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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nonstoichiometric Salt Intercalation as a Means to Stabilize Alkali Doping of 2D Materials

Although doping with alkali atoms is a powerful technique for introducing charge carriers into physical systems, the resulting charge-transfer systems are generally not air stable. Here, in this paper, we describe computationally a strategy towards increasing the stability of alkali-doped materials that employs stoichiometrically unbalanced salt crystals with excess cations (which could be deposited during, e.g., in situ gating) to achieve doping levels similar to those attained by pure alkali metal doping. The crystalline interior of the salt crystal acts as a template to stabilize the excess dopant atoms against oxidation and deintercalation, which otherwise would be highly favorable. We characterize this doping method for graphene, NbSe 2 , and Bi 2 Se 3 and its effect on direct-to-indirect band gap transitions, 2D superconductivity, and thermoelectric performance. Salt intercalation should be generally applicable to systems which can accommodate this “ionic crystal” doping (and particularly favorable when geometrical packing constraints favor nonstoichiometry).

2-dimensional systems↗
DOE OSTI2023

Effects of the surface termination and the oxygen vacancy position on LaNiO 3 ultra-thin films: First-principles study

In this study, while ultra-thin layers of the LaNiO 3 film exhibit a remarkable metal-insulator transition as the film thickness becomes smaller than a few unit cell (u.c.), the formation of possible oxygen vacancies and their effects on the correlated electronic structure have been rarely studied using first principles. Here, we investigate the effects of the surface termination and the oxygen vacancy position on the electronic properties and vacancy energetics of LaNiO 3 ultra-thin films under the compressive strain using density functional theory plus U (DFT + U). We find that oxygen vacancies can be easily formed in the Ni layers with the NiO 2 terminated surface (0.5 u.c. and 1.5 u.c. thickness) compared to the structures with the LaO terminated surface and the in-plane vacancy is energetically favored than the out-of-plane vacancy. When two vacancy sites are allowed, the Ni square plane geometry is energetically more stable in most cases as two oxygen vacancies tend to stay near a Ni ion. Strong anisotropy between the in-plane and out-of-plane vacancy formation as well as the layer and orbital dependent electronic structure occur due to strain, surface termination, charge reconstruction, and quantum confinement effects. The in-plane vacancy of the NiO 2 terminated structure is favored since the released charge due to the oxygen vacancy can be easily accommodated in the d x 2 -y 2 orbital, which is less occupied than the d z 2 orbital. Remarkably, the oxygen vacancy structure containing the Ni square-plane geometry becomes an insulating state in DFT + U with a sizable band gap of 1.2 eV because the large crystal field splitting between d z 2 and d x 2 -y 2 orbitals in the square-plane favors an insulating state and the Mott insulating state is induced in other Ni sites due to strong electronic correlations. In the thin-film structure without oxygen vacancies, the strong correlation effect in DFT + U drives a pseudogap ground state at the Fermi energy, similarly as the experimental photo-emission spectra; however, the variation of the DFT + U electronic structure depending on the surface termination becomes weaker compared to those obtained in DFT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Thermodynamics and kinetics of H adsorption and intercalation for graphene on 6 H -SiC(0001) from first-principles calculations

Previous experimental observations for H intercalation under graphene on SiC surfaces motivate the clarification of configuration stabilities and kinetic processes related to intercalation. From first-principles density-functional-theory calculations, we analyze H adsorption and intercalation for graphene on a 6H-SiC(0001) surface, where the system includes two single-atom-thick graphene layers: the top-layer graphene (TLG) and the underling buffer-layer graphene (BLG) above the terminal Si layer. Our chemical potential analysis shows that in the low-H coverage regime (described by a single H atom within a sufficiently large supercell), intercalation into the gallery between TLG and BLG or into the gallery underneath BLG is more favorable thermodynamically than adsorption on top of TLG. However, intercalation into the gallery between TLG and BLG is most favorable. We obtain energy barriers of about 1.3 and 2.3 eV for a H atom diffusing on and under TLG, respectively. From an additional analysis of the energy landscape in the vicinity of a step on the TLG, we assess how readily one guest H atom on the TLG terrace can directly penetrate the TLG into the gallery between TLG and BLG versus crossing a TLG step to access the gallery. Finally, we also perform density functional theory calculations for higher H coverages revealing a shift in favorability to intercalation of H underneath BLG and characterizing the variation with H coverage in interlayer spacings.

