushes with an extended backbone show higher activity and selectivity, suggesting better core-shell segregation of the micelles and exclusion of water from the catalytic site. Catalytic efficiencies are not improved above the cloud point temperature, the catalytic be-havior is rather sensitive to conformational changes of the polymer chains.

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

How accurate is a machine learning-based wind speed extrapolation under a round-robin approach?

As the size of commercial wind turbines keeps increasing, having accurate ways to vertically extrapolate wind speed is essential to obtain a precise characterization of the wind resource for wind energy production. Recently, machine learning has been proposed and applied to extrapolate wind speed to hub heights. However, previous studies trained and tested the machine learning methods at the same site, giving them an unfair advantage over the conventional extrapolation techniques, which are instead more universal. Here, we use data from four sites in Oklahoma to test a round-robin validation approach for machine learning, under which we train a random forest at a site, and test it at a different site, where the model has no prior knowledge of the wind resource. We quantify how the accuracy of this technique varies with distance from the training site, and we find that it outperforms conventional techniques for wind extrapolation at all the considered spatial separations. We then assess how the accuracy of the machine-learning based approach varies when it is used to predict wind speed in a wind farm far wake. Finally, we explore as case study the performance of the random forest in extrapolating winds during a low-level jet event.

17 WIND ENERGY↗
DOE OSTI2022

Controlled site coverage of strong metal–support interaction (SMSI) on Pd NP catalysts

Here, strong metal–support interaction catalysts have been shown to improve desired product selectivity at the cost of fractional rates due to active site coverage. The goal of this study was to determine if the active site coverage of metallic nanoparticles could be controlled to lower levels than have been previously reported in SMSI catalysts with the aim of improving the rate while maintaining high selectivity. 2Pd–XTi/SiO 2 (2 wt% Pd, X wt% Ti) strong metal–support interaction (SMSI) catalysts with Ti loadings between 0–1.0 wt% were synthesized to control Pd nanoparticle coverage. Calcination at 450 °C and reduction at 550 °C were sufficient for forming ~2 nm sized Pd particles in all catalysts. Increasing the Ti loading from 0.1 to 1.0 wt% increased the surface coverage from 40 to 85% at a fixed reduction temperature of 550 °C. The IR spectra of the SMSI catalysts were similar with a high fraction of linear bonded CO which was much higher than that of Pd nanoparticles of similar size. The SMSI overlayer could be removed by oxidation at 350 °C and re-reduction at 200 °C. EXAFS of the oxidized catalysts indicates that nearly full oxidation of the metallic nanoparticle was required to remove the SMSI overlayer. Oxidation temperatures from 30 to 300 °C partially oxidized the Pd nanoparticles and subsequent re-reduction at 200 °C partially decreases the SMSI coverage. The fractional surface coverage was determined by measuring the rate of propylene hydrogenation with and without the SMSI overlayer. Increasing the reduction temperature from 200 to 550 °C increased the SMSI coverage from 0 to 85% depending on the Ti loading and temperature. In conclusion, after reduction at 550 °C and oxidation at 350 °C, the range of coverages varied between ~10% with 0.1 wt% Ti after re-reduction at 300 °C and ~85% with 1 wt% Ti after reduction at 550 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Composite Analysis for Low-Level Waste Disposal in the Hanford Site Central Plateau (FY 2020) (Rev. 2)

