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

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Reformer Fuel Injector

Today's form of jet engine power comes from what is called a gas turbine engine. This engine is on average 14% efficient and emits great quantities of green house gas carbon dioxide and air pollutants, Le. nitrogen oxides and sulfur oxides. The alternate method being researched involves a reformer and a solid oxide fuel cell (SOFC). Reformers are becoming a popular area of research within the industry scale. NASA Glenn Research Center's approach is based on modifying the large aspects of industry reforming processes into a smaller jet fuel reformer. This process must not only be scaled down in size, but also decrease in weight and increase in efficiency. In comparison to today's method, the Jet A fuel reformer will be more efficient as well as reduce the amount of air pollutants discharged. The intent is to develop a 10kW process that can be used to satisfy the needs of commercial jet engines. Presently, commercial jets use Jet-A fuel, which is a kerosene based hydrocarbon fuel. Hydrocarbon fuels cannot be directly fed into a SOFC for the reason that the high temperature causes it to decompose into solid carbon and Hz. A reforming process converts fuel into hydrogen and supplies it to a fuel cell for power, as well as eliminating sulfur compounds. The SOFC produces electricity by converting H2 and CO2. The reformer contains a catalyst which is used to speed up the reaction rate and overall conversion. An outside company will perform a catalyst screening with our baseline Jet-A fuel to determine the most durable catalyst for this application. Our project team is focusing on the overall research of the reforming process. Eventually we will do a component evaluation on the different reformer designs and catalysts. The current status of the project is the completion of buildup in the test rig and check outs on all equipment and electronic signals to our data system. The objective is to test various reformer designs and catalysts in our test rig to determine the most efficient configuration to incorporate into the specific compact jet he1 reformer test rig. Additional information is included in the original extended abstract.

Suder, Jennifer L.↗
DOE OSTI2022

Catlas: an automated framework for catalyst discovery demonstrated for direct syngas conversion

Catalyst discovery is paramount to support access to energy and key chemical feedstocks in a post fossil fuel era. Exhaustive computational searches of large material design spaces using ab initio methods like density functional theory (DFT) are infeasible. We seek to explore large design spaces at relatively low computational cost by leveraging large, generalized, graph-based machine learning (ML) models, which are pretrained and therefore require no upfront data collection or training. We present Catlas, a framework that distributes and automates the generation of adsorbate-surface configurations and ML inference of DFT energies to achieve this goal. Catlas is open source, making ML assisted catalyst screenings easy and available to all. To demonstrate its efficacy, we use Catlas to explore catalyst candidates for the direct conversion of syngas to multi-carbon oxygenates. For this case study, we explore 947 stable/metastable binary, transition metal intermetallics as possible catalyst candidates. On this subset of materials, we are able to predict the adsorption energy of key descriptors, *CO and *OH, with good accuracy (0.16, 0.14 eV MAE, respectively). Using the projected selectivity towards C 2+ oxygenates from an existing microkinetic model, we identified 144 candidate materials. For 10 promising candidates, DFT calculations reveal a good correlation with our assessment using ML. Finally, among the top elemental combinations were Pt–Ti, Pd–V, Ni–Nb, and Ti–Zn, all of which appear unexplored experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Alternative Fuel Research in Fischer-Tropsch Synthesis

NASA Glenn Research Center has recently constructed an Alternative Fuels Laboratory which is solely being used to perform Fischer-Tropsch (F-T) reactor studies, novel catalyst development and thermal stability experiments. Facility systems have demonstrated reliability and consistency for continuous and safe operations in Fischer-Tropsch synthesis. The purpose of this test facility is to conduct bench scale Fischer-Tropsch (F-T) catalyst screening experiments while focusing on reducing energy inputs, reducing CO2 emissions and increasing product yields within the F-T process. Fischer-Tropsch synthesis is considered a gas to liquid process which reacts syn-gas (a gaseous mixture of hydrogen and carbon monoxide), over the surface of a catalyst material which is then converted into liquids of various hydrocarbon chain length and product distributions1. These hydrocarbons can then be further processed into higher quality liquid fuels such as gasoline and diesel. The experiments performed in this laboratory will enable the investigation of F-T reaction kinetics to focus on newly formulated catalysts, improved process conditions and enhanced catalyst activation methods. Currently the facility has the capability of performing three simultaneous reactor screening tests, along with a fourth fixed-bed reactor used solely for cobalt catalyst activation.