36 MATERIALS SCIENCE↗
DOE OSTI2025

When to vaccinate for seasonal influenza: check the peak forecast

Background Seasonal influenza infects 5-20% of people every year in the United States, resulting in hospitalizations, deaths, and adverse economic impacts. To mitigate these impacts, influenza vaccines are developed and distributed annually; however, growing evidence suggests that vaccine effectiveness (VE) wanes over the course of a flu season. Delaying influenza vaccination for older adults has attracted attention as a potential public health strategy. However, given the uncertainties in seasonal peak, vaccine effectiveness, and waning rates, postponing vaccination could also lead to increased morbidity, motivating an evaluation of a range of potential scenarios. The aim of this study was to investigate favorable age group-specific vaccination schedules that could lead to the greatest disease burden reduction. Methods We systematically investigated a broad range of vaccination start times for five age groups under six combinations of initial effectiveness and waning rates, based on influenza cases and vaccine uptake data from 10 influenza seasons. We defined the most favorable vaccination schedule as the one that resulted in the greatest reduction in disease burden. Results In scenarios with fast waning, all age groups benefit from delaying vaccination regardless of initial VE and peak timing. In scenarios with slower waning, results are mixed. For the ≥65 group, high initial VE and slow waning suggests that in early-peaking seasons, early vaccination most effectively reduces disease burden, while in late-peaking seasons delaying vaccination is most effective. For the ≥65 group in medium and low initial VE, and slow waning scenarios, delaying vaccination appears to prevent the greatest number of cases, regardless of whether the season peaks early or late. Conclusion The most favorable vaccination schedule is sensitive to changes in initial VE, waning rate, and peak timing. Given estimates of these quantities from statistical and immunological models and observations, our methods can inform vaccination recommendations in order to most effectively reduce the annual disease burden caused by seasonal influenza. Specifically, accurate peak timing forecasts for the upcoming season have the potential to guide decisions on when to vaccinate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

First-Principles Study of Tritium Trapping by Point Defects in Fe-Al Aluminide Coating Phases

Density functional theory simulations have been carried out to investigate the potential for tritium trapping by metal vacancies in five different Fe-Al aluminide coating phases. It was found that tritiation of Fe and Ni vacancies is generally less favorable than the tritiation of Al vacancies. However, for the first tritiation, a trend in the defect formation energy can be obtained such that metal defects in the Fe 2 Al x family of materials (i.e., Fe 2 Al 4 , Fe 2 Al 5 , and Fe 2 Al 6 ) trap tritium species more favorably than metal vacancies in Fe 4 Al 13 and FeNiAl 5 . Further investigations using ab initio thermodynamics calculations confirmed that trend for a range of tritium partial pressure at a temperature of 700 K. Especially, it was shown that the energy difference between tritiated and non-tritiated metal vacancies is smaller and more favorable for the Fe 2 Al x family, followed by Fe 4 Al 13 , and FeNiAl 5 . While this study shows that tritium interacts differently in the various Fe-Al aluminide phases, it also suggests that tritium trapping and retention could be more efficient if metal defects are present in some Fe-Al phases.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Origin of Life on Mars: Suitability and Opportunities

