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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Metal fluxes at the sediment–water interface in a free water surface constructed wetland

Metal biogeochemistry in the sediment, water, and the sediment–water interface (SWI) was studied in a free water surface constructed wetland. Concentrations of labile copper (Cu), zinc (Zn), sulfate, chloride, and dissolved organic carbon (DOC) were measured with the diffusive gradients in thin film (DGT) and peeper. A good agreement between peeper- and DGT-measured metals was observed for Cu (regression r 2 = 0.3, 95% CI of the slopes > 0), but not for Zn (95% CI of the slopes overlapped with 0), which was attributed to the different complexed compounds between Cu and Zn in porewater. The depth profile of labile metals in sediment porewater varied with time and was consistent with the solid-phase metal deposition, showing higher concentrations in the surface layer (3 to –3 cm) than in the bottom layer (–4 to –13 cm). The depth-averaged labile Cu and Zn concentrations measured by DGT were 1.0 and 3.1 µg/L, and labile sulfate, chloride, and DOC concentrations measured by peeper were 1.8, 3.6, and 2.1 mg/L, respectively. A sharp decrease in sulfate occurred in September when sulfate concentrations became the lowest among sampling months. This was caused by the seasonal sulfur cycles in the wetland, where the dominant sulfur reaction is sulfate reduction in warm seasons and sulfide oxidation in cold seasons. Different metal-removal mechanisms were observed in the two wetland cells; sulfur dynamics controlled the removal processes in the cell without frequent disturbance but failed to influence metal removal in the cell with frequent disturbance due to the interruption of anoxic layers. The flux ratios that compare labile element concentrations between the water column and the SWI (R-Cu, R-Zn, R-DOC, R-sulfate, and R-chloride) were generated to determine metal diffusive fluxes at the interface. Labile Zn was mostly transported from the water to the SWI during all seasons (R-Zn < 1 for all months except January). Labile Cu moved from the SWI to the water during the warm months (R-Cu < 1), which was explained by the bioturbation-induced transport of organic matter based on the positive correlations between R-Cu and R-DOC. In general, sediment can serve either as a sink or a source depending on the environmental conditions, metal speciation, and presence of living organisms. Here, metal flux at the SWI is a key component in the biogeochemical cycling of a constructed wetland.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Metal Removal by a Free Surface Constructed Wetland and Prediction of Metal Bioavailability and Toxicity with Diffusive Gradients in Thin Films (DGT) and Biotic Ligand Model (BLM)

The H-02 constructed wetland is a free water surface wetland to remove copper (Cu) and zinc (Zn) from the industrial wastewater. In this study, we evaluated the performance of the wetland from 2018 to 2019 and coupled the diffusive gradients in thin films (DGTs) and biotic ligand model (BLM) to explore metal speciation and bioavailability in wetland waters. Surface water samples were collected and piston DGTs were deployed in different sites of the wetland. The H-02 wetland functioned well during the sampling period with high removal efficiencies (Cu: 73.8 ± 1.2% and Zn: 75.2 ± 16.0%). In our study, with the assumption that the combination of BLM predicted inorganic metals species, BLM Cu(II) and BLM Zn(II), were the bioavailable and toxic species, DGT-Cu did not correlate to BLM Cu(II) (P = 0.47), but DGT-Zn positively correlated to BLM Zn(II) (R 2 = 0.35, P < 0.001). Compared to the modeling results of BLM, DGT-indicated labile and/or bioavailable Cu included not only free Cu ions and inorganic Cu complexes but also a high percentage of Cu-labile organic matter complexes. DGT-indicated Zn included free Zn ion, inorganic Zn, and only a low percentage of Zn-labile organic matter complexes. Our findings illustrated the appropriate use of passive sampling techniques and geological modeling when biomonitoring could be substituted. Furthermore, the close monitoring of metal concentrations, speciation, and bioavailability helps us understand metal biogeochemistry and metal removal processes and ensure the long-term sustainability of the constructed wetland.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Wetlands Geoprocessor (v 1.0)