Surgenor, Angela D.↗
DOE OSTI2020

Predicting metal–metal interactions. II. Accelerating generalized schemes through physical insights

Operando-computational frameworks that integrate descriptors for catalyst stability within catalyst screening paradigms enable predictions of rates and selectivity on chemically faithful representations of nanoparticles under reaction conditions. These catalyst stability descriptors can be efficiently predicted by density functional theory (DFT)-based models. The alloy stability model, for example, predicts the stability of metal atoms in nanoparticles with site-by-site resolution. In this work, we use physical insights to present accelerated approaches of parameterizing this recently introduced alloy-stability model. These accelerated approaches meld quadratic functions for the energy of metal atoms in terms of the coordination number with linear correlations between model parameters and the cohesive energies of bulk metals. By interpolating across both the coordination number and chemical space, these accelerated approaches shrink the training set size for 12 fcc p- and d-block metals from 204 to as few as 24 DFT calculated total energies without sacrificing the accuracy of our model. We validate the accelerated approaches by predicting adsorption energies of metal atoms on extended surfaces and 147 atom cuboctahedral nanoparticles with mean absolute errors of 0.10 eV and 0.24 eV, respectively. This efficiency boost will enable a rapid and exhaustive exploration of the vast material space of transition metal alloys for catalytic applications.

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

Parallelized Screening of Characterized and DFT-Modeled Bimetallic Colloidal Cocatalysts for Photocatalytic Hydrogen Evolution

Using a newly designed and developed parallelized photoreactor and colorimetric detection method, a large sampling of bimetallic co-catalysts (Pd/Sn, Pd/Mo, Pd/Ru, Pd/Pb, Pd/Ni, Ni/Sn, Mo/Sn and Pt/Sn) for photocatalytic water reduction have been tested in this work. Of these co-catalysts, the combination of palladium and tin showed the highest synergistic behavior and peak hydrogen gas production at a low relative fraction of palladium. The resulting Pd/Sn bimetallic co-catalysts were characterized using high-angle annular dark-field (HAADF) and scanning transmission electron microscopy energy dispersive X-ray spectroscopy (STEM-EDS), and specifically, investigation of the palladium/tin mixture indicated that palladium and tin elements reside within the same particle. The experimental catalytic activity for the palladium/tin mixture was compared to density functional theory-derived energy values associated with the adsorption of hydrogen onto a surface. This comparison demonstrated that the typical peak found in electrochemical Sabatier volcano plots at ΔG H* = ~0 eV was replicated in the experimental photocatalytic system with a peak activity observed at ΔG H* = -0.036 eV. Computational confirmation of the results expressed here demonstrates the efficacy of colorimetric detection of hydrogen in parallel and presents a model for increasingly rapid catalyst screening.

08 HYDROGEN↗
DOE OSTI2020

Use of a segmented cell for the combinatorial development of platinum group metal-free electrodes for polymer electrolyte fuel cells

The development of novel platinum group metal (PGM)-free catalysts is a difficult task, particularly when coupled with the integration into a cathode catalyst layer (CCL). The optimization of such PGM-free electrode structures is often non-linear and iterative, making it a demanding task due to the high number of parameters that affect performance. To accelerate both materials discovery and electrode development, this work demonstrates the application of a high-resolution segmented cell (SC) with 121 segments of 0.413 cm 2 size for combinatorial high-throughput PGM-free catalyst screening and CCL optimization. The approach utilizes three flow-field strips with active areas of 4.45 cm 2 each, distributed over 11 segments. Electrodes with identical catalyst material and fabrication method result in reproducible data with typically less than 10% variation between each segment and match in performance with differential single cell data. High throughput testing of combinatorial sample sets, with varied PGM-free electrocatalyst materials or electrode composition, demonstrated the ability to rapidly discern high performing outliers, and establish or confirm trends in electrode optimization. The results indicated significant performance benefits of electrodes with ionomer content of 45 wt% over lower values, and of water rich inks with 82% water content over those with 50%.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Ligand enhanced activity of in situ formed nanoparticles for photocatalytic hydrogen evolution

One consistent challenge of both computational and empirical catalyst screening is ensuring that the variables chosen for the screen are driving the performance analyzed. Furthermore, we compare photocatalytic hydrogen evolution from in situ formed Au and Au/Cu nanoparticles to nanoparticles of the same composition synthesized prior to being used as catalysts, as well as compare them to in situ formed Au and Au/Cu nanoparticles in the presence of exogeneous ligand. For all experiments, we observed that ligand-terminated nanoparticles performed better than un-stabilized in situ formed nanoparticles. We tested the generality of this result by studying Co, Ni, and Pd in the same system and also observed that the introduction of nanoparticle ligand leads to enhanced catalytic activity. Taken together, these results suggest 1) nanoparticle ligands can be beneficial, and even necessary, to produce catalysts with sustained activity 2) For computational prediction of these catalysts, factors relating to particle formation and stability need to be considered when both generating predictions as well as interpreting experimental results based on those predictions