Although the habitability of early Mars is now well established, its suitability for conditions favorable to an independent origin of life (OoL) has been less certain. With continued exploration, evidence has mounted for a widespread diversity of physical and chemical conditions on Mars that mimic those variously hypothesized as settings in which life first arose on Earth. Mars has also provided water, energy sources, CHNOPS elements, critical catalytic transition metal elements, as well as B, Mg, Ca, Na and K, all of which are elements associated with life as we know it. With its highly favorable sulfur abundance and land/ocean ratio, early wet Mars remains a prime candidate for its own OoL, in many respects superior to Earth. The relatively well-preserved ancient surface of planet Mars helps inform the range of possible analogous conditions during the now-obliterated history of early Earth. Continued exploration of Mars also contributes to the understanding of the opportunities for settings enabling an OoL on exoplanets. Favoring geochemical sediment samples for eventual return to Earth will enhance assessments of the likelihood of a Martian OoL.

transition elements↗
DOE OSTI2024

Geothermal Play Fairway Analysis of Low-Temperature Resources for Sedimentary Basin Geothermal Play Types: An Example in the Denver Basin

This project is part of a nationwide effort to highlight the advantages of incorporating low-temperature geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). The initiative aims to hasten the nation's decarbonization process by exploring the potential for using low-temperature geothermal resources (< 150 Degrees Celsius) in selected sedimentary basins that have several population centers. The Play Fairway Analysis (PFA) techniques were modified from earlier studies of sedimentary basin geothermal play types (SBGPTs) that assessed the viability of low-temperature resources. The decision-making process for leveraging low-temperature geothermal resources for GDU and CHP applications is complex and considers a variety of factors, including geological, economic, and risk criteria. This study covers workflows, relevant datasets, python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. The proposed geothermal PFA approach for low-temperature geothermal resources includes: (1) identifying available relevant data and grouping data sets into PFA criteria (e.g., geological, economic, and risk criteria); (2) analyzing data gaps enable future focalized exploration; (3) performing uncertainty quantification; (4) weighting relevant data; (5) developing favorability and common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection. This project will facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Low-Temperature Geothermal Play Fairway Analysis for the Denver Basin: Preprint

This project is part of a national initiative to showcase the benefits of incorporating low-temperature geothermal resource assessment into the deployment of geothermal heating and cooling (GHC), combined heat and power (CHP), and geothermal direct use (GDU) technologies. The initiative was established to accelerate the country's decarbonization efforts by identifying potential for low-temperature geothermal resource utilization (< 150 Degrees Celsius, i.e., GHC, CHP, and GDU) in selected sedimentary basins with numerous population centers. The Play Fairway Analysis (PFA) methodologies in this study were adapted from previous PFA investigations of sedimentary basin geothermal play types (SBGPTs) that evaluated the potential for low-temperature resources (< 150 Degrees Celsius). Workflows, relevant datasets, python code, common and composite geological criteria maps are utilized to develop low-temperature geothermal resource favorability maps for the Denver Basin, a sedimentary basin spanning Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. To facilitate future assessment of low-temperature geothermal resources in SBGPTs, this project provides PFA workflows, data, tools, and favorability maps that will ultimately support the utilization of low-temperature geothermal resources in sedimentary basins.

Denver Basin↗
DOE OSTI2025

Low-Temperature Geothermal Play Fairway Analysis for the Denver Basin

This project is part of a national initiative to showcase the benefits of incorporating low-temperature geothermal resource assessment into the deployment of geothermal heating, combined heat and power (CHP), and geothermal direct-use (GDU) technologies. The initiative was established to accelerate the country's decarbonization efforts by identifying potential for low-temperature geothermal resource utilization (<150 degrees C, e.g., CHP and GDU) in selected sedimentary basins with numerous population centers. The play fairway analysis (PFA) methodologies in this study were adapted from previous PFA investigations of sedimentary basin geothermal play types (SBGPTs) that evaluated the potential for low-temperature resources (<150 degrees C). Workflows, relevant datasets, a new Python library, and common and composite geological criteria maps are utilized to develop low-temperature geothermal resource favorability maps for the Denver Basin, a sedimentary basin spanning Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. To facilitate future assessment of low-temperature geothermal resources in SBGPTs, this project provides PFA workflows, data, tools, and favorability maps that will ultimately support the utilization of low-temperature geothermal resources in sedimentary basins.