This document provides an updated Hanford Site composite analysis (CA). A Hanford Site CA was prepared and issued in 1998 (PNNL-11800) with an addendum provided in 2002 (PNNL-11800 Addendum 1). The CA was approved in 2002 (Frei, 2002) and has been maintained (DOE/RL-2000-29 and subsequent revisions) to support low-level waste disposal performance assessments (PAs) and disposal authorizations for facilities at the Hanford Site, including the following: Continued operation of the Environmental Restoration Disposal Facility (ERDF) and the 200 East and 200 West Low-Level Burial Grounds; Construction of the Integrated Disposal Facility (IDF); Forthcoming closure of tank residual waste systems such as Waste Management Area (WMA) C. The CA maintenance program resulted in a determination in 2015 (DOE/RL-2015-66) that the Hanford Site CA needed an update for the following reasons: While the initial Hanford Site CA has been maintained since 2001, the accumulation of basis changes reported in the annual summary reports over the succeeding 14 years merit evaluation in an updated analysis; The U.S. Department of Energy (DOE) Headquarters requested in a memorandum in 2015 (Gilbertson and Marcinowski, 2015) that “as soon as the relevant PAs are complete, the CA will be revised to account for all of the new information.” This updated Hanford Site CA accounts for the following new information: 1. Inclusion of a detailed Hanford Site baseline disposition that projects remedial activities through site closure. There have been significant changes through decision making in the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) process that were not available when the original CA was produced; 2. Inclusion of an updated inventory basis, new modeling capabilities, and new decisions reached in the associated record of decision (ROD) that was provided by issuance of DOE/EIS-0391 in fiscal year (FY) 2013. Development of a Hanford Site groundwater model from the baseline provided in a technical transfer of models for the Final Tank Closure and Waste Management Environmental Impact Statement (DOE/EIS-0391) commenced in FY 2014 and resulted in the plateau-to-river (P2R) groundwater flow model that is used in this updated Hanford Site CA; 3. Accounting for pump and treat systems, which were not evaluated in the initial CA. Pump and treat systems have had significant impact on groundwater flow system behavior, contaminant transport, and contaminant removal from Hanford Site groundwater. This process is accounted for in the use of the P2R model for this updated Hanford Site CA; 4. Inclusion of water-level data collected since the initial CA was completed. Data collected as the unconfined aquifer water levels continue to recede since the cessation of large liquid discharges in the late 1990s have led to marked improvement in understanding of the flow system for future conditions, particularly regarding northward flow potential in the critical Gable Gap area. The calibration in the latest version of the P2R model accounts for this information; 5. Inclusion of results from the revised ERDF PA completed in 2013 (WCH-5209) that account for updated inventory and expansion of the ERDF facility to about twice the size that was evaluated in the original CA; 6. Use of updated geoframeworks to provide the structural basis for numerical fate and transport models in the groundwater pathway of this updated CA. The geologic basis for groundwater models has continued to improve with additional data collection and interpretation with the creation and maintenance of the Hanford South Geoframework and the Central Plateau Vadose Zone Geoframework tools; 7. Incorporation of updated tank residual inventory estimates. Tank residual inventory estimates have improved with the incorporation of tank retrieval inventory data for those tanks that have completed retrieval. The CA inventory data package includes this updated information; 8. Incorporation of WMA C PA results. Two additional PAs for tank farm closure decisions are in preparation during the period required to prepare an updated Hanford Site CA: WMA C (FY 2016) and WMA A-AX (in preparation). The WMA C PA results are incorporated into the updated Hanford Site CA, and its grouted residuals model is used as the basis for a release model to account for the other tank farm systems modeling in this updated CA; 9. An update to the IDF PA was submitted in FY 2017 and has been reviewed and approved. The results of the IDF PA are incorporated into this updated CA; 10. Updated risk assessment scenarios. The risk assessment scenarios currently in use for Hanford Site CERCLA and Resource Conservation and Recovery Act of 1976 (RCRA) analyses differ from those evaluated in the initial Hanford Site CA. The representative person exposure scenario evaluated in this updated Hanford Site CA is consistent with recent PAs and CERCLA and RCRA analyses as the Hanford Site. This updated Hanford Site CA provides the following: A comparison of the updated Hanford Site CA all-pathway dose results with the performance measures during the compliance period, which is assumed to begin with site closure in calendar 2070 with the last scheduled disposal action and continue for 1,000 years postclosure (to calendar year 3069); A comparison of Hanford Site CA all-pathway dose results with the performance measures during the postcompliance period to address potential peaks beyond the compliance period. This is accomplished by evaluating dose in the period for 9,000 years following the compliance period (i.e., from calendar year 3070 to 12070).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

