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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MOF-enabled confinement and related effects for chemical catalyst presentation and utilization

A defining characteristic of nearly all catalytically functional MOFs is uniform, molecular-scale porosity. MOF pores, linkers and nodes that define them, help regulate reactant and product transport, catalyst siting, catalyst accessibility, catalyst stability, catalyst activity, co-catalyst proximity, composition of the chemical environment at and beyond the catalytic active site, chemical intermediate and transition-state conformations, thermodynamic affinity of molecular guests for MOF interior sites, framework charge and density of charge-compensating ions, pore hydrophobicity/hydrophilicity, pore and channel rigidity vs. flexibility, and other features and properties. Collectively and individually, these properties help define overall catalyst functional behaviour. Here, this review focuses on how porous, catalyst-containing MOFs capitalize on molecular-scale confinement, containment, isolation, environment modulation, energy delivery, and mobility to accomplish desired chemical transformations with potentially superior selectivity or other efficacy, especially in comparison to catalysts in homogeneous solution environments.

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

The evolving role of geothermal energy for decarbonizing the United States

Geothermal energy is often referred to as a niche technology that is too localized, too small or too expensive to make much of a difference in how renewable energy will be supplied in a fully decarbonized future. As a result, geothermal energy has been undervalued in terms of what it could provide to complement, rather than compete with, electricity generation from wind, solar photovoltaic, concentrating solar power and other renewables. Geothermal energy systems are fully dispatchable and can provide baseload or load-following electric power or heat suitable for a wide range of applications including supplying district heating for communities and cities, and heating and cooling of individual buildings. The focus of our study is on the potential of utilizing geothermal energy for providing heat for buildings and industry at lower temperatures, a substitute for the combustion of fossil fuels. Because heating represents about 20% (20 EJ per year) of the annual primary energy consumption in the U.S.—with most of it coming from burning natural gas, oil and/or propane in furnaces—deploying geothermal heating on a national scale could have a significant impact on lowering carbon emissions. In heating-dominated states in the U.S. Northern Tier, heating often is among the largest contributors to the state's carbon footprint. This review begins with a discussion of the motivation and rationale behind considering geothermal as a key low-carbon heating option for the U.S. The study summarizes the U.S. geothermal resource and describes the applications and main engineering components of using geothermal energy for heating and cooling, electric power generation, and co-generation using district heating, geothermal heat pumps, and power conversion with steam flashing and organic Rankine plants. Environmental benefits and impacts are described. An extensive discussion of geologic and thermal-hydraulic aspects of the subsurface is included in the review because of their critical role in determining reservoir designs at specific sites to ensure sufficient productivity that is both safe and economically viable. Models for estimating levelized costs of district heating are used to show how costs are affected by reservoir performance, infrastructure capital costs, and financial parameters. Here, the review concludes with an assessment of technical subsurface issues associated with reservoir performance and the economic requirements for providing geothermal heating in district heating systems at a sufficient scale to have an impact on decarbonizing the U.S.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Separation of alkane and alkene mixtures by metal–organic frameworks

The separation of alkane/alkene gas mixtures represents an important yet challenging process in the petrochemical industry to produce valuable chemical feedstocks with sufficiently high purity. These molecules have similar physical properties, making their separation difficult and capital-intensive. The current separation and purification technology relies largely on heat-driven distillations with a huge unit composed of hundreds of trays. Adsorptive separation using porous solids is capable of accomplishing the purification under ambient conditions, offering potential energy and environmental benefits. In particular, metal–organic frameworks (MOFs) hold enormous promise for this separation process in light of their highly tunable pore shape, pore size, and pore surface functionality. In this review article, we provide a comprehensive account of metal–organic frameworks that have been investigated for the separation of alkanes and alkenes with a focus on C 2 –C 3 hydrocarbons. Here, the material design rationale, separation mechanisms, and structure–property relations are highlighted. Finally, the existing challenges and possible design strategies for desirable materials are also discussed.