combined heat and power↗
DOE OSTI2024

Environmental and economic analyses of chemical recycling via dissolution of waste polyethylene terephthalate

Globally, more than 1000 organizations and 175 nations are facing the plastic waste problem and have realized the need to transition from “linear-to-circular” economy of plastics. While the current mechanical recycling technologies for plastics are struggling to increase the U.S. plastic recycling rates beyond 9%, chemical recycling technologies become important complementary technologies to the predominant mechanical recycling that are needed to realize the circular economy in plastics supply chains. Dissolution is one such chemical recycling technology that can recycle waste plastic back into high-quality virgin grade plastic. However, the environmental and economic impacts of chemical recycling of waste polyethylene terephthalate (PET) via dissolution technology using a green solvent are unknown. Our study evaluated environmental metrics such as greenhouse gas (GHG) emissions and cumulative energy demand, and economic metrics such as net present value (NPV), minimum selling price, payback period, return on investment, and discounted internal rate of return for three dissolution processes with polymer recovery via anti-solvent, evaporation, and cooling precipitation techniques. The dissolution process with evaporation technique was the most economically favorable, whereas that with cooling technique was the most environmentally favorable. The anti-solvent approach had low economic performance and the highest environmental impacts. The NPV for all of these technologies ranged from $2.67 MM to $10.93 MM for a capacity of 8,400 MT/year and was found to be the highest for dissolution with evaporation approach and the least for anti-solvent approach. The cradle-to-gate GHG emissions and energy demand for PET dissolution processes ranged from 1.33-3.77 kg CO2-eq/kg of chemically recycled (CR) PET and18.9-56.1 MJ/kg of CR-PET, respectively. These economic and environmental metrics will be helpful in evaluating the sustainability of circular PET supply chains in the U.S.

09 BIOMASS FUELS↗
DOE OSTI2023

Highly Tunable Syngas Product Ratios Enabled by Novel Nanoscale Hybrid Electrolytes Designed for Combined CO 2 Capture and Electrochemical Conversion

Coupling renewable energy with the electrochemical conversion of CO 2 to chemicals and fuels has been proposed as a strategy to achieve a new circular carbon economy and help mitigate the effects of anthropogenic CO 2 emissions. Liquid-like Nanoparticle Organic Hybrid Materials (NOHMs) are composed of polymers tethered to nanoparticles and are previously explored as CO 2 capture materials and electrolyte additives. Here, in this study, two types of aqueous NOHM-based electrolytes are prepared to explore the effect of CO 2 binding energy (i.e., chemisorption versus physisorption) on CO 2 electroreduction over a silver nanoparticle catalyst for syngas production. Poly(ethylenimine) (PEI) and Jeffamine M2070 (HPE) are ionically tethered to SiO 2 nanoparticles to form the amine-containing NOHM-I-PEI and ether-containing NOHM-I-HPE, respectively. At less negative cathode potentials, PEI and NOHM-I-PEI-based electrolytes produce CO at higher rates than 0.1 molal. KHCO 3 due to favorable catalyst-electrolyte interactions. Whereas at more negative potentials, H 2 production is favored because of the carbamate electrochemical inactivity. Conversely, HPE and NOHM-I-HPE-based electrolytes display poor CO 2 reduction performance at less negative potentials. At more negative potentials, their performance approached that of 0.1 molal. KHCO 3 , highlighting how the polymer functional groups of NOHMs can be strategically selected to produce value-added products from CO 2 with highly tunable compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Zero-Valent Palladium Single-Atoms Catalysts Confined in Black Phosphorus for Efficient Semi-Hydrogenation

