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Growth of Carbon Nanotubes Using Mixed-Metal Catalysts That Include Heavy Refractory Metals as Catalyst Stabilizers
Here, we report new findings from studies of a novel technique to augment the growth of CNTs. In this method, the catalytic metals used for CNT growth are combined with high-melting-point heavy refractory metals, which serve to stabilize the metal catalyst nanoparticles, from which the CNTs nucleate and grow. Our study investigates the combination of an iron catalyst with tungsten and osmium refractory stabilizers. We find that both tungsten and osmium enhance the lifetime of the iron catalyst particles by a factor of approximately two. Tungsten stabilizer resulted in production of CNTs longer by a factor of 1.25 compared to those produced using a pure iron catalyst, while the osmium stabilizer did not significantly affect the ultimate length of the CNTs due to the decreased CNT growth rate with a combined Fe/Os catalyst. These results suggest a possible new route toward producing CNTs with lengths sufficient for materials applications.
An ultrastable heterostructured oxide catalyst based on high-entropy materials: A new strategy toward catalyst stabilization via synergistic interfacial interaction
Designing high–performance catalysts that can stabilize catalytic active sites against sintering to deactivation at temperature higher than 900°C is significant but challenging. In this work, we report a new strategy to obtain a transition metal oxide catalyst with high temperature stability for CO oxidation. This is achieved through a synergistic interfacial interaction at the interface of a heterostructure between high– entropy oxides (HEO, high temperature stability) and CuCeO x (catalytic site). The catalytic site (CuCeO x ) for CO oxidation is realized by dissolving an amount of Cu species in HEO into CeO 2 via an entropy–driven mechanochemical process. In situ XRD and HAADF–STEM have confirmed the high temperature stability of the heterostructure CuCeO x –HEO, which can remain its CO oxidation catalytic activity at elevated temperatures. It should be expected that this innovative will offer the potential to the synthesis of catalysts with high temperature stability in industry.
Metal Identity and Coordination Environment Modulate Single-Atom Catalyst Stability During Electrocatalysis
A major hurdle to the implementation of single-atom catalysts (SACs) in real-world systems is a poor understanding of their stability under operating conditions, which is particularly relevant due to the high surface free energy of SACs. Here, we evaluated the aggregation behavior of a suite of SACs varied by metal identity (Fe, Co, Ni, and Cu) during electrocatalytic nitrate reduction using in situ X-ray absorption spectroscopy. The metal center had significant influence on reconstruction, where under identical applied reductive potentials, SACs underwent varying levels of reconstruction, ranging from no discernible change to complete reduction into metallic nanoparticles. Such in situ experiments revealed Cu SACs to be the most susceptible to aggregation, prompting a deeper investigation into how coordination environment (O-, B-, and N-graphene) affected Cu SAC aggregation. We further conducted density functional theory calculations to elucidate the relationship between Cu SAC structure and stability. This work deconvolutes the relationship between SAC architecture and stability, which is essential to evaluate and explain for the realization of SACs for electrocatalysis.
Understanding Methanol Synthesis on Inverse ZnO/CuO x /Cu Catalysts: Stability of CH 3 O Species and Dynamic Nature of the Surface
Inverse ZnO/Cu catalysts are key systems in the conversion of CO 2 , a common atmospheric pollutant, into methanol, a high-value chemical and fuel. The chemistry of methanol and methoxy groups over inverse ZnO/Cu 2 O/Cu(111) catalysts was investigated employing Ambient Pressure X-ray Photoelectron Spectroscopy (AP-XPS), Scanning Tunneling Microscopy (STM) and calculations based on Density Functional Theory (DFT). The results of AP-XPS show that the adsorption of methanol on the binary oxide substrate at 300 K leads to formation of *CH 3 O and *HCOO species with a minor amount of *CH x . Furthermore, most of the methoxy groups disappeared from the surface after heating to 450 K, the onset temperature for the formation of methanol during the hydrogenation of CO 2 . The results of AP-XPS, STM and DFT point to preferential adsorption of methoxy on the ZnO regions of the binary oxide. On the supported ZnO or on a ZnO-Cu 2 O interface, the breaking of the O-H bond in methanol is an exothermic process with a negligible (1-2 kcal/mol) or non-existent energy barrier depending on the size and shape of the ZnO islands. STM
Ligand-coordinated Ir single-atom catalysts stabilized on oxide supports for ethylene hydrogenation and their evolution under a reductive atmosphere
In this work, we present a novel series of oxide-supported Ir-ligand single-atom catalysts (SACs) for ethylene hydrogenation. The SACs were created by a metal–ligand self-assembly strategy developed by our group, using one of two ligands, either 1,10-phenanthroline-5,6-dione (PDO) or 3,6-Di-2-pyridyl-1,2,4,5-tetrazine (DPTZ), on powder supports of either CeO 2 or MgO. Characterization by XAS, XPS, and CO adsorption proved that Ir exist principally as highly uniform, cationic single-atoms. Ir SACs show significantly higher durability and metal utilization efficiency than Ir nanoparticle (NP) catalysts during ethylene hydrogenation at 100 °C, as well as excellent stability, as no Ir aggregates were detected after >10 h reaction. The activity can be tuned by ligand and support effects: PDO and CeO 2 are superior to DPTZ and MgO, respectively. This tunability is attributed to differences in H 2 activation capability, which results from differences in support reducibility, electron density on Ir, and, potentially, the local coordination environment of Ir. The Ir SACs lose H 2 activation activity either under inert gas or under H 2 . Through XPS and in situ XAS studies, we attributed the former to the reversible loss of Ir hydride, which is the active species for H 2 activation, and the latter to irreversible over-hydrogenation and loss of Ir–O/N coordination. This work presents a new type of Ir hydrogenation SACs that are more durable, efficient, and tunable than supported Ir NPs, while more stable than homogeneous Ir complexes. It also offers fundamental understanding regarding ligand and support effects, as well as the evolution of Ir single-atoms under H 2 , instructing future design of stable, effective hydrogenation SACs.
