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Linic, Suljo

Publications and source records attributed to Linic, Suljo.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Overcoming limitations in propanedehydrogenation by codesigning catalyst-membrane systems

Propylene production through propane dehydrogenation (PDH) is endothermic, and high temperatures required to achieve acceptable propane conversions lead to low selectivity and severe carbon-induced deactivation of conventional catalysts. We developed a catalyst-membrane system that removes the hydrogen by-product and can thus achieve propane conversions that exceed equilibrium limits. In this codesigned system, a silica/alumina (SiO 2 /Al 2 O 3 ) hollow-fiber hydrogen membrane was packed with a selective platinum-tin (Pt 1 Sn 1 /SiO 2 ) PDH catalyst on the tube side with hydrogen diffusing from the tube to the shell side. We demonstrate that the catalyst-membrane system can achieve propane conversions >140% of the nominal equilibrium conversion with a propylene selectivity >98% without deactivation of the system components. Here, we also show that by introducing oxygen on the shell side of the catalyst-membrane system, we can couple the endothermic PDH reaction on the tube side with exothermic hydrogen oxidation on the shell side. This coupling results in higher rates of hydrogen transport, leading to further enhancements in the propane conversion as well as desired thermoneutral system operation.

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

High-Performance Iridium–Molybdenum Oxide Electrocatalysts for Water Oxidation in Acid: Bayesian Optimization Discovery and Experimental Testing

Ir oxides are costly and scarce catalysts for oxygen evolution reaction (OER) in acid. There has been extensive interest in developing alternatives that are either Ir-free or require smaller amounts of Ir to drive the reactions at acceptable rates. One design strategy is to identify Ir-based mixed oxides that achieve similar performance while requiring smaller amounts of Ir. The obstacle to this strategy has been a very large phase space of the Ir-based mixed metal oxides, in terms of the metals combined with Ir and the different crystallographic structures of the mixed oxides, which prevents a thorough exploration of possible materials. In this work, we developed a workflow that uses machine-learning-aided Bayesian optimization in combination with density functional theory to make the exploration of this phase space plausible. This screening identified Mo as a promising dopant for forming acid-tolerant Ir-based oxides for the OER. We synthesized and characterized the Ir–Mo mixed oxides in the form of thin-film electrocatalysts with a known surface area. We show that these mixed oxides exhibited overpotentials ~30 mV lower than a pure Ir control while maintaining 24% lower Ir dissolution rates than the Ir control. Furthermore, these findings suggest that Mo is a promising dopant and highlight the promise of machine learning to guide the experimental exploration and optimization of catalytic materials.

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

Optimizing hierarchical membrane/catalyst systems for oxidative coupling of methane using additive manufacturing

The advantage of a membrane/catalyst system in oxidative coupling of methane (OCM) compared to conventional reactive systems is that by introducing oxygen to the OCM catalytic sites through a membrane, parasitic gas phase reactions of O 2 (g), responsible for lowering product selectivity, can be avoided. The design and fabrication of membrane/catalyst systems has, however, been hampered by low volumetric chemical conversion rates, high capital cost, and difficulties in codesigning membrane and catalyst properties to optimize the performance. We solve these issues by developing a dual-layer additive manufacturing process, based on phase inversion, to design, fabricate and optimize a hollow fiber membrane/catalyst system for OCM. We demonstrate the approach though a case study using BaCe 0.8 Gd 0.2 O 3-δ (BCG) as the basis of both the catalyst and separation layers. We show that by using the manufacturing approach we can codesign the membrane thickness and catalyst surface area so that the flux of oxygen transport through the membrane and methane activation rates in the catalyst layer match each other. Here, we demonstrate that this “rate matching” is critical for maximizing the performance, with the membrane/catalyst system significantly overperforming conventional reactor designs under identical conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mechanisms of Ethylene Epoxidation over Silver from Machine Learning-Accelerated First-Principles Modeling and Microkinetic Simulations

In this work we employed machine learning-augmented density functional theory (DFT) thermodynamic calculations to assess the stability of different AgO x structures under catalytic ethylene epoxidation reaction conditions. We found that there are multiple AgO x surface motifs that could co-exist under the relevant conditions. These included Ag surface oxides (e.g., AgO_p(4 × 4) and Ag 1.83 O) and atomic oxygen-covered Ag(111) surfaces. Furthermore, we employed DFT calculations to evaluate the energetics of different reaction mechanisms by which ethylene and oxygen can react on these surfaces. These studies revealed several energetically viable reaction pathways for ethylene epoxidation. Microkinetic modeling analyses, based on the DFT-calculated reaction pathways, showed that ethylene epoxidation can proceed on all surfaces and that multiple pathways, including those involving Langmuir–Hinshelwood and Eley–Rideal mechanisms, could be involved in selective and unselective reactions. The diversity of mechanisms that we discovered in the context of the relatively simple ethylene epoxidation reaction on Ag suggests that the richness and complexity of surface chemistry are most likely a rule rather than an exception in heterogeneous catalytic chemical transformations on metal surfaces and that the concept of a single or even a dominant mechanism and reaction intermediates might need to be revisited for many reactions.