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

Microporous metal–organic frameworks for the purification of propylene

Separation of propylene from its analogous hydrocarbons such as propane is of great importance in the petrochemical industry to produce valuable chemical feedstocks with desired purity. However, the well-established method currently used for industrial propane/propylene separation is energy intensive. It involves repeated cycling in the cryogenic and high-pressure distillation process and requires multiple columns and high reflux ratios because of the very similar physical properties of the two species. Thus, it is identified as one of the most capital- and energy-intensive processes. Adsorptive separation based on porous adsorbents is regarded as an alternative energy-efficient technology to replace or supplement the traditional heat-driven cryogenic distillation processes. In this context, metal–organic frameworks (MOFs) have emerged as the most promising candidates for propane/propylene separation, taking into consideration their unique tunability with respect to pore geometry and pore functionality. In this highlight, we summarize the latest advancement in developing MOFs as physisorbents for the separation and purification of propylene from propane, with a focus on those that demonstrate selective molecular exclusion and propane-selective adsorption. We discuss the adsorption preferences related to the material design and separation mechanisms, and review the existing challenges. Lastly, we offer our perspectives on various strategies for the future design of MOFs that hold true potential for propylene purification under industrial settings.

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

Techno-economic and life cycle analysis of bio-hydrogen production using bio-based waste streams through the integration of dark fermentation and microbial electrolysis

Hydrogen derived from bio-based sources, or biohydrogen (bioH 2 ), has the potential to reduce GHG emissions from industrial and transportation sectors, owing to the low carbon footprint and myriad applications like refinery operation, ammonia production, steel production, fuel cell, etc. To evaluate the commercialization potential of bioH 2 production, we modeled bioH 2 production and conducted techno-economic analysis (TEA) and life cycle analysis (LCA) of two facilities producing 50 metric tonnes of bioH 2 per day from cheese whey (CW) and solid food waste (SFW) through the integration of dark fermentation (DF) and microbial electrolysis cell (MEC) technologies. LCA results showed that CW and SFW can produce carbon-negative bioH 2 , with emissions of −8.6 and −8.0 kg GHG kg −1 bioH 2 with carbon sequestration and renewable electricity resources, respectively, making bioH 2 potentially eligible for a tax credit of $\$3$ kg −1 H 2 based on provision 45 V of the U.S. Inflation Reduction Act (IRA). In this study, bioH 2 production treats waste streams to generate fresh water, thus, potentially can receive waste water treatment fee that varies with regions. The MEC capital cost dominates the bioH 2 cost, which is mainly determined by current density. With a current density of 20 A m −2 , the production cost for CW input varied between $\$17$ and $\$24$ kg −1 bioH 2 , while that for SFW input ranged from $\$29$ to $\$30$ kg −1 bioH 2 under different operating conditions, considering the 45 V tax credit, waste water treatment fee and production revenue. If the current density increases to 100 A m −2 , the bioH 2 cost decreases to a range of $\$4.0$–$\$6.9$ for CW and $\$5$–$\$6$ for SFW scenarios. This study also shows that low-cost bioH 2 can be produced using CW waste stream as feedstock.

Ganguly, Arna [Argonne National Laboratory (ANL), ↗
DOE OSTI2024

Biomimetic mineralization of positively charged silica nanoparticles templated by thermoresponsive protein micelles: applications to electrostatic assembly of hierarchical and composite superstructures

High information content building blocks offer a path toward the construction of precision materials by supporting the organization and reconfiguration of organic and inorganic components through engineered functions. Here, we combine thermoresponsiveness with biomimetic mineralization by fusing the Car9 silica-binding dodecapeptide to the C-terminus of the (VPGVG) 54 elastin-like polypeptide (ELP). Using small angle X-ray scattering, we show that the short Car9 cationic block is sufficient to promote the conversion of disordered unimers into 30 nm micelles comprising about 150 proteins, 5 °C above the transition temperature of the ELP. While both species catalyze self-limiting silica precipitation, micelles template the mineralization of highly monodisperse (62 nm) nanoparticles, while unimers yield larger polydisperse species. Strikingly, and unlike traditional synthetic silica, these particles exhibit a positive surface charge, likely due to cationic Car9 sidechains projecting from their surface. Capitalizing on the high monodispersity and positive charge of the micelle-templated products, we use smaller silica and gold particles bearing a native negative charge to create a variety of superstructures via electrostatic co-assembly. Furthermore, this simple biomimetic route to positively charged silica eliminates the need for multiple precursors or surface modifications and enables the rapid creation of single-material and composite architectures in which components of different sizes or compositions are well dispersed and integrated.

