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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Suppressing Auger Recombination in Multiply Excited Colloidal Silicon Nanocrystals with Ligand-Induced Hole Traps

Nonradiative Auger recombination in multiply excited nanocrystals is a dominant efficiency loss pathway for nanocrystal-containing optoelectronic devices that rely on high-rate emission and absorption operating conditions. Overcoming Auger recombination in these quantum-confined systems is therefore a longstanding challenge to the synthetic nanocrystal as well as device manufacturing communities. Several successful strategies have been realized to reduce Auger recombination, but they rely on complex and time-consuming nanocrystal core/shell synthesis. Alternatively, controlling Auger rates by varying the nanocrystal–ligand-binding chemistry is a promising route to obtain functional tunability, which reduces the barrier to large-scale manufacturing. The covalent surface chemistry and the extremely long-lived photoexcited lifetimes of silicon nanocrystals (Si NCs) make them a unique system among colloidal semiconductor NCs to study the intersection between surface chemistry and photoexcited carrier dynamics. Here, we show that changing the functional group that binds a saturated dodecyl ligand to the surface of nonthermal plasma-synthesized Si NCs from alkyl to thiolate slows Auger recombination rates within multiply excited Si NCs. This reduction in Auger rate persists across Si NC sizes ranging from 3.5 to 8 nm in diameter, but the expected linear dependence of Auger rates on the NC volume is retained for both alkyl and alkylthiolate surface terminations. To understand the origin behind this elongation, we carry out steady-state and time-resolved photoluminescence measurements as well as time-resolved terahertz spectroscopy measurements. These measurements reveal that thiolate groups introduce mid-gap surface states, which, we argue, reduces the photoexcited electron–hole overlap and elongates Auger recombination times. These results highlight how a typically detrimental chemical species—mid-band gap NC surface states—can be beneficial under high-rate absorption/emission conditions.

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

Manifold Learning-Based Polynomial Chaos Expansions for High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantities of interest of the computational or analytical model. For this purpose, we employ Grassmannian diffusion maps, a two-step nonlinear dimension reduction technique which allows us to reduce the dimensionality of the data and identify meaningful geometric descriptions in a parsimonious and inexpensive manner. Polynomial chaos expansion is then used to construct a mapping between the stochastic input parameters and the diffusion coordinates of the reduced space. An adaptive clustering technique is proposed to identify an optimal number of clusters of points in the latent space. The similarity of points allows us to construct a number of geometric harmonic emulators which are finally utilized as a set of inexpensive pretrained models to perform an inverse map of realizations of latent features to the ambient space and thus perform accurate out-of-sample predictions. Thus, the proposed method acts as an encoder-decoder system which is able to automatically handle very high-dimensional data while simultaneously operating successfully in the small-data regime. The method is demonstrated on two benchmark problems and on a system of advection-diffusion-reaction equations which model a first-order chemical reaction between two species. In all test cases, the proposed method is able to achieve highly accurate approximations which ultimately lead to the significant acceleration of UQ tasks.

42 ENGINEERING↗
DOE OSTI2024

Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications

Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. Here, this computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.

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

Experimental and DFT Calculated IR Spectra of Guests in Zeolites: Acyclic Olefins and Host-Guest Interactions