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

Elucidating the Roles of Local and Nonlocal Rate Enhancement Mechanisms in Plasmonic Catalysis

Plasmonic metal nanoparticles (e.g., Ag, Au, and Cu) constitute a class of materials that interact with light via the excitation of localized surface plasmon resonance (LSPR). Numerous studies have reported substantial enhancements in the rates of chemical reactions on illuminated plasmonic nanoparticle catalysts compared to corresponding systems in the absence of illumination. There are two mechanisms that have been proposed to explain the LSPR-induced chemical reactivity. One mechanism assumes a local plasmon-induced hot charge-carrier-mediated activation of the reactants, while the other assumes an LSPR-induced equilibrium heating of the catalyst, which leads to energy transfer to and chemical reaction of the adsorbed reactants. Here, in this contribution, we developed a setup amenable to accurate in situ catalyst temperature and kinetic reaction rate measurements. We employed this setup to study the LSPR-induced rate enhancement in a case study of the CO oxidation reaction on plasmonic, monometallic Ag nanoparticle catalysts supported on α-Al 2 O 3 . We explored various Ag loadings and clustering levels. Our data show that the equilibrium heating of the catalyst cannot fully explain the illumination-induced plasmonic rate enhancements. This is the case even for high loading and clustering of Ag nanoparticles, where the equilibrium heating significantly increases. Based on the analysis, we propose that local effects, related to the plasmon-induced activation of adsorbates (reactants) via electronic excitation of the reactant or photothermal heating of the reactants that is highly localized to the individual nanoparticles, play a critical role in driving LSPR-induced chemical reactions.

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

Optimizing molecular light absorption in the strong coupling regime for solar energy harvesting

The strong coupling of optical absorbers (e.g., molecules or semiconductors) to confined photonic modes fundamentally alters the physical properties of the coupled system via the formation of hybrid light-matter states. One potential application of strong light-matter coupling relies on exploiting it to localize light-induced charge excitation processes to small volumes of material. Applications that would benefit from this localization include thin-film photovoltaics, photodetection, photocatalysis, and others, where the overall performance depends on the ability of a material to amplify light absorption (i.e., the formation of electron-hole pairs) within specific locations in space. This contribution investigates how strong light-matter coupling affects light absorption rates in molecular absorbers coupled to photonic nanostructures. Here, our results show that the molecular light absorption efficiencies are highest in configurations where the strongly coupled molecules interact directly with the incoming photon flux. We also identify a nonlinear dependence in the molecular absorption as a function of concentration, unique to the strongly coupled systems. Based on these results, we propose design principles for engineering nanostructured systems that allow for high efficiencies of charge carrier localization into strongly coupled absorbers.

14 SOLAR ENERGY↗
DOE OSTI2022

Interpretable machine learning for knowledge generation in heterogeneous catalysis

Most applications of machine learning in heterogeneous catalysis thus far have used black-box models to predict computable physical properties (descriptors), such as adsorption or formation energies, that can be related to catalytic performance (that is, activity or stability). Here, extracting meaningful physical insights from these black-box models has proved challenging, as the internal logic of these black-box models is not readily interpretable due to their high degree of complexity. Interpretable machine learning methods that merge the predictive capacity of black-box models with the physical interpretability of physics-based models offer an alternative to black-box models. In this Perspective, we discuss the various interpretable machine learning methods available to catalysis researchers, highlight the potential of interpretable machine learning to accelerate hypothesis formation and knowledge generation, and outline critical challenges and opportunities for interpretable machine learning in heterogeneous catalysis.

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

Characterizing the Geometry and Quantifying the Impact of Nanoscopic Electrocatalyst/Semiconductor Interfaces under Solar Water Splitting Conditions