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

Broadband cross polarization for ultra-wideline magic-angle spinning NMR

Over the past decade, there has been a sustained interest in using frequency-swept (FS) pulses for the efficient acquisition of wideline and ultra-wideline (UW) NMR powder patterns. Such experiments are typically conducted under static conditions, employing both direct- and indirect-excitation methods (i.e., WCPMG and BRAIN-CP/WCPMG, respectively). Recently, Koppe et al. demonstrated that the WCPMG pulse sequence can be used to efficiently acquire wideline and UW NMR spectra with spinning sideband (SSB) manifolds under magic-angle spinning (MAS) conditions, capitalizing on the increased signal-to-noise ratios (SNR) afforded by MAS. To date, there have been only a few instances of broadband cross-polarization (CP) experiments using FS pulses under MAS conditions and no applications to systems exhibiting wideline and/or ultra-wideline powder patterns, despite the clear advantages these experiments could offer. Herein, we demonstrate that FS pulses selectively applied to a single sideband of the S spin can be used for efficient 1 H-S polarization transfer to S = 1/2 nuclides with large anisotropic chemical shift interactions at slow to moderate MAS rates. The Hartmann–Hahn matching conditions in BRAIN-CP/WCPMG-MAS experiments bear similarity to those of standard CP sequences, yet operate over UW frequency ranges and only require low-amplitude RF pulses on the S channel. Crucial to the success of the BRAIN-CP/WCPMG-MAS experiment is careful calibration of the RF amplitude, transmitter offset, and effective frequency sweep of the FS pulse applied to the S spins at a given MAS rate. Thus, by means of numerical simulations and experimental testing, we provide recommendations for the parameterization and setup of BRAIN-CP/WCPMG-MAS experiments for their most efficient use. Results showcasing the capability of the BRAIN-CP/WCPMG-MAS pulse sequence are presented, including applications to 119 Sn, 195 Pt, and 103 Rh NMR.

Kimball, James J. [Florida State University, Talla↗
DOE OSTI2025

Near-cryogenic direct air capture using adsorbents

Direct air capture (DAC) of CO 2 is a key component in the portfolio of negative emissions technologies for mitigating global warming. However, even with the most potent amine sorbents, large-scale DAC deployment remains limited by high energy and capital costs. Recently, adsorbents relying on weak interactions with CO 2 have emerged as a potential alternative, thanks to their rapid adsorption kinetics and superior long-term stability, particularly under sub-ambient conditions (∼253 K). Despite these advantages, their use is hindered by the need for a water-removal process, location-specific constraints, and insufficient working capacity even in cold climates. In this study, we hypothesized that further reducing the adsorption temperature to a near-cryogenic range (160–220 K) could enable cost-effective DAC by utilizing the full potential of physisorbents. We primarily consider integrating DAC with a relatively untapped source of cold energy—liquified natural gas (LNG) regasification—to perform near-cryogenic DAC. From large-scale molecular simulations, Zeolite 13X and CALF-20 were identified as promising candidates. These materials were subsequently examined through experiments, including breakthrough analyses at 195 K. Their high CO 2 sorption capacity (4.5–5.5 mmol g −1 ), combined with a low desorption enthalpy and robust long-term stability, led to a threefold reduction in the levelized cost of capture (down to 68.2 USD per tonne CO 2 ). Estimates of the global LNG regasification resource suggest that LNG–DAC coupling could potentially enable the capture of 103–142 megatonnes of CO 2 annually as of 2050.