Wetlands have often been described as the “Earth’s kidneys” because wetlands have the ability filter pollutants and purify water. Based upon wetland storage capacity, average daily flow, and inflow nutrient loading this model estimates potential load reductions of nitrate and orthophosphate) from a constructed surface flow wetland (CW). The model relies upon equations, coefficients, and models provided by Cheng et al. 2020 and Cheng & Basu 2017. Nitrogen (N) and phosphorus are important nutrients to ecosystems, but high concentrations can lead to water quality issues. Major sources of these nutrients come from agricultural areas where fertilizer is applied in large quantitates and/or animal waste is present. Excess nitrate and phosphorus may result in overgrowth of algae, which can decrease the dissolved oxygen in water, thereby harming and killing fish and other aquatic species. This model evaluates water purification results and estimates cost to install a surface flow constructed wetlands.

Davis, Cleve↗
DOE OSTI2023

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization in Co3Sn2S2

Abstract Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co 3 Sn 2 S 2 , we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co 3 Sn 2 S 2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co 3 Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co 3 Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Automated discovery and construction of surface phase diagrams using machine learning

Surface phase diagrams are necessary for understanding surface chemistry in electrochemical catalysis, where a range of adsorbates and coverages exist at varying applied potentials. These diagrams are typically constructed using intuition, which risks missing complex coverages and configurations at potentials of interest. More accurate cluster expansion methods are often difficult to implement quickly for new surfaces. We adopt a machine learning approach to rectify both issues. Using a Gaussian process regression model, the free energy of all possible adsorbate coverages for surfaces is predicted for a finite number of adsorption sites. Our result demonstrates a rational, simple, and systematic approach for generating accurate free-energy diagrams with reduced computational resources. Finally, the Pourbaix diagram for the IrO 2 (110) surface (with nine coverages from fully hydrogenated to fully oxygenated surfaces) is reconstructed using just 20 electronic structure relaxations, compared to approximately 90 using typical search methods. Similar efficiency is demonstrated for the MoS 2 surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Ab initio constructed diabatic surfaces of NO{sub 2} and the photodetachment spectra of its anion

A thorough investigation has been performed for electronic structure, topological effect, and nuclear dynamics of NO{sub 2} molecule, where the adiabatic potential energy surfaces (PESs), conical intersections between the ground (X{sup 2}A{sub 1}) and the first excited state (A{sup 2}B{sub 2}), and the corresponding non-adiabatic coupling terms between those states are recalculated [Chem. Phys. 416, 11 (2013)] to achieve enough accuracy in dynamics. We employ beyond Born-Oppenheimer theory for these two state sub-Hilbert space to carry out adiabatic to diabatic transformation (ADT) to obtain the ADT angles and thereby, to construct single-valued, smooth, and continuous diabatic PESs. The analytic expressions for the adiabatic PESs and ADT angles are provided to represent a two-state three-mode diabatic Hamiltonian of NO{sub 2} for performing nuclear dynamics to calculate the photo-electron spectra of its anion. It appears that not only Jahn-Teller type coupling but also Renner-Teller interaction contributes significantly on the overall spectrum. The coupling between the electronic states (X{sup 2}A{sub 1} and A{sup 2}B{sub 2}) of NO{sub 2} is essentially through the asymmetric stretching mode, where the functional form of such interaction is distinctly symmetric and non-linear.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Sink or source? Insights into the behavior of copper and zinc in the sediment porewater of a constructed wetland by peepers