We performed experimental and periodic density functional theory (DFT) IR spectroscopy to investigate the adsorption of acyclic olefins over both acidic and non-acidic zeolites. Two conjugated polyenes, 2,4-dimethyl-1,3-pentadiene (I) and 2,6-dimethyl-2,4,6-octatriene (II) were studied to probe organic intermediates that can form during methanol conversion, and that can lead to deactivating species known collectively as “coke.” We computed vibrational spectra using zeolite-adsorbed and gas-phase models for both neutral and protonated forms of I and II, and compared these DFT results to diffuse reflectance IR Fourier transform (DRIFT) spectra of zeolite-guest systems. Our experimental and computational results are precise enough to pinpoint that the gauche s-cis conformation of species I predominates during adsorption over de-aluminated zeolite beta. Computed zeolite-adsorbed spectra of the protonated species I and II best represent the DRIFT spectra obtained after the adsorption of the olefins on HMOR at 20 ?, with computed bands at 1543 and 1562 cm–1 for molecules I+ and II+, respectively, attributed to the allylic stretching mode, ?(C=C–C+). These computed band frequencies are within 6 cm–1 of experimental data and confirm that the interaction between neutral acyclic olefins and acidic zeolites leads to protonation of the olefin. Comparison of computed spectra of the protonated species in the gas phase to those in the zeolite indicates that the electrostatic interaction between alkenyl and alkadienyl cations and negative zeolite framework does not significantly impact the position of the allylic stretching bands. These results highlight that computed spectroscopy and thermodynamics coupled with experimental spectra can be used for elucidating complex mixtures in zeolites, and certain spectral features of adsorbed olefins can be accurately modeled by gas-phase calculations. ACKNOWLEDGMENTS BM and SMA were supported by the National Science Foundation under Award # CBET-1512442. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support (or partial support) of this research (#589978-ND5, EDH and FCJ). MDB was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences (BES), Division of Materials Science and Engineering. CJM was supported by the DOE, Office of Science, BES, Division of Chemical Sciences, Geosciences, and Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated by Battelle for the U.S. DOE. Computing resources were generously provided through PNNL’s institutional computing (PIC).

Manookian, Babgen↗
DOE OSTI2021

Intelligent Agents for the Optimization of Atomic Layer Deposition

Atomic layer deposition (ALD) is a highly controllable thin film synthesis approach with applications in computing, energy, and separations. The flexibility of ALD means that it can access a massive chemical catalogue; however, this chemical and process diversity results in significant challenges in determining processing parameters that result in stable and uniform film growth with minimal precursor consumption. In situ measurements of the ALD growth per cycle (GPC) can accelerate process development but it still requires expert intuition and time-consuming trial and error to identify acceptable processing parameters. This procedure is made more difficult by the presence of experimental noise in the GPC values and the complexity of ALD surface chemistries. Here, a need exists for efficient optimization approaches capable of autonomously determining processing conditions resulting in optimal ALD film growth. In this work, we present the development of three optimization strategies and compare their performance in optimizing four simulated ALD processes. Furthermore, the effect of noise in the GPC measurements on optimization convergence is studied.

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

Stochastic Kinetics of Nanocatalytic Systems

Catalytic reaction events occurring on the surface of a nanoparticle constitute a complex stochastic process. Although advances in modern single-molecule experiments enable direct measurements of individual catalytic turnover events occurring on a segment of a single nanoparticle, we do not yet know how to measure the number of catalytic sites in each segment or how the catalytic turnover counting statistics and the catalytic turnover time distribution are related to the microscopic dynamics of catalytic reactions. Here, we address these issues by presenting a stochastic kinetics for nanoparticle catalytic systems. We propose a new experimental measure of the number of catalytic sites in terms of the mean and variance of the catalytic event count. By considering three types of nanocatalytic systems, we investigate how the mean, the variance, and the distribution of the catalytic turnover time depend on the catalytic reaction dynamics, the heterogeneity of catalytic activity, and communication among catalytic sites. This work enables accurate quantitative analyses of single-molecule experiments for nanocatalytic systems and enzymes with multiple catalytic sites.