Kim, Seo-Yul [Georgia Institute of Technology, Atl↗
DOE OSTI2026

Techno-Economic Analysis of Repurposing Natural Gas Transmission Pipeline Networks to Accommodate Hydrogen Blends

Blending hydrogen into natural gas infrastructure could supplement natural gas supply and increase resilience for applications such as ammonia production, peaking and load-following power plants, and heating. The United States has an extensive network of natural gas pipelines, but the feasibility of employing this infrastructure to transport hydrogen is unclear. We analyze the costs associated with repurposing three distinct natural gas transmission pipelines in different locations within the United States to carry blends of hydrogen up to 100% via three different pipeline network modification methods and compare against the cost of building a new dedicated hydrogen pipeline. We conduct a sensitivity analysis on the hoop stress limit of the existing pipe, techno-economic parameters, emissions, and relative capacity. The results show that the capital costs required to upgrade a pipeline can vary from tens of millions to billions of dollars depending on the length and capacity of the existing pipeline section, whether the existing pipeline already operates at or below its maximum allowable operating pressure, whether future demand is expected to increase or decrease, the network modification method selected, and pipe material costs. The delivered cost of energy to end users is impacted less by the levelized cost of transporting hydrogen blends than by the cost of the natural gas and hydrogen fuels being transported. The emissions impact of blending hydrogen into natural gas transmission networks scales proportionally with the amount of energy displaced with low-emission hydrogen (such as from natural gas with carbon capture and sequestration or electrolysis powered by nuclear, renewable, or geothermal electricity), therefore low blend ratios (e.g., < 20% vol. hydrogen) will result in low emissions impacts. Factors such as permitting and right-of-way costs, the proximity of the pipeline to hydrogen demand and production, and the compatibility of and/or retrofitting costs of end-use gas-fueled technologies will likely be greater drivers in determining whether converting a particular natural gas pipeline to carry hydrogen makes economic sense.

08 HYDROGEN↗
DOE OSTI2020

Extreme Compression for Large Scale Data Store

For the last 5 years Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom line outcome would be to provide a state-of-the-art compression algorithm that surpasses those currently available in the ROOT framework, with the purpose of enabling substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4.In this contribution, we will present our concepts of “functionally lossless compression”, have a glance at examples and achievements in other communities, present the results and outcome of our current, ongoing R&D, as well as present a high-level view of our plan to move forward with a ROOT implementation that would deliver a basic solution readily integrated into HENP applications. As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Automated Electric Vehicle Fleet Operations for On-Demand Service: Challenges and Opportunities

Automated/autonomous vehicle fleet operations within automated mobility districts have been studied over the past five years by the National Renewable Energy Laboratory, a US Department of Energy federally funded research and development center. This paper extends the analysis in this third phase of research underway to include considerations for electric vehicle operations and charging within a fleet of right-sized automated vehicles providing on-demand public mobility services. The current focus of research is on the operational complexities and associated challenges for automated/autonomous vehicles employing electric drivetrains and the resultant need for an efficient battery charging process while vehicles are operating in an "on-demand" mode of service. The blossoming of microtransit with shared-ride and point-to-point dispatching of each vehicle instills complex operations, with multiple mobility-on-demand transit operating sites being deployed, studied, and analyzed across North America. As a starting point, the authors' experience over the past 20 years with the analysis of automated transit network systems operating on and within dedicated and protected transitways provides initial insights into the system-level operational implications for maintaining a sufficient battery charge for a fleet of automated vehicles. Lessons learned through the prior analyses of automated transit network systems operating in on-demand service are identified, along with the capital cost implications for the requisite operating fleet size and charging station infrastructure for various approaches. These costs are summarized in juxtaposition with the benefits of realizing the higher goals of reducing environmental impacts and energy use within automated mobility districts as automated/autonomous vehicle technology matures. Finally, the discussion addresses key aspects of battery-electric propulsion for managed fleets in fully automated operation that will be studied as the third phase of research continues.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Pulsed RF schemes for tearing mode stabilization