The Effect of Grain Boundary Facet Junctions on Segregation and Embrittlement

Junctions are discontinuities in flat grain boundaries that arise in all polycrystalline materials and are thought to play important roles in the response of a grain boundary network to thermal and mechanical loads. A key open question concerns the mechanisms by which solute segregation to junctions impacts properties of the grain boundary. Here, in this work, we investigate the influence of grain boundary facet junctions on solute embrittlement, and we present an analytical model that uses the hydrostatic stress field contributed by dislocations at multiple junctions to describe these effects. Specifically, we study junctions between {112} facets of various lengths in Au $\langle111\rangle$ Σ3 tilt grain boundaries. Copper and silver solutes are employed to determine if the effect of junctions on solute segregation and embrittlement is dependent on size relative to the host. Combined, atomistic simulation data and the analytical model show that Cu and Ag have opposite segregation responses to junctions due to the sign of the hydrostatic stress field induced by junctions. However, a positive shift in the embrittling potency is computed near junctions regardless of solute type or the stress state of the segregation site. Hence, for the conditions studied, junctions consistently shift the energetic landscape towards embrittlement.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sterols are required for the coordinated assembly of lipid droplets in developing seeds

Abstract Lipid droplets (LDs) are intracellular organelles critical for energy storage and lipid metabolism. They are typically composed of an oil core coated by a monolayer of phospholipids and proteins such as oleosins. The mechanistic details of LD biogenesis remain poorly defined. However, emerging evidence suggest that their formation is a spatiotemporally regulated process, occurring at specific sites of the endoplasmic reticulum defined by a specific set of lipids and proteins. Here, we show that sterols are required for formation of oleosin-coated LDs in Arabidopsis. Analysis of sterol pathway mutants revealed that deficiency in several ∆ 5 -sterols accounts for the phenotype. Importantly, mutants deficient in these sterols also display reduced LD number, increased LD size and reduced oil content in seeds. Collectively, our data reveal a role of sterols in coordinating the synthesis of oil and oleosins and their assembly into LDs, highlighting the importance of membrane lipids in regulating LD biogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Molecular-based analysis of nanoparticle solvation: Classical density functional approach

Proper statistical mechanics understanding of nanoparticle solvation processes requires an accurate description of the molecular structure of the solvent. Achieving this goal with standard molecular dynamics (MD) simulation methods is challenging due to large length scales. An alternative approach to this problem can be formulated using classical density functional theory (cDFT), where a full configurational description of the positions of all the atoms is replaced by collective atomic site densities in the molecule. Using an example of the negatively charged silica-like system in an aqueous polar environment represented by a two-site water model, we demonstrate here that cDFT can reproduce MD data at a fraction of the computational cost. An important implication of this result is the ability to understand how the solvent molecular features may affect the system’s properties at the macroscopic scale. A concrete example highlighted in this work is the analysis of nanoparticle interactions with sizes of up to 100 nm in diameter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

In situ observation of medium range ordering and crystallization of amorphous TiO 2 ultrathin films grown by atomic layer deposition

The evolution of medium range ordering (MRO) and crystallization behavior of amorphous TiO 2 films grown by atomic layer deposition (ALD) were studied using in situ four-dimensional scanning transmission electron microscopy. The films remain fully amorphous when grown at 120 °C or below, but they start showing crystallization of anatase phases when grown at 140 °C or above. The degree of MRO increases as a function of temperature and maximizes at 140 °C when crystallization starts to occur, which suggests that crystallization prerequires the development of nanoscale MRO that serves as the site of nucleation. In situ annealing of amorphous TiO 2 films grown at 80 °C shows enhancement of MRO but limited number of nucleation, which suggests that post-annealing develops only a small portion of MRO into crystal nuclei. The MRO regions that do not develop into crystals undergo structural relaxation instead, which provides insights into the critical size and degree of ordering and the stability of certain MRO types at different temperatures. In addition, crystallographic defects were observed within crystal phases, which likely negate corrosion resistance of the film. Our result highlights the importance of understanding and controlling MRO for optimizing ALD-grown amorphous films for next-generation functional devices and renewable energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Joint effects of climate, tree size, and year on annual tree growth derived from tree–ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

generalized least squares (GLS)↗