The H-02 free water surface constructed wetland has been applied to remove heavy metals, mainly copper (Cu) and zinc (Zn), from wastewater on the Savannah River Site (Aiken, SC, USA). More and more studies focus on the metal behavior between the sediment and the overlying water, which directly reflects the stability of metals after sedimentation in constructed wetlands. This study focused on the biogeochemical pathways in metal bioavailability and remobilization in the sediment after metals were removed from the overlying water. The dialysis sampling devices (peepers) were used to collect porewater samples from eight depths in the sediment for the measurement of Cu, Zn, dissolved organic carbon (DOC), and major anions (sulfate and chloride). Surface water samples were also collected for the measurement of Cu, Zn, DOC, and anions. Different temporal trends were observed for dissolved Cu between the surface and bottom waters, but not for dissolved Zn. There were no obvious changes in porewater metal concentrations with increasing depths in the sediment. Sediment served as a sink for Cu as only 3% of porewater samples showed higher labile Cu concentrations than the surface water during the entire year. Furthermore, sediment served as a source for Zn in summer and winter as 32% of porewater samples showed higher labile Zn concentrations than the surface water, and these samples were collected at all sediment depths. We think the seasonal changes in the behaviors of Cu and Zn were primarily controlled by the sulfur dynamics and the metal removal processes in the constructed wetland, as well as the different complexing chemistry between Cu and Zn. Also, our study supports that peeper is a powerful tool for studying the biogeochemistry of metals in the sediment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Theoretical/experimental comparison of deep tunneling decay of quasi-bound H(D)OCO to H(D) + CO{sub 2}

The measured H(D)OCO survival fractions of the photoelectron-photofragment coincidence experiments by the Continetti group are qualitatively reproduced by tunneling calculations to H(D) + CO{sub 2} on several recent ab initio potential energy surfaces for the HOCO system. The tunneling calculations involve effective one-dimensional barriers based on steepest descent paths computed on each potential energy surface. The resulting tunneling probabilities are converted into H(D)OCO survival fractions using a model developed by the Continetti group in which every oscillation of the H(D)-OCO stretch provides an opportunity to tunnel. Four different potential energy surfaces are examined with the best qualitative agreement with experiment occurring for the PIP-NN surface based on UCCSD(T)-F12a/AVTZ electronic structure calculations and also a partial surface constructed for this study based on CASPT2/AVDZ electronic structure calculations. These two surfaces differ in barrier height by 1.6 kcal/mol but when matched at the saddle point have an almost identical shape along their reaction paths. The PIP surface is a less accurate fit to a smaller ab initio data set than that used for PIP-NN and its computed survival fractions are somewhat inferior to PIP-NN. The LTSH potential energy surface is the oldest surface examined and is qualitatively incompatible with experiment. This surface also has a small discontinuity that is easily repaired. On each surface, four different approximate tunneling methods are compared but only the small curvature tunneling method and the improved semiclassical transition state method produce useful results on all four surfaces. The results of these two methods are generally comparable and in qualitative agreement with experiment on the PIP-NN and CASPT2 surfaces. The original semiclassical transition state theory method produces qualitatively incorrect tunneling probabilities on all surfaces except the PIP. The Eckart tunneling method uses the least amount of information about the reaction path and produces too high a tunneling probability on PIP-NN surface, leading to survival fractions that peak at half their measured values.

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

Ultrathin Boron Growth onto Nanodiamond Surfaces via Electrophilic Boron Precursors

Diamond as a templating substrate is largely unexplored, and the unique properties of diamond, including its large bandgap, thermal conductance, and lack of cytotoxicity, makes it versatile in emergent technologies in medicine and quantum sensing. Surface termination of an inert diamond substrate and its chemical reactivity are key in generating new bonds for nucleation and growth of an overlayer material. Oxidized high-pressure high temperature (HPHT) nanodiamonds (NDs) are largely terminated by alcohols that act as nucleophiles to initiate covalent bond formation when an electrophilic reactant is available. In this work, we demonstrate a templated synthesis of ultrathin boron on ND surfaces using trigonal boron compounds. Boron trichloride (BCl 3 ), boron tribromide (BBr 3 ), and borane (BH 3 ) were found to react with ND substrates at room temperature in inert conditions. BBr 3 and BCl 3 were highly reactive with the diamond surface, and sheet-like structures were produced and verified with electron microscopy. Surface-sensitive spectroscopies were used to probe the molecular and atomic structure of the ND constructs’ surface, and quantification showed the boron shell was less than 1 nm thick after 1–24 h reactions. Observation of the reaction supports a self-terminating mechanism, similar to atomic layer deposition growth, and is likely due to the quenching of alcohols on the diamond surface. X-ray absorption spectroscopy revealed that boron-termination generated midgap electronic states that were originally predicted by density functional theory (DFT) several years ago. DFT also predicted a negative electron surface, which has yet to be confirmed experimentally here. The boron-diamond nanostructures were found to aggregate in dichloromethane and were dispersed in various solvents and characterized with dynamic light scattering for future cell imaging or cancer therapy applications using boron neutron capture therapy (BNCT). The unique templating mechanism based on nucleophilic alcohols and electrophilic trigonal precursors allows for covalent bond formation and will be of interest to researchers using diamond for quantum sensing, additive manufacturing, BNCT, and potentially as an electron emitter.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A near-stationary subspace for ridge approximation