Statistical Physics↗
DOE OSTI2025

Life cycle assessment of a novel gas switching reforming for sustainable hydrogen production with CO2 capture

Gas switching reforming for hydrogen production (GSR-H2) presents an efficient, low-carbon hydrogen production method that incorporates integrated carbon capture, offering efficiency gains over traditional methods such as proton exchange membrane (PEM) electrolysis, steam methane reforming (SMR) and the newer method of chemical looping reforming (CLR). GSR-H2 has been demonstrated in lab scale which operates as an exothermic process that eliminates the need for additional natural gas combustion, using its own waste heat to generate process steam and partially offset energy usage through electricity production. Beyond its thermal self-sufficiency, GSR-H2 advances upon CLR by integrating all reaction stages within a single reactor cluster, eliminating the complexities of solid circulation, reducing capital costs, and enhancing overall process efficiency. This streamlined design simplifies scale-up and enables inherent CO2 separation with minimal energy penalty, making GSR-H2 a highly competitive pathway for low-carbon hydrogen production. This study presents the first life cycle assessment (LCA) of GSR-H2, offering a novel evaluation of this new process’s environmental impacts across diverse energy scenarios. Key findings reveal that in the renewables-powered scenario, GSR-H2 achieves a GWP of 2.77 kg CO2 eq per kg H2, a substantial improvement over SMR’s 10.4 kg CO2 eq and close to the low emissions of CLR (1.84 kg CO2 eq) and PEM electrolysis (1.85 kg CO2 eq). These results demonstrate GSR-H2’s competitive advantage as a lower-emission alternative, combining design simplicity and efficiency gains, especially in renewable-integrated systems. These results establish GSR-H2 as a competitive, scalable option for hydrogen production, particularly in decarbonization efforts.

03 NATURAL GAS↗
DOE OSTI2023

Climate response to off-equatorial stratospheric sulfur injections in three Earth system models – Part 2: Stratospheric and free-tropospheric response

The paper constitutes Part 2 of a study performing a first systematic inter-model comparison of the atmospheric responses to stratospheric aerosol injection (SAI) at various single latitudes in the tropics, as simulated by three state-of-the-art Earth system models – CESM2-WACCM6, UKESM1.0, and GISS-E2.1-G. Building on Part 1 (Visioni et al., 2023) we demonstrate the role of biases in the climatological circulation and specific aspects of the model microphysics in driving the inter-model differences in the simulated sulfate distributions. We then characterize the simulated changes in stratospheric and free-tropospheric temperatures, ozone, water vapor, and large-scale circulation, elucidating the role of the above aspects in the surface SAI responses discussed in Part 1. We show that the differences in the aerosol spatial distribution can be explained by the significantly faster shallow branches of the Brewer–Dobson circulation in CESM2, a relatively isolated tropical pipe and older tropical age of air in UKESM, and smaller aerosol sizes and relatively stronger horizontal mixing (thus very young stratospheric age of air) in the two GISS versions used. We also find a large spread in the magnitudes of the tropical lower-stratospheric warming amongst the models, driven by microphysical, chemical, and dynamical differences. These lead to large differences in stratospheric water vapor responses, with significant increases in stratospheric water vapor under SAI in CESM2 and GISS that were largely not reproduced in UKESM. For ozone, good agreement was found in the tropical stratosphere amongst the models with more complex microphysics, with lower stratospheric ozone changes consistent with the SAI-induced modulation of the large-scale circulation and the resulting changes in transport. In contrast, we find a large inter-model spread in the Antarctic ozone responses that can largely be explained by the differences in the simulated latitudinal distributions of aerosols as well as the degree of implementation of heterogeneous halogen chemistry on sulfate in the models. The use of GISS runs with bulk microphysics demonstrates the importance of more detailed treatment of aerosol processes, with contrastingly different stratospheric SAI responses to the models using the two-moment aerosol treatment; however, some problems in halogen chemistry in GISS are also identified that require further attention. Overall, our results contribute to an increased understanding of the underlying physical mechanisms as well as identifying and narrowing the uncertainty in model projections of climate impacts from SAI.