The materials that are receiving the most attention in photoelectrochemical water splitting are metallic nanoparticle electrocatalysts (np-EC) attached to the surface of a semiconductor (SC) light absorber. In these multicomponent systems, the interface between the semiconductor and electrocatalysts critically affects performance. However, the np-EC/SC interface remains poorly understood as it is complex on atomic scales, dynamic under reaction conditions, and inaccessible to direct experimental probes. This contribution sheds light on how the electrocatalyst/semiconductor interface evolves under reaction conditions by investigating the behavior of nickel electrocatalysts (as nanoparticles and films) deposited on silicon semiconductors. Rigorous electrochemical experiments, interfacial atomistic characterization, and computational modeling are combined to demonstrate critical links between the atomistic features of the interface and the overall performance. It is shown that electrolyte-induced atomistic changes to the interface lead to (1) modulation of the charge carrier fluxes and a dramatic decrease in the electron/hole recombination rates and (2) a change in the barrier height of the interface. Additionally, the critical roles of nonidealities and electrocatalyst coverage due to interfacial geometry are explored. Each of these factors must be considered to optimize the design of metal/semiconductor interfaces which are broadly applicable to photoelectrocatalysis and photovoltaic research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Here, we show that unsupervised machine learning (ML) using principal component analysis (PCA) provides a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of the chemical and catalytic properties of materials. We demonstrate the approach by finding chemisorption descriptors for metal alloys and surface oxygens on metals and metal oxides. In both cases, the principal component (PC) descriptors yield ML models that predict the material’s chemical properties with competitive accuracy compared to ML models built using established descriptors. Importantly, interpreting the electronic-structure patterns captured by each PC descriptor via signal reconstruction suggests potential design motifs for future electronic-structure descriptor design and allows us to identify links between a material’s geometric and catalytic properties. Ultimately, we show that the unsupervised ML approach provides a route to find electronic-structure descriptors of the catalytic properties of materials that readily connect to geometric structure and composition.

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

Stable and selective catalysts for propane dehydrogenation operating at thermodynamic limit

Hitting the limits on propene synthesis The greater abundance of propane from shale gas has spurred efforts to use it as a propylene feedstock. Direct dehydrogenation catalysts consisting of platinum–tin alloy nanoparticles supported on alumina often must run with hydrogen dilution to avoid carbon buildup and excess tin to avoid alloy segregation. Motagamwala et al. report that platinum–tin nanoparticles interact more weakly with a silica support and the metals thus do not segregate. The use of undiluted reactants allowed the reaction to run near the thermodynamically limit of about 67% conversion with a selectivity to propylene of more than 99%. This catalyst also does not build up carbon and could run up to 30 hours without deactivation. Science , abg7894, this issue p. 217

Science & Technology - Other Topics↗
DOE OSTI2021

Plasma-driven solution electrolysis

Plasmas interacting with liquids enable the generation of a highly reactive interfacial liquid layer due to a variety of processes driven by plasma-produced electrons, ions, photons, and radicals. These processes show promise to enable selective, efficient, and green chemical transformations and new material synthesis approaches. While many differences are to be expected between conventional electrolysis and plasma–liquid interactions, plasma–liquid interactions can be viewed, to a first approximation, as replacing a metal electrode in an electrolytic cell with a gas phase plasma. For this reason, we refer to this method as plasma-driven solution electrochemistry (PDSE). In this Perspective, we address two fundamental questions that should be answered to enable researchers to make transformational advances in PDSE: How far from equilibrium can plasma-induced solution processes be driven? and What are the fundamental differences between PDSE and other more traditional electrochemical processes? Different aspects of both questions are discussed in five sub-questions for which we review the current state-of-the art and we provide a motivation and research vision.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Design Principles for Efficient and Stable Water Splitting Photoelectrocatalysts

Photoelectrochemical water splitting is a promising avenue for sustainable production of hydrogen used in the chemical industry and hydrogen fuel cells. The basic components of most photoelectrochemical water splitting systems are semiconductor light absorbers coupled to electrocatalysts, which perform the desired chemical reactions. A critical challenge for the design of these systems is the lack of stability for the majority of desired semiconductors under operating water splitting conditions. One strategy to address this issue is to protect the semiconductor by covering it with a stabilizing insulator layer, creating a metal–insulator–semiconductor (MIS) architecture, which has demonstrated improved stability. In addition to enhanced stability, the insulator layer may significantly affect the electron and hole transfer, which governs the recombination rates. Furthermore, the insertion of an insulator layer leads to the introduction of additional insulator/electrocatalyst and insulator/semiconductor interfaces. These interfaces can impact the system’s performance significantly, and they need to be carefully engineered to optimize the efficiencies of MIS systems. In this Account, we describe our recent progress in shedding light on the critical role of the insulator and the interfaces on the performance of MIS systems. We discuss our findings by focusing on the concrete example of planar n-type Si protected by a HfO 2 insulator layer and coupled to a Ni or Ir electrocatalyst that performs the oxygen evolution reaction, one of the water splitting half-reactions. To improve our fundamental understanding of the insulator layer, we precisely control the HfO 2 insulator thickness using atomic layer deposition (ALD), and we perform a series of rigorous electrochemical experiments coupled with theory and modeling. We demonstrate that by tuning the insulator thickness, we can control the flux and recombination of photogenerated electrons and holes to optimize the generated photovoltage. Despite optimizing the thickness, we find that the maximum generated photovoltage in MIS systems is often significantly lower than the upper performance limit, i.e., there are additional losses in the system that could not be addressed by optimizing the insulator thickness. We identify the sources of these losses and describe strategies to minimize them by a combination of improving the semiconductor light absorption, removing nonidealities associated with interfacial defects, and finding alternative insulators with improved charge carrier selectivity. Finally, we quantify the improvements that can be obtained by implementing these specific strategies. Our collective work outlines strategies to analyze MIS systems, identify the sources of efficiency losses, and optimize the design to approach the fundamental performance limits. Furthermore, these general approaches are broadly applicable to photoelectrochemical materials that utilize sunlight to produce value-added chemicals.