Single-atom catalysts (SACs) represent a new frontier in heterogeneous catalysis due to their remarkable catalytic properties and maximized atomic utilization. However, single atoms often bond to the support with polarized electron density and thus exhibit a high valence state, limiting their catalytic scopes in many chemical transformations. In this study, it is demonstrated that 2D black phosphorus (BP) acts as giant phosphorus (P) ligand to confine a high density of single atoms (e.g., Pd 1 , Pt 1 ) via atomic layer deposition. Unlike other 2D materials, BP with relatively low electronegativity and buckled structure favors the strong confinement of robust zero-valent palladium SACs in the vacancy site. Metallic Pd 1 /BP SAC shows a highly selective semi-hydrogenation of phenylacetylene toward styrene, distinct from metallic Pd nanoparticles that facilitate the formation of fully hydrogenated products. Density functional theory calculations reveal that Pd atom forms covalent-like bonding with adjacent P atoms, wherein H atoms tend to adsorb, aiding the dissociative adsorption of H 2 . Zero-valent Pd in the confined space favors a larger energy gain for the synthesis of partially hydrogenated product over the fully hydrogenated one. This work provides a new route toward the synthesis of zero-valent SACs on BP for organic transformations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tethered Small-Molecule Acceptors Simultaneously Enhance the Efficiency and Stability of Polymer Solar Cells

For polymer solar cells (PSCs), the mixture of polymer donors and small-molecule acceptors (SMAs) is fine-tuned to realize a favorable kinetically trapped morphology and thus a commercially viable device efficiency. However, the thermodynamic relaxation of the mixed domains within the blend raises concerns related to the long-term operational stability of the devices, especially in the record-holding Y-series SMAs. Here, a new class of dimeric Y6-based SMAs tethered with differential flexible spacers is reported to regulate their aggregation and relaxation behavior. In their polymer blends with PM6, it is found that they favor an improved structural order relative to that of Y6 counterpart. Most importantly, the tethered SMAs show large glass transition temperatures to suppress the thermodynamic relaxation in mixed domains. For the high-performing dimeric blend, an unprecedented open circuit voltage of 0.87 V is realized with a conversion efficiency of 17.85%, while those of regular Y6-base devices only reach 0.84 V and 16.93%, respectively. Most importantly, the dimer-based device possesses substantially reduced burn-in efficiency loss, retaining more than 80% of the initial efficiency after operating at the maximum power point under continuous illumination for 700 h. In conclusion, the tethering approach provides a new direction to develop PSCs with high efficiency and excellent operating stability.

14 SOLAR ENERGY↗
DOE OSTI2025

How the Arrangement of Platinum Atoms on Ruthenium Nanoparticles Improves Hydrogen Evolution Activity

The platinum‐ruthenium (PtRu) system is highly active for hydrogen evolution reaction (HER) in alkaline media with both Pt and Ru playing active roles in the water dissociation step that generates adsorbed hydrogen atoms. Precise control of the arrangement of Pt atoms on Ru nanoparticles can maximize the Pt‐Ru sites for water dissociation and Pt‐Pt sites for hydrogen production and can considerably improve HER catalytic performance. By directing the growth and distribution of Pt on Ru hourglass nanoparticles, the arrangement of Pt on Ru is controlled into forming Pt islands, small Pt clusters, and strings of a few Pt atoms. Calculations show that the unique atomic string arrangements of Pt on Ru is the thermodynamically favorable configuration. Additionally, these strings have a favorable combination of Pt‐Ru and Pt‐Pt sites, making the Pt‐string on Ru the most active catalyst with a more than fivefold increase in turnover frequency for alkaline HER compared to the Pt‐island on Ru catalyst. The results show how controlling the Pt atomic arrangement on Ru nanoparticle surfaces for the tuning of Pt‐Pt and Pt‐Ru neighboring sites can direct toward a more efficient HER mechanism and thereby significantly enhancing HER performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Understanding initial zeolite oligomerization steps with first principles calculations