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

Cathodic Protection Modeling for Hanford Underground Double-Shell Tank Farms

Hanford stores millions of gallons of radioactive and chemically hazardous waste from the production of weapon materials in tank farms consisting of underground carbon-steel storage tanks surrounded by reinforced concrete. Six of these Hanford tank farms use double-shell storage tanks (DSTs). The DST farms were constructed from 1968 to 1986 with a planned 40–50 year design life, so some are already operating beyond their initial life expectancy. Ultrasonic testing (UT) has indicated significant thinning on the bottom of the secondary (outer) liner of these tanks, believed to arise from groundwater intrusion driving concrete side corrosion. There is no direct access to the steel/concrete interface between the tank and the concrete pad, making it difficult to apply a chemical-based mitigation strategy or to conduct repairs, but cathodic protection (CP) is a possible method to inhibit further concrete-side corrosion. Hanford already uses CP to protect below grade steel piping within the tank farms and connected to the tanks, but this system was not designed to protect the tank bottoms. CP design must account for the structures surrounding the DSTs, including the steel reinforcing bars (rebar) within the concrete pad and vault, various process lines, and the existing CP system. In this study, finite element analysis (FEA) modeling was carried out to simulate CP protection of 1) a single tank and CP anode to develop options for modeling the rebar and to compare to a simpler circuit model and 2) the entire Hanford AN tank farm as a representative example consisting of seven tanks, associated piping, and both existing and new CP anodes. Both circuit and FEA models predict that significant protective current could be delivered to the bottoms of the tanks with the addition of tank-protection anodes below the depth of the tanks. Simulations with only the existing pipe-protection anodes active confirmed that only a very small current to the tank bottoms is predicted under present conditions. Multiple simplified representations of the dome and wall rebar were tested to reduce the computational complexity of the tank-farm simulations, resulting in modeling the rebar as edge elements with a prescribed effective circumference that matches the real rebar surface area. The geometry of the rebar is also simplified into horizontal hoops around the tank walls and radial rebar over the dome with increased effective circumference to retain the target surface area. This simplification was found to greatly reduce the complexity and solution time of the models without large changes in current distributions, especially to the tank bottom. A range of values were tested for model parameters such as soil and concrete resistivities and polarization resistance to investigate their impact on the current and electric potential distributions. Depending on the parameters used, FEA simulations predict some risk of overprotection, particularly on the piping system; since overprotection can also lead to surface damage associated with hydrogen gas generation at the interface (e.g. hydrogen embrittlement or damage to coatings), this needs to be considered when refining the design of the new CP system. Comparison between the FEA models and the circuit model representation demonstrated that the circuit model could not match the predicted FEA current distribution, even when using the exact same surface areas. This discrepancy appeared to be at least partly attributable to the impact of the relative positions of the tank components and anodes to each other and to the ground surface. The FEA model accounts for the relative positions since it solves the governing equations in three dimensions, but the circuit model cannot account for the positioning. In particular, the circuit model underpredicts the current to the tank bottom and overpredicts the current to the dome compared to FEA for the baseline geometry. The FEA models omitted the electrically isolated rebar in the bottom concrete slab. However, a circuit based stray current model estimated that only 2.1% of the total current through the slab would stray into the rebar, corresponding to ~0.21 A for a target current density of 2 mA/ft2 to the tank bottom. The estimated corrosion driven by this amount of stray current is predicted to yield a lifetime of >400 years for the minimum rebar diameter, assuming an acceptable cross-section area loss of 10%.

d'Entremont, Anna [Savannah River National Laborat↗
DOE OSTI2021

Adsorption and activation of CO 2 on Pt/CeOx/TiO 2 (110): Role of the Pt-CeO x interface