08 HYDROGEN↗
DOE OSTI2026

Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

The growing demand for energy-efficient processes to support a sustainable future drives the need for research to rapidly explore chemical and material space through accelerated catalyst discovery initiatives. Recent breakthroughs in high-throughput experimental and computational methods are transforming the catalysis field, surpassing traditional approaches to manipulating variables in catalytic processes. Key advancements in innovation include the integration of machine learning for efficient catalyst screening, high-throughput experimentation, data-driven methodologies employing comprehensive databases, and in situ and in operando techniques for realistic observations. This progress has undoubtedly been intertwined with a collaborative framework across disciplines, reshaping catalyst discovery methods in both industry and academia. This Opinion article presents a multifaceted perspective from coauthors with expertise spanning various stages of the Technology Readiness Level spectrum, highlighting both opportunities and persistent challenges in integrating computational and experimental approaches in catalysis. These challenges span from obtaining high-quality experimental data, scaling simulations to industrially relevant materials and process conditions to navigating the complexity and predictive accuracy of computational models.

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

Production of neo acids from biomass-derived monomers

Neo acids are highly branched carboxylic acids currently produced from fossil fuels. In this work, we produce renewable neo acids from lignocellulosic biomass-derived furan and keto acids via C–C coupling through hydroxyalkylation/alkylation (HAA), followed by ring-opening of furans through hydrodeoxygenation (HDO). Here, we show effective C–C coupling over acid catalysts. Catalyst screening and multi-parameter optimization using machine learning optimize the yield and elucidate the correlation between variables and outcomes. We demonstrate selective furan ring-opening without affecting the carboxylic acid to make neo acids using a co-catalyst involving Pd supported on carbon and metal triflate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Upper Stage Flight Experiment 10K Engine Design and Test Results

A 10,000 lbf thrust chamber was developed for the Upper Stage Flight Experiment (USFE). This thrust chamber uses hydrogen peroxide/JP-8 oxidizer/fuel combination. The thrust chamber comprises an oxidizer dome and manifold, catalyst bed assembly, fuel injector, and chamber/nozzle assembly. Testing of the engine was done at NASA's Stennis Space Center (SSC) to verify its performance and life for future upper stage or Reusable Launch Vehicle applications. Various combinations of silver screen catalyst beds, fuel injectors, and combustion chambers were tested. Results of the tests showed high C* efficiencies (97% - 100%) and vacuum specific impulses of 275 - 298 seconds. With fuel film cooling, heating rates were low enough that the silica/quartz phenolic throat experienced minimal erosion. Mission derived requirements were met, along with a perfect safety record.

Ross, R.↗
DOE OSTI2022

Enhanced descriptor identification and mechanism understanding for catalytic activity using a data-driven framework: revealing the importance of interactions between elementary steps

We report accurate identification of descriptors for catalytic activities has long been essential to the in-depth understanding of catalysis and recently to set the basis for catalyst screening. However, commonly used methods suffer from low accuracy in predictability. This study reports an enhanced approach to accurately identify the descriptors from a kinetic dataset using a machine learning (ML) surrogate model. CO hydrogenation to methanol over Cu-based catalysts was taken as a case study. Our model captures not only the contribution from individual elementary steps but also the interaction between relevant steps within a reaction network, which was found to be essential for high accuracy. As a result, six effective descriptors are identified, which are accurate enough to ensure the trained gradient boosted regression (GBR) model for good prediction of the methanol turnover frequency (TOF) over metal (M)-doped Cu(111) model surfaces (M = Au, Cu, Pd, Pt, Ni). More importantly, going beyond the purely mathematical ML model, the catalytic role of each identified descriptor can be revealed by using model-agnostic interpretation tools, which enhances the insight into the promoting effect of alloying. The trained GBR model outperforms the conventional derivative-based methods in terms of both the predictability and the mechanism understanding. It opens alternative possibilities toward accurate descriptor-based rational catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Activity Trends for Catalytic CO and NO Co-Oxidation at Low Temperature Diesel Emission Conditions

The diesel oxidation catalyst (DOC) is an essential component of modern vehicle emissions control systems. The pervasive challenge for low temperature oxidation of engine exhaust gas is the mutual inhibition between the various pollutants, causing a marked increase in light-off temperature. Using a combination of density functional theory and descriptor-based microkinetic modeling, we have screened catalysts for low temperature co-oxidation of CO and NO with specific emphasis on minimizing inhibition effects. Compared to standard Pt–Pd alloys, we find that coinage metal alloys, i.e., Cu, Ag, and Au with at least one oxophilic constituent, should possess more robust low temperature activity with minimal inhibition. We attribute this remarkable performance to high surface concentrations of oxygen due to the oxophilic component and less competitive adsorption between CO and NO to the exposed coinage metal sites. We believe that these fundamental insights provide valuable design principles for improved low temperature oxidation catalysts.