The RF stabilization of tearing modes with current condensation has the potential to increase stabilization efficiency and loosen power localization requirements. Such benefits stem from the cooperative feedback between the RF deposition and resulting island temperature perturbation governed by diffusion. A self consistent treatment of the damping of an rf ray as it traverses the island shows that low damping scenarios can require unfavorably high powers to overcome initial power leakage and effectively capitalize on the nonlinear effect. In this work it is demonstrated that for such regimes,modulated stabilization schemes can achieve significant improvements in heating and current drive contributions to stabilization for the same average power as a continuous wave scheme. The impact of modulation frequency and duty cycle on the performance is explored, the results of which suggest modulation strategies in which the pulsing periods are kept on the order of a diffusive time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Materials representation and transfer learning for multi-property prediction

The adoption of machine learning in materials science has rapidly transformed materials property prediction. Hurdles limiting full capitalization of recent advancements in machine learning include the limited development of methods to learn the underlying interactions of multiple elements as well as the relationships among multiple properties to facilitate property prediction in new composition spaces. To address these issues, we introduce the Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP) framework that seamlessly integrates: (i) prediction using only a material's composition, (ii) learning and exploitation of correlations among target properties in multi-target regression, and (iii) leveraging training data from tangential domains via generative transfer learning. The model is demonstrated for prediction of spectral optical absorption of complex metal oxides spanning 69 three-cation metal oxide composition spaces. H-CLMP accurately predicts non-linear composition-property relationships in composition spaces for which no training data are available, which broadens the purview of machine learning to the discovery of materials with exceptional properties. This achievement results from the principled integration of latent embedding learning, property correlation learning, generative transfer learning, and attention models. The best performance is obtained using H-CLMP with transfer learning [H-CLMP(T)] wherein a generative adversarial network is trained on computational density of states data and deployed in the target domain to augment prediction of optical absorption from composition. H-CLMP(T) aggregates multiple knowledge sources with a framework that is well suited for multi-target regression across the physical sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Techno-Economic Analysis of CSP Incorporating sCO2 Brayton Power Cycles: Trade-Off Between Cost and Performance

Concentrating solar power (CSP) plants, thanks to the implementation of cost-competitive thermal energy storage, represent a dispatchable zero-emission alternative to traditional fossil fuel power plants. Next generation solar towers are expected to adopt high temperature receivers (>700 degrees C) coupled to sCO2-based power blocks, which optimal design is generally pushed towards the maximum cycle efficiency, often neglecting the economic impact with the justification that the main share of the capital cost is represented by the heliostat field. As result, the scientific literature lacks in comprehensive studies on techno-economic evaluation of CSP+sCO2 power plants addressing the important correlation that exists between system cost and performances. This work provides a preliminary techno-economic analysis of a solar power tower comparing four different cycle configurations for the sCO2 power block. Results have been reported on a Pareto front, highlighting the tradeoff between the plant investment cost and the solar-to-electricity plant efficiency. The trends of the optimization variables and cycle results have been reported to give useful insights about proper assumptions for the sCO2 power block design. The recompressed cycle with intercooling resulted as the most promising configuration and it has been further analyzed through a comparison of different solutions on the Pareto front. The cost breakdown of the sCO2 power block has been reported to highlight which components have the greatest impact on the overall plant cost and how they vary along the optimal solutions front. Eventually, the optimization has been repeated introducing a correlation to compute the turbomachinery isentropic efficiencies, to investigate their effect on the techno- economic analysis.

concentrated solar power↗
DOE OSTI2023

A fast, dense Chebyshev solver for electronic structure on GPUs

Matrix diagonalization is almost always involved in computing the density matrix needed in quantum chemistry calculations. In the case of modest matrix sizes (≲4000), performance of traditional dense diagonalization algorithms on modern GPUs is underwhelming compared to the peak performance of these devices. This motivates the exploration of alternative algorithms better suited to these types of architectures. We newly derive, and present in detail, an existing Chebyshev expansion algorithm whose number of required matrix multiplications scales with the square root of the number of terms in the expansion. Focusing on dense matrices of modest size, our implementation on GPUs results in large speed ups when compared to diagonalization. Additionally, we improve upon this existing method by capitalizing on the inherent task parallelism and concurrency in the algorithm. Furthermore, this improvement is implemented on GPUs by using CUDA and HIP streams via the MAGMA library and leads to a significant speed up over the serial-only approach for smaller (≲1000) matrix sizes. Finally, we apply our technique to a model system with a high density of states around the Fermi level, which typically presents significant challenges.