The adsorption and dissociation of CO 2 on TiO 2 (110), CeO x /TiO 2 (110) and Pt/CeO x /TiO 2 (110) surfaces has been examined using Ambient Pressure X-ray Photoelectron Spectroscopy (AP-XPS). The substrates under study exhibited different degrees of complexity which were tested for the binding of the adsorbate and the cleavage of C-O bonds. The surfaces were prepared by depositing CeO x (0.1 ML) onto TiO 2 (110) to form a mixed oxide support, onto which Pt nanoparticles (0.2 ML) were deposited. This configuration yields a complex set of interfaces between metal and oxides and we have systematically titrated the active role of each component (Pt 4f, Ce 3d and Ti 2p regions) and the arising surface intermediates (C 1s and O 1s regions). CO 2 barely bonds to stoichiometric TiO 2 (110). It heals oxygen vacancies of this oxide surface (CO 2,gas → CO gas + O a ) and does not form stable carbonates. A stable carbonate was seen upon adsorption of CO 2 on CeO x /TiO 2 (110) and on this type of substrate the adsorbate also removed O vacancies leading to the oxidation of Ti 3+ and Ce 3+ sites. Pt nanoparticles dispersed on CeO x /TiO 2 (110) were highly effective for the binding and dissociation of CO 2 , with the formation of CO 3 , CO, C and CH x species on the Pt/CeO x /TiO 2 (110) system. The results of theoretical calculations based on density-functional theory (DFT) show that Pt/CeOx/TiO2(110) binds CO2 much stronger than surfaces of bulk platinum {(111), (100), (110)} or other late transition metals. On a Pt-CeO x interface, the molecule adsorbs with a bent configuration (~ 130° O-C-O bond angle) and with a substantial elongation (~ 0.1 Å) of the C-O bonds, facilitating its transformation into high value chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Role of the Terrestrial Biosphere in Atmospheric Chemistry and Climate

The terrestrial biosphere–atmosphere interface provides a key chemical, biological, and physical lower boundary for the atmosphere. The presence of vegetation itself modifies the physical boundary, or the biogeophysical aspects of the system, by controlling important climate drivers such as soil moisture, light environment, and temperature. The leaf surface area of the terrestrial biosphere provides additional surface area for emissions, and it can be up to 55% of the total Earth’s surface area during the boreal summer. Vegetation also influences the biogeochemical aspects of the system by emitting a broad suite of reactive trace gases such as biogenic volatile organic compound (BVOC) emissions and climate-relevant primary biological aerosol particles (PBAP). Many of these emissions are a function of meteorological and climatological conditions at the surface, including temperature, light environment, soil moisture, and winds. Once emitted, they can be processed in the troposphere through a suite of chemical reactions. BVOC can contribute to the formation of ozone and secondary organic aerosols (SOA), and PBAP can rupture to form smaller particles with climatic relevance. These emissions and subsequent aerosol products can influence atmospheric processes that affect the surface climate, such as the attenuation of radiation, the formation of greenhouse gases such as ozone that can feedback to surface air temperature, and the alteration of clouds and subsequent precipitation. These atmospheric changes can then feedback to the land surface and emissions themselves, creating positive or negative feedback loops that can dampen or amplify the emission response. For the dominant BVOC isoprene, the feedback response to temperature can be positive or negative depending on ambient temperatures that drive isoprene emissions. The feedback response to soil moisture and precipitation can be positive, negative, or uncoupled depending on the moisture content of the soil and the total atmospheric aerosol loading. For light, the isoprene response can be positive or negative depending on the role of diffuse light. Overall, these feedbacks highlight the dynamical response of the biosphere to changing atmospheric conditions across a range of time scales, from minutes for trace gases and aerosols, to months for phenological changes, to years for land cover and land use change. Here, the dynamic aspect of this system requires us to understand, simulate, and predict the complex feedbacks between the biosphere and atmosphere and understand their role in the simulation and understanding of climate and global change. From the observational perspective, these feedbacks are challenging to identify in observations, and predictive modeling tools provide a crucial link for understanding how these feedbacks will change under warming climate scenarios.