Response surfaces are common surrogates for expensive computer simulations in engineering analysis. However, the cost of fitting an accurate response surface increases exponentially as the number of model inputs increases, which leaves response surface construction intractable for high-dimensional, nonlinear models. Here we describe ridge approximation for fitting response surfaces in several variables. A ridge function is constant along several directions in its domain, so fitting occurs on the coordinates of a low-dimensional subspace of the input space. We review essential theory for ridge approximation – e.g., the best mean-squared approximation and an optimal low-dimensional subspace – and we prove that the gradient-based active subspace is near-stationary for the least-squares problem that defines an optimal subspace. Motivated by the theory, we propose a computational heuristic that uses an estimated active subspace as an initial guess for a ridge approximation fitting problem. We show a simple example where the heuristic fails, which reveals a type of function for which the proposed approach is inappropriate. We then propose a simple alternating heuristic for fitting a ridge function, and we demonstrate the effectiveness of the active subspace initial guess applied to an airfoil model of drag as a function of its 18 shape parameters.

42 ENGINEERING↗
DOE OSTI2019

Identification of Critical Surface Parameters Driving Lectin-Mediated Capture of Bacteria from Solution

Lectin-functional interfaces are useful for isolation of bacteria from solution because they are low-cost and allow nondestructive, reversible capture. This study provides a systematic investigation of physical and chemical surface parameters that influence bacteria capture over lectin-functionalized polymer interfaces and then applies these findings to construct surfaces with significantly enhanced bacteria capture. The designer block copolymer poly(glycidyl methacrylate)-block-poly(vinyldimethyl azlactone) was used as a lectin attachment layer, and lectin coupling into the polymer film through azlactone–lectin coupling reactions was first characterized. Here, experimental parameters including polymer areal chain density, lectin molecular weight, and lectin coupling buffer were systematically varied to identify parameters driving highest azlactone conversions and corresponding lectin surface densities. To introduce physical nanostructures into the attachment layer, nanopillar arrays (NPAs) of varied heights (300 and 2100 nm) were then used to provide an underlying surface template for the functional polymer layer. Capture of Escherichia coli on lectin–polymer surfaces coated over both flat and NPA surfaces was then investigated. For flat polymer interfaces, bacteria were detected on the surface after incubation at a solution concentration of 10 3 cfu/mL, and a corresponding detection limit of 1.7 × 10 3 cfu/mL was quantified. This detection limit was 1 order of magnitude lower than control lectin surfaces functionalized with standard, carbodiimide coupling chemistry. NPA surfaces containing 300 nm tall pillars further improved the detection limit to 2.1 × 10 2 cfu/mL, but also reduced the viability of captured cells. Finally, to investigate the impact of cell surface parameters on capture, we used Agrobacterium tumefaciens cells genetically modified to allow manipulation of exopolysaccharide adhesin production levels. Statistical analysis of surface capture levels revealed that lectin surface density was the primary factor driving capture, as opposed to exopolysaccharide adhesin expression. These findings emphasize the critical importance of the synthetic interface and the development of surfaces that combine high lectin densities with tailored physical features to drive high levels of capture. These insights will aid in design of biofunctional interfaces with physicochemical surface properties favorable for capture and isolation of bacteria cells from solutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Multiscale modeling of polyisoprene on graphite

The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Surface-Enhanced Raman Scattering Optophysiology Nanofibers for the Detection of Heavy Metals in Single Breast Cancer Cells