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

An implicit solution for Asay foil trajectories generated by separable, sustained-production ejecta source models

We present a simple implicit solution for the time-dependent trajectory of a thin Asay foil ejecta diagnostic for the general case where the impinging ejecta cloud is generated by a source function characterized by an arbitrary (sustained) time dependence and a time-independent (stationary) particle velocity distribution. In the limit that the source function time dependence becomes a delta function, this solution—which is amenable to rapid numerical calculations of arbitrary accuracy—exactly recovers a previously published solution for the special case of instantaneous ejecta production. We also derive simple expressions for the free-surface arrival (catch-up) time as well as the true ejecta areal mass accumulation on the accelerating foil and place bounds on the level of error incurred when applying instant-production mass solutions to a sustained-production trajectory. We demonstrate these solutions with example calculations for hypothetical source functions spanning a wide range of ejecta production durations, velocity distributions, and temporal behaviors. These calculations demonstrate how the foil trajectory is often insensitive to the temporal dependence of the source function, instead being dominated by the velocity distribution. We quantify this insensitivity using a “compatibility score” metric. Under certain conditions, one may capitalize upon this insensitivity to obtain a good approximation of the second integral of the velocity distribution from the observed foil trajectory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Least-cost targets and avoided fossil fuel capacity in India’s pursuit of renewable energy

India has set aggressive targets to install more than 400 GW of wind and solar electricity generation by 2030, with more than two-thirds of that capacity coming from solar. This paper examines the electricity and carbon mitigation costs to reliably operate India’s grid in 2030 for a variety of wind and solar targets (200 GW to 600 GW) and the most promising options for reducing these costs. We find that systems where solar photovoltaic comprises only 25 to 50% of the total renewable target have the lowest carbon mitigation costs in most scenarios. This result invites a reexamination of India’s proposed solar-majority targets. We also find that, compared to other regions and contrary to prevailing assumptions, meeting high renewable targets will avoid building very few new fossil fuel (coal and natural gas) power plants because of India’s specific weather patterns and need to meet peak electricity demand. However, building 600 GW of renewable capacity, with the majority being wind plants, reduces how often fossil fuel power plants run, and this amount of capacity can hold India’s 2030 emissions below 2018 levels for less than the social cost of carbon. With likely wind and solar cost declines and increases in coal energy costs, balanced or wind-majority high renewable energy systems (600 GW or ≈ 45% share by energy) could result in electricity costs similar to a fossil fuel-dominated system. As an alternative strategy for meeting peak electricity demand, battery storage can avert the need for new fossil fuel capacity but is cost effective only at low capital costs (≈ USD 150 per kWh).

14 SOLAR ENERGY↗
DOE OSTI2020

Facilitating hydrogen atom migration via a dense phase on palladium islands to a surrounding silver surface

Significance The energy efficiency of catalytic processes hinges on achieving high selectivity and activity; bimetallic catalysts have potential to increase both by exploiting different chemical properties of the components. Transport of intermediates between the two metals, for example, transport of hydrogen atoms for selective hydrogenation, is required to capitalize on this bifunctionality. A mechanism for the migration of hydrogen atoms to silver from palladium is demonstrated here. Dihydrogen first dissociates on palladium, then forms a dense hydrogen phase on the palladium island. The dense phase includes weakly bound hydrogen atoms that are nearly isoenergetic with hydrogen on silver, rendering migration nearly energy neutral. The efficiency for hydrogen migration across the palladium−silver is maximized for small ensembles of palladium atoms.

O’Connor, Christopher R.↗