Zeolites are porous aluminosilicate materials that find various applications in the chemical industry in separations, catalysis, ion exchange, and so forth. However, despite their widespread use, the reaction mechanisms occurring during zeolite growth are still unclear. In the study, we use density functional theory calculations to gain insights into the thermodynamics of oligomerization, which constitute the initial steps of zeolite growth. By taking into consideration solvent and temperature effects, our results demonstrate that the growth of aluminosilicate systems is significantly more exothermic than their pure silicate counterparts. Under pH neutral conditions, water prefers to dissociate on the early-growth-stage aluminosilicate complexes rather than desorb, thus generating potential Brønsted acid sites on the oligomers. Additionally, (alumino)silicate growth pathways are evaluated in the presence of Na + cation, as well as the Ca 2+ cation for the pure silicate pathway. The presence of cations increases the exothermicity of growth, with Ca 2+ exhibiting the most energetically favorable growth environment for the silicate systems. Importantly, we demonstrate through reaction extent analysis that the presence of cations modulates the speciation of the formed oligomers, with Na + favoring linear species in addition to the generally preferred cyclic ones. Overall, this work provides a fundamental understanding of the thermodynamics of complex reaction paths that occur during early stages of zeolite growth and suggests that the initial growth steps can have significant impact on the final zeolite structure.

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

Ethylene Dehydroaromatization over Ga‐ZSM‐5 Catalysts: Nature and Role of Gallium Speciation

Abstract Bifunctional catalysis in zeolites possessing both Brønsted and Lewis acid sites offers unique opportunities to tailor shape selectivity and enhance catalyst performance. Here, we examine the impact of framework and extra‐framework gallium species on enriched aromatics production in zeolite ZSM‐5. We compare three distinct methods of preparing Ga‐ZSM‐5 and reveal direct (single step) synthesis leads to optimal catalysts compared to post‐synthesis methods. Using a combination of state‐of‐the‐art characterization, catalyst testing, and density functional theory calculations, we show that Ga Lewis acid sites strongly favor aromatization. Our findings also suggest Ga(framework)–Ga(extra‐framework) pairings, which can only be achieved in materials prepared by direct synthesis, are the most energetically favorable sites for reaction pathways leading to aromatics. Calculated acid site exchange energies between extra‐framework Ga at framework sites comprised of either Al or Ga reveal a site‐specific preference for stabilizing Lewis acids, which is qualitatively consistent with experimental measurements. These findings indicate the possibility of tailoring Lewis acid siting by the placement of Ga heteroatoms at distinct tetrahedral sites in the zeolite framework, which can have a marked impact on catalyst performance relative to conventional H‐ZSM‐5.

Zhou, Yunwen↗
DOE OSTI2021

Thermal Unequilibrium of PdSn Intermetallic Nanocatalysts: From In Situ Tailored Synthesis to Unexpected Hydrogenation Selectivity

Abstract Effective control on chemoselectivity in the catalytic hydrogenation of C=O over C=C bonds is uncommon with Pd‐based catalysts because of the favored adsorption of C=C bonds on Pd surface. Here we report a unique orthorhombic PdSn intermetallic phase with unprecedented chemoselectivity toward C=O hydrogenation. We observed the formation and metastability of this PdSn phase in situ. During a natural cooling process, the PdSn nanoparticles readily revert to the favored Pd 3 Sn 2 phase. Instead, using a thermal quenching method, we prepared a pure‐phase PdSn nanocatalyst. PdSn shows an >96 % selectivity toward hydrogenating C=O bonds of various α,β‐unsaturated aldehydes, highest in reported Pd‐based catalysts. Further study suggests that efficient quenching prevents the reversion from PdSn‐ to Pd 3 Sn 2 ‐structured surface, the key to the desired catalytic performance. Density functional theory calculations and analysis of reaction kinetics provide an explanation for the observed high selectivity.

Chen, Minda↗