Mercury(II) ions (Hg2+) and silver ions (Ag+) are two of the most hazardous pollutants causing serious damage to human health. Here, we constructed surface enhanced Raman scattering (SERS)-active nanofibers covered with 4-mercaptopyridine (4-Mpy)-modified gold nanoparticles (AuNPs) to detect Hg2+ and Ag+. Experimental evidence suggests that the observed spectral changes originate from the combined effect of (i) the coordination between the nitrogen on 4-Mpy and the metal ions and (ii) the 4-Mpy molecular orientation (from flatter to more perpendicular with respect to the metal surface). The relative intensity of a pair of characteristic Raman peaks (at ~428 and ~708 cm-1) was used to quantify the metal ion concentration, greatly increasing the reproducibility of the measurement compared to signal-on or signal-off detection based on a single SERS peak. The detection limit of this method for Hg2+ is lower than that for the Ag+ (5 nM vs 100 nM), which can be explained by the stronger interaction energy between Hg2+ and N compared to Ag+ and N, as demonstrated by density functional theory (DFT) calculations. The Hg2+ and Ag+ ions can be masked by adding ethylenediaminetetraacetate (EDTA) and Cl-, respectively, to the Hg2+ and Ag+ samples. The good sensitivity, high reproducibility and excellent selectivity of these nanosensors were also demonstrated. Furthermore, detection of Hg2+ in living breast cancer cells at the subcellular level is possible thanks to the nanometric size of the herein described SERS nanosensors, allowing high spatial resolution and minimal cell damage.

Zhao, Xingjuan↗
DOE OSTI2019

Structure and Thermodynamic Stability of Zeolitic Imidazolate Framework Surfaces

Extensive efforts over the last several decades have focused on the possibility of “crystal engineering” metal–organic framework (MOF) materials with bulk properties tailored toward specific applications. However, beyond their bulk structure, MOF interfaces and surfaces can also play an important role in governing the materials properties relevant to many applications, including both interfacial mass and/or charge transport. We presently examine the diversity of stable surface structures/terminations of zeolitic imidazolate frameworks (ZIFs), a subclass of MOFs, under a variety of conditions that are characteristic of either gas-phase, “post-synthetic” conditions (relevant to many MOF applications) or solution-phase conditions (typical of those used during MOF synthesis). We construct surface phase diagrams to predict the most stable ZIF surface terminations as a function of external parameters (including temperature, adsorbate pressures, and pH), making explicit comparison against prior experimental observations, when possible. Overall, we find that the resulting phase diagrams can be used to explain the results of prior experimental studies of ZIF terminations across a variety of conditions and provide important insights into the factors that govern the structure of ZIF interfaces.

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

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗
DOE OSTI2013

Theory Aided Design of Active and Durable Nanoscale Cathode Catalysts (Final Report)