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

Sequential Dosing Strategies for Controlling Selectivity and Plasma-Phase Contributions in Plasma Catalysis

Plasma-assisted catalysis has advanced in recent years, particularly for transforming stable reactants at atmospheric pressure and ambient temperature. However, achieving a deeper understanding of the many plasma and catalytic contributions remains a significant goal, as improving product yield and selectivity in plasma catalysis depends on proper catalyst selection, which is often challenging due to the complex interplay between plasma-phase and plasma-surface reactions. A sequential methodology has emerged as a means to decouple the catalyst activity from plasma-phase reactions. In this approach, nonthermal plasma is used in one step to activate and/or convert a gas phase or surface bound reactant, while in a second step, the catalyst directs product formation under steady-state or temperature-programmed conditions. This review examines studies using this technique for reactions involving N 2 , CO 2 , and SO 2 , offering insights into reaction mechanisms and catalyst behavior/selection for these transformations. These systematic studies provide a framework that can be applied to other plasma-assisted reactions. We also highlight remaining questions, propose directions for future studies, and discuss the potential of applying this methodology to other reaction systems.

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

In-depth understanding of molecular mechanisms of aldehyde toxicity to engineer robust Saccharomyces cerevisiae

Aldehydes are ubiquitous electrophilic compounds that ferment microorganisms including Saccharomyces cerevisiae encounter during the fermentation processes to produce food, fuels, chemicals, and pharmaceuticals. Aldehydes pose severe toxicity to the growth and metabolism of the S. cerevisiae through a variety of toxic molecular mechanisms, predominantly via damaging macromolecules and hampering the production of targeted compounds. Compounds with aldehyde functional groups are far more toxic to S. cerevisiae than all other functional classes, and toxic potency depends on physicochemical characteristics of aldehydes. The yeast synthetic biology community established a design–build–test–learn framework to develop S. cerevisiae cell factories to valorize the sustainable and renewable biomass, including the lignin-derived substrates. However, thermochemically pretreated biomass-derived substrate streams contain diverse aldehydes (e.g., glycolaldehyde and furfural), and biological conversions routes of lignocellulosic compounds consist of toxic aldehyde intermediates (e.g., formaldehyde and methylglyoxal), and some of the high-value targeted products have aldehyde functional group (e.g., vanillin and benzaldehyde). Numerous studies comprehensively characterized both single and additive effects of aldehyde toxicity via systems biology investigations, and novel molecular approaches have been discovered to overcome the aldehyde toxicity. Based on those novel approaches, researchers successfully developed synthetic yeast cell factories to convert lignocellulosic substrates to valuable products, including aldehyde compounds. Here, we highlight the salient relationship of physicochemical charac- teristics and molecular toxicity of aldehydes, the molecular detoxification and macromolecules protection mechanisms of aldehydes, and the advances of engineering robust S. cerevisiae against complex mixtures of aldehyde inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A DFT Comparison of C–C Reductive Coupling from Terminal Cyanido and Cyaphido Complexes of Nickel

The density functional theory study of the thermal C–C reductive coupling from terminal cyanido and hypothetical cyaphido complexes of [Ni(dmpe)] (dmpe = 1,2-bis(dimethylphosphino)ethane) revealed the key reaction intermediate in the reductive C–CP coupling being a σ-CC complex unlike an η 2 -aryl complex in the Ni C–CN system, as already observed in our previous studies. The reaction in THF is endothermic by 4.9 kcal/mol for cyanido with a 32.0 kcal/mol activation barrier and exothermic by 28.5 kcal/mol for cyaphido with an 11.3 kcal/mol activation barrier. To compare our results with the existing experimental data, we chose mesityl as the aryl group and also studied the CP reaction with [Pt(dmpe)] and [Pt(dmpm)] (dmpe = 1,2-bis(dimethylphosphino)methane) fragments. Our findings are consistent with the thermodynamically uphill photolytic C–CP bond activation in phosphaalkynes with Pt and a faster thermal back-reaction with [Pt(dmpe)] compared to that of [Pt(dmpm)]. Furthermore, based on the natural population analysis, when the polarity of the C–C bond is inverted, the sign of ΔG° is also inverted.