02 PETROLEUM↗
DOE OSTI2022

Perspectives on Polyolefin Catalysis in Microfluidics for High-Throughput Screening: A Minireview

Polyolefins are the largest produced plastics in the world which traditionally employ continuous stirred tank reactors and fluidized bed reactors for commercial production. The operating condition, reaction kinetics, and molecular interactions inside the reactor strongly affect the polyolefin properties, which require stringent process control in conventional procedures. Understanding the catalytic pathway, behavior of polymer particles and effect of reactor conditions are essential for designing specific polymer properties, namely the molecular weight, chain length, polydispersity, etc. Microfluidics can play a significant role in designing polymers tailored to the user needs. Smaller channel dimensions help obtain uniform reaction conditions over the length of the microfluidic reactor in a controlled environment. With real-time monitoring techniques in microfluidics, even single particle growth of polymer can be studied to understand the parameters affecting the polymer properties. High throughput microfluidics can help catalyst screening in a short duration with less consumption of reagents generating less waste. When supplemented with efficient machine learning algorithms, automated high throughput microfluidics has the potential to rapidly optimize the process and develop new knowledge even with a limited data set. When trained on data sets generated using microfluidic experiments that are designed efficiently with working knowledge of the process, machine learning algorithms can provide the relationship between the multivariable parameters space and polymer properties, which is not possible with the traditional statistical methods and interpolation techniques. Here, the rise in the utilization of microfluidics, with the advancement of machine learning algorithms, for polyolefin catalysis, highlights the importance of microfluidics for catalyst discovery, parameter optimization, and understanding reaction pathway for producing polymers with specific properties for specialized applications.

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

Calorimetric metal vapor adsorption energies for characterizing industrial catalyst support materials

Many important catalysts and electro-catalysts for energy and environmental technologies involve late transition metal atoms and nanoparticles dispersed across the surface of high-surface-area support materials, for example, oxide nanoparticles. The surface reactivity and long-term stability against deactivation of these materials depends strongly on the strength of bonding of the metal atom and nanoparticles to the support surface. Here, we introduce a novel calorimetry method that implements a LiTaO 3 crystal for heat detection and extends metal adsorption calorimetry to surfaces of nanomaterials that are deposited from liquid solutions, as is typical when preparing industrial catalyst supports. This allows one to measure the strength of metal atom bonding and the adhesion energy of metal nanoparticles to clean surfaces of technologically relevant catalyst supports. We demonstrate that here by measuring the heat of Ag vapor adsorption onto the clean surfaces of high-surface-area TiO 2 anatase powdered support materials (i.e., 5-nm-diameter nanoparticles). These heats of adsorption show a pulse-to-pulse standard deviation of only 9.3 kJ/mol (3.3%) for pulses containing only 1% of a monolayer of Ag vapor, with potential for a 5-fold reduction in noise if used with another metal evaporator. The calorimeter was also proven to work well measuring heats of Ag adsorption on calcium niobate(001) nanosheets deposited as thin films from liquid solution. Here, this calorimeter opens up the possibility of using metal adsorption calorimetry to screen catalyst support materials for the strengths with which they bind metal atoms and metal nanoparticles, offering new opportunities to discover better support materials or for basic scientific study of structure / function relationships with respect to metal / support bond energies.

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

Incorporating Coverage-Dependent Reaction Barriers into First-Principles-Based Microkinetic Models: Approaches and Challenges

Mean-field microkinetic models (MKMs) are appealing for their relatively facile construction, computational tractability, and high-throughput catalyst screening capabilities. As such, they will continue to be a valuable tool for materials design in heterogeneous catalysis even as the field aims to describe more complex systems. Numerous prior reports have provided the groundwork for constructing first-principles-based MKMs, including the analysis of strategies for incorporating lateral interactions into thermodynamic parameters (e.g., adsorption energies). Yet, there remains a need for concerted dialogue on methods for calculating and incorporating coverage-dependent kinetic parameters into MKMs. In this Perspective, we assess strategies for doing so, including the corresponding key physical implications and computational challenges. Here, we emphasize that decoupling thermodynamic and kinetic parameters within MKMs can violate thermodynamic consistency and risk unphysical solutions. For some reactions and catalyst materials, scaling relationships can predict coverage-dependent activation energies, but there are several exceptions evident in the literature, indicating that this approach is not universally applicable and that the field could benefit from research aimed at elucidating the limitations. Conducting high-coverage transition state searches is a rigorous but computationally costly strategy, and the effects of various methods for mitigating this cost on resulting energetics have yet to be broadly explored and validated. The goal of this Perspective is to generate discussion on and inspire focused research into the physical relevance of approaches for describing coverage-dependent reaction barriers in MKMs, including the development of computationally tractable methodologies, to advance the applicability of MKMs across diverse reaction chemistries and conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Active site design enables industrial scale H 2 O 2 electrosynthesis with metal-free catalysts