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

Development of physically transparent, predictive structure-performance relationships for rational design of multi-component catalytic materials. Final Report

Solid surfaces act as catalysts for many important chemical processes, including commodity chemicals production, energy conversion and pollution mitigation. The outcome of catalytic processes is mainly governed by interactions of adsorbates with active sites on the catalyst surface. These interactions can be dramatically affected by the changes in the local characteristics of the active site, which can be accomplished by an introduction of various promoters and poisons, or by alloying with other metal atoms. In fact, many commercial heterogeneous catalysts contain metal nanoparticles promoted by various additives. Our goal is to develop fundamental understanding about the impact of perturbations in the local geometry of a catalytic site on the local surface reactivity. These insights are crucial for a more systematic and rational catalyst design. The project aims to advance the field of catalysis by formulating reliable structure/performance relationships and utilizing these relationships to identify novel catalytic materials. Benefits for DOE and our society are in the development of fundamental theories that guide the process of discovery of energy-efficient and environmentally friendly heterogeneous catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In-operando surface-sensitive probing of electrochemical reactions on nanoparticle electrocatalysts: Spectroscopic characterization of reaction intermediates and elementary steps of oxygen reduction reaction on Pt

In this paper we present an in-operando spectroscopic study of the reaction intermediates involved in ORR on electrified Pt nanoparticle electrocatalysts. To accomplish this, we have synthesized Ag-Pt core–shell nanoparticles, that contain a thin shell of Pt (~1 nm) uniformly deposited on a larger Ag core (~60 nm). We show that these nanostructures are ideal platforms for in-operando Plasmon Enhanced Raman Spectroscopy (PERS) of ORR on Pt. We combined these PERS studies with DFT calculations to assign the measured vibrational spectra to relevant surface intermediates as a function of electrocatalyst potential. Overall, these vibrational assignments were further verified and validated by performing PERS measurements using de-oxygenated and heavy oxygen (O 2 -18) saturated electrolyte. These studies allowed us to identity the presence of critical reaction intermediates (OH, O 2 , OOH, and H 2 O) as the function of operating voltage on the Pt surface and derive voltage-dependent elementary step mechanisms of the reaction.

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

Flow and extraction of energy and charge carriers in hybrid plasmonic nanostructures

Strong interactions of electromagnetic fields with plasmonic nanomaterials have been exploited in various applications. These applications have centred on plasmon-enhanced scattering rates in nearby molecules or plasmon-induced heating. A question that has emerged recently is whether it is possible to use plasmonic nanostructures in a range of hot electron (hole) applications, including photocatalysis, photovoltaics and photodetection. These applications require coupling of a plasmonic component, which amplifies the interaction of light with the material, to an attached non-plasmonic component that extracts this energy in the form of electronic excitations to perform a function. Here, in this Perspective, we discuss recent work in the emerging field of hybrid plasmonics. We focus on fundamental questions related to the nanoscopic flow of energy and excited charge carriers in these multicomponent materials. We also address critical misconceptions, challenges and opportunities that require more attention.

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

Critical Practices in Rigorously Assessing the Inherent Activity of Nanoparticle Electrocatalysts

Accurate activity measurements for electrocatalytic materials are the backbone of impactful electrocatalyst research. Inherent to accurate measurements is the correct accounting of the active catalyst sites and the design of experiments to ensure that these sites are participating in the measured reaction. Improvements in electrocatalyst activity for fuel cell reactions (hydrogen oxidation and oxygen reduction) are essential for the widespread adoption of this carbon-neutral energy source. Activities for these half-reactions can be reported in a variety of ways including specific activities, mass activities, volumetric activities, and half-wave potentials. These values are traditionally measured with a rotating disk electrode (RDE) in which the electrocatalyst is supported on a porous active layer film attached to the RDE. To accurately measure electrocatalyst activity with an RDE, two major sources of errors must be addressed: (i) accurate electrochemical surface area (ECSA) quantification and (ii) fast diffusion of reactants through the active layer film. In this contribution, we first aim to detail through RDE experiments and mass transport modeling the potential errors that can be observed when these factors are not properly addressed. We then present recommendations and discuss techniques for properly constructing electrocatalyst thin films and characterizing the ECSA on monometallic and novel alloy electrocatalysts. These practices, when adopted, ensure greater confidence and reliability in reports of electrocatalyst activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