One of the greatest technological hurdles to deployment of fuel cells relates to the sluggish activity, low durability and the high cost of the catalysts that are currently employed. For automotive PEM fuel cells to become commercially viable, the Pt-specific power density would need to be reduced to less than 0.2gPt/kW (at cell voltages >0.65 V). This would require the Pt loadings to be less than 0.15 mg Pt /cm 2 MEA within the membrane electrode assembly. This could be achieved by enhancing the catalytic activity at the cathode, thus lowering its overpotential. Various different Pt-alloys have shown 2-4 times enhanced activities over Pt alone but still suffer some of the same durability issues as that of the pure Pt. There is a general loss of active Pt due to dissolution and sintering. While there have been a number of elegant fundamental experimental and theoretical studies on ideal single crystal Pt and Pt alloy surfaces which have helped to elucidate the factors that control the activity, there have been very few fundamental studies focused on the stability, reactivity and durability of well-defined Pt nanoparticles. We carried out ab initio density functional theory together with a novel double reference method that we developed to simulate constant potential electrochemical systems in order to model the electrocatalytic reduction of oxygen over model Pt alloy surfaces and nanoparticles. These simulations were used to probe the factors that control the electrocatalytic activity, guide the potential selection of new materials and test their stability under reaction conditions. Ab initio calculations were used to determine the reaction energies and activation barriers for a comprehensive array of different elementary adsorption, desorption, surface reaction and diffusion steps over Pt and Pt alloys involved in the electroreduction of oxygen as a function of surface coverage, the electrochemical potential and temperature. The calculations were used to simulate the potential dependent adsorption and surface reaction energies along with activation barriers in order to determine the kinetics for different surface structures and structural features (step edge and corner sites) to provide the necessary input for kinetic Monte Carlo simulations to follow the rates of reaction. More coarse-grained simulated annealing methods were used to help establish the lowest energy structures and morphologies for different Pt and Pt-alloy nanoparticles that form. The results from the DFT calculations were used to establish an ab initio-derived kinetic database that was used in both 2D and 3D kinetic Monte Carlo simulations that were used to follow the electrocatalytic performance over different particle sizes, shapes and compositions. The ab initio calculations together with the kinetic Monte Carlo simulations were used to complete the following objectives: 1) Determine the controlling elementary reaction pathways and intrinsic kinetics involved in ORR and their potential dependent behavior; 2) Establish the influence of the extrinsic reaction environment including surface structure, alloy composition and spatial arrangement and the humidity on ORR kinetics; 3) Elucidate the effects of particle size and morphology as well as the atomic structure and composition of nanoparticles of Pt, Pt 3 Co, Pt 3 Ni, Pt 3 Fe and other Pt-alloys on the electrocatalytic activity and reaction selectivity; 5) Construct surface Pourbaix phase diagrams for different Pt and Pt-alloys in order to map out the most stable surface phases for different material compositions and reaction conditions; 6) Elucidate the mechanisms that control dissolution and re-deposition of Pt.

08 HYDROGEN↗
DOE OSTI2023

Numerical Study of Solar Receiver Tube With Modified Surface Roughness for Enhanced and Selective Absorptivity in Concentrated Solar Power Tower

Abstract Concentrated solar power (CSP) is a reliable renewable energy source that is progressively lowering its cost of energy. However, the heat loss due to reflected and emitted radiation hinders the maximum achievable thermal efficiency for solar receiver tubes on the solar tower. Current solar selective coatings cannot withstand the high temperatures that come with state-of-the-art CSP towers often needing to be recoated soon after initial operation. We intend to use Inconel 718 with different additive manufacturing (AM) practices to construct surfaces that allow for more light-trapping to occur. By adjusting printing parameters, we can tailor a surface to allow for more absorption while diminishing emitted radiation heat loss. By using COMSOL Multiphysics, we can generate these theoretical surfaces to emulate a printed surface, and using the coupled Multiphysics we can simulate how the surface dictates radiation properties. Our results show that by having a rougher surface we can enhance the absorptivity of Inconel 718 (IN718) by 38.8%. We expect this work to transform how solar absorber tubes are manufactured without using selective coatings and supplement the US Department of Energy (DOE) 2030 SunShot Initiative.

14 SOLAR ENERGY↗
DOE OSTI2019

Topologically-guided continuous protein crystallization controls bacterial surface layer self-assembly

Abstract Many bacteria and most archaea possess a crystalline protein surface layer (S-layer), which surrounds their growing and topologically complicated outer surface. Constructing a macromolecular structure of this scale generally requires localized enzymatic machinery, but a regulatory framework for S-layer assembly has not been identified. By labeling, superresolution imaging, and tracking the S-layer protein (SLP) from C. crescentus , we show that 2D protein self-assembly is sufficient to build and maintain the S-layer in living cells by efficient protein crystal nucleation and growth. We propose a model supported by single-molecule tracking whereby randomly secreted SLP monomers diffuse on the lipopolysaccharide (LPS) outer membrane until incorporated at the edges of growing 2D S-layer crystals. Surface topology creates crystal defects and boundaries, thereby guiding S-layer assembly. Unsupervised assembly poses challenges for therapeutics targeting S-layers. However, protein crystallization as an evolutionary driver rationalizes S-layer diversity and raises the potential for biologically inspired self-assembling macromolecular nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