The electrosynthesis of hydrogen peroxide (H 2 O 2 ) via a two-electron oxygen reduction reaction enables decentralized H 2 O 2 production. While metal-free carbon catalysts are sustainable and low-cost, their performance is hindered by poorly defined active sites and uncontrolled defect states. Here, we resolve these challenges through active site design and catalyst screening using fluorine (F) and nitrogen (N) codoped carbons as model materials. Statistical analysis combined with density functional theoretical calculations reveals that F-induced structural modification and defect passivation optimize OOH* binding, with F-doping and adjacent F atoms predominantly lowering abs ΔG(OOH*). Experimental results confirm that semi-ionic C–F bonds passivate defects in nitrogen-doped carbon, enhancing catalytic activity and durability. The resulting (N, F)-codoped carbon achieves nearly 100% H 2 O 2 selectivity at 0.5–0.65 V versus the reversible hydrogen electrode and maintains > 95% across 0.01–0.65 V versus the reversible hydrogen electrode. In an electrolyzer, (N, F)-codoped carbon exhibits an H 2 O 2 yield rate of 74.35 mol g cat. −1 h -1 and sustains 300 mA cm -2 for 105 hours with ~95% faradaic efficiency. Coupling the two-electron oxygen reduction reaction with methanol oxidation further reduces cell voltage and enhances productivity. This work provides a means to design efficient catalysts for industrial H 2 O 2 electrosynthesis.

H2O2 electrosynthesis↗
DOE OSTI2021

Catalytic Activity and Water Stability of the MgO(111) Surface for 2-Pentanone Condensation

Nanomaterials derived from earth-abundant metal oxides have gained tremendous interest as catalysts; although, water stability remains a challenge. This study examines MgO(111) surfaces for 2-pentanone condensation and their evolution during D2O hydration. Catalyst screening confirmed the high activity of fresh MgO(111) for 2-pentanone condensation relative to conventionally prepared MgO(100). Computational modeling suggests that the (111) surface is readily hydroxylated, and that surface hydroxyls help stabilize the surface and reduce the barrier for 2-pentanone condensation. Vapor-phase D2O hydration after 3 min increased MgO(111) hydroxyls and retained surface area and activity; however, after 1 h, deuteroxide formation reduced the surface area and activity by >30 %. After 24 h, deuteroxide growth slowed down, and surface area and activity remained stable. This suggests MgO(111)-derived hydroxide may be the dominant surface responsible for 2-pentanone condensation following water exposure. Thermal regeneration of the 24-h sample restored 86 % of the surface area and 94 % of the activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Quantum mechanical study of CO 2 and CO hydrogenation on Cu(111) surfaces doped with Ga, Mg, and Ti

DFT methods were used to analyze metal (M)-doped Cu(111) surfaces to identify surface alloys that could catalyze the hydrogenation of CO 2 . Here, the adsorption of relevant species for CO 2 /CO hydrogenation were studied on Cu(111) surfaces doped with Ga, Mg, and Ti. Preferred adsorption sites, geometries, and binding energies for relevant intermediates were determined. A systematic study of the thermochemistry of plausible surface reactions for CO 2 /CO hydrogenation on Ga/Cu(111), Mg/Cu(111), and Ti/Cu(111) was performed to postulate reaction mechanisms for the synthesis of formic acid, formaldehyde, and methanol. Our results suggest that Ga/Cu(111) and Mg/Cu(111) surfaces might be promising catalysts for the synthesis of methanol from CO 2 hydrogenation. CO 2 is activated by chemisorption on Mg/Cu(111) and Ti/Cu(111), but the latter surface has a strong interaction with O, which inhibits the last reaction steps and the desorption of the products. Our results demonstrate that the thermochemistry of CO 2 hydrogenation for the synthesis of the different products varies drastically depending on the dopant on Cu(111). Furthermore, our results suggest that the formation energies of HCOO, CH 2 O, CH 3 O, and HCO are good descriptors for catalyst screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