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

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

In operando studies of CO oxidation on epitaxial SrCoO 2.5+δ thin films

The high abundance and fast kinetics of select transition metal oxide catalysts are attractive features for many chemical and electrochemical device applications. However, the activity of such catalysts can be accompanied by phase instabilities that prevent their widespread usage. Furthermore, complexities associated with variations in phase behavior and oxygen stoichiometry have hindered studies on the true origins of catalytic activity. Here, we explore the interactions between activity, phase stability, and microstructure using in operando synchrotron X-ray techniques and gas chromatography/mass spectroscopy (GCMS) to probe the behavior of model SrCoO 2.5+δ (SCO) catalysts. Pulsed laser deposition was used to prepare SCO thin films on (001) SrTiO 3 , (111) SrTiO 3 , and pseudocubic (001) DyScO 3 substrates. The GCMS catalytic measurements were performed with a custom-built microreactor compatible with a synchrotron X-ray diffractometer at the Advanced Photon Source. The activity for carbon monoxide oxidation was determined as a function of temperature from 500 °C to 800 °C. We show that the SrCoO 2.5+δ films are active for CO oxidation, most likely by direct reaction with lattice oxygen; consequently, the activity was observed to increase as the films become less stable, with the most active film being the one exhibiting the lowest surface and crystal quality. All films decompose at high temperatures, with in operando diffraction indicating the gradual formation of Sr-rich hexagonal and CoO phases. We find that real-time studies of model oxide systems with synchrotron X-rays is a powerful means of gaining insight into the varied processes taking place at catalytic surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bimetallics in a Nutshell: Complexes Supported by Chelating Naphthyridine-Based Ligands

Bimetallic motifs are a structural feature common to some of the most effective and synthetically useful catalysts known, including in the active sites of many metalloenzymes and on the surfaces of industrially relevant heterogeneous materials. However, the complexity of these systems often hampers detailed studies of their fundamental properties. To glean valuable mechanistic insight into how these catalysts function, this research group has prepared a family of dinucleating 1,8-naphthyridine ligands that bind two first-row transition metals in close proximity, originally designed to help mimic the proposed active site of metal oxide surfaces. Of the various bimetallic combinations examined, dicopper(I) is particularly versatile, as neutral bridging ligands adopt a variety of different binding modes depending on the configuration of frontier orbitals available to interact with the Cu centers. Organodicopper complexes are readily accessible, either through the traditional route of salt metathesis or via the activation of tetraarylborate anions through aryl group abstraction by a dicopper(I) unit. The resulting bridging aryl complexes engage in C-H bond activations, notably with terminal alkynes to afford bridging alkynyl species. In this work, the μ-hydrocarbyl complexes are surprisingly tolerant of water and elevated temperatures. This stability was leveraged to isolate a species that typically represents a fleeting intermediate in Cu-catalyzed azide-alkyne coupling (CuAAC); reaction of a bridging alkynyl complex with an organic azide afforded the first example of a well-defined, symmetrically bridged dicopper triazolide. This complex was shown to be an intermediate during CuAAC, providing support for a proposed bimetallic mechanism. These platforms are not limited to formally low oxidation states; chemical oxidation of the hydrocarbyl complexes cleanly results in formation of mixed valence Cu I Cu II complexes with varying degrees of distortion in both the bridging moiety and the dicopper core. Higher oxidation states, e.g. , dicopper(II), are easily accessed via oxidation of a dicopper(I) compound with air to give a Cu II 2 (μ-OH) 2 complex. Reduction of this compound with silanes resulted in the unexpected formation of pentametallic copper(I) dihydride clusters or trimetallic monohydride complexes, depending on the nature of the silane. Finally, development of an unsymmetrical naphthyridine ligand with mixed donor side-arms enables selective synthesis of an isostructural series of six heterobimetallic complexes, demonstrating the power of ligand design in the preparation of heterometallic assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