A Comparison of Novel Woodstove Catalytic Combustors to Improve Low Temperature Light off and Catalyst Stability at High Temperatures and Corrosive Environments, Including Stability of Catalytic Combustors used in Coastal Environments
Wood heaters with catalytic combustors often emit higher levels of particulate matter (PM) and volatile organic compounds (VOCs) at startup before the catalytic combustor is at operational temperature. This project aims to advance wood heater catalytic combustor technology by studying degradation mechanisms in failed field catalysts and using those insights to develop an improved catalytic combustor. Findings will provide critical insights into the degradation mechanisms of wood heater catalytic combustors and inform the design of catalysts that deliver improved efficiency, durability, and performance compared to current commercial products. The outcomes of this project will not only improve catalytic combustor technology but also contribute to operational guidelines to extend catalyst lifetimes.
Zeolite Nanosheets Stabilize Catalyst Particles to Promote the Growth of Thermodynamically Unfavorable, Small–Diameter Carbon Nanotubes
A challenge in the synthesis of single–wall carbon nanotubes (SWCNTs) is the lack of control over the formation and evolution of catalyst nanoparticles and the lack of control over their size or chirality. Here, zeolite MFI nanosheets (MFI–Ns) are used to keep cobalt (Co) nanoparticles stable during prolonged annealing conditions. Environmental transmission electron microscopy (ETEM) shows that the MFI–Ns can influence the size and shape of nanoparticles via particle/support registry, which leads to the preferential docking of nanoparticles to four or fewer pores and to the regulation of the SWCNT synthesis products. The resulting SWCNT population exhibits a narrow diameter distribution and SWCNTs of nearly all chiral angles, including sub–nm zigzag (ZZ) and near–ZZ tubes. Theoretical simulations reveal that the growth of these unfavorable tubes from unsupported catalysts leads to the rapid encapsulation of catalyst nanoparticles bearing them; their presence in the growth products suggests that the MFI–Ns prevent nanoparticle encapsulation and prologue ZZ and near–ZZ SWCNT growth. Furthermore, these results thus present a path forward for controlling nanoparticle formation and evolution, for achieving size– and shape–selectivity at high temperature, and for controlling SWCNT synthesis.
Enhancement of Copper Catalyst Stability for Catalytic Ozonation in Water Treatment Using ALD Overcoating
Abstract not provided
Structural Evolution and Stability of Rh/TiO 2 Catalysts under CO 2 Hydrogenation Conditions: Influence of the Initial Rh Structure
Characterizing catalyst stability by identifying the predominant mechanisms, timescales and driving forces of catalyst reconstruction under relevant reaction conditions is necessary for the design and commercialization of new catalysts. Here, in this paper, we study Rh/TiO 2 catalysts under CO 2 hydrogenation conditions (773 K, 75% H 2 , 25% CO 2 ) at high conversion and utilize reactivity studies along with ex-situ and in-situ spectroscopy and microscopy to characterize changes in catalyst activity and structure as a function of time on stream and the initial catalyst structure. This is a prototypical catalyst for CO 2 hydrogenation where Rh structure and Rh-TiO 2 interactions have been proposed to explain reactivity, selectivity (between CO and CH 4 formation) and catalyst stability. The influence of the initial Rh structure (varying from Rh single atoms to Rh nanoparticles), support stability, regeneration and pretreatment(s), and the chemical potential(s) of the reaction environment on reaction selectivity and catalyst stability were explored. The product selectivity between CO and CH 4 was determined to be dependent on the relative fraction of Rh single atoms and Rh nanoparticle-TiO 2 interfacial sites under reaction conditions, each exhibiting distinct stability under prolonged time on stream. Surprisingly, Rh single atoms exhibited stability for the duration of 90 h reactivity measurements, even at high Rh density (≥ 1.8 Rh atoms/nm 2 ) on the support, while Rh nanoparticles sintered under reaction conditions. As a result, all catalysts exhibited increasing selectivity to CO with increasing time on stream (> 10 h). We conclude the distribution of Rh structures evolved over time under reaction conditions through three distinct reconstruction mechanisms (Rh particle fragmentation, Ostwald ripening, and particle migration and coalescence) that occurred on varying timescales. Catalyst stability on the ~90 h time scale was ultimately controlled by the initial Rh structure.
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.
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.
Synergistic effect of polyaniline on stabilizing Pt nanoparticles in PEMFCs†
The stability of Pt nanoparticles on a carbon support is crucial for the lifespan of polymer electrolyte membrane fuel cells as well as other electrocatalysis systems such as electrolyzers. Here we took the approach of utilizing the covalently grafted polyaniline on carbon to stabilize Pt nanoparticles by simultaneously alleviating the particle migration and mitigating the Ostwald ripening, which are two major mechanisms for loss of the catalyst stability. A comprehensive investigation of the stability and performance of Pt catalyst nanoparticles on these supports reveals that the polyaniline can shift the Pt L edge binding energy and the Pt 4f peak energy, leading to the increased redox potential of the Pt nanoparticles and making them more resistant to oxidation. Interestingly, the highest polyaniline density (50 wt%) does not show the best catalyst stability, rather, the second (33 wt%) demonstrates the best catalyst stability among these catalysts. Combining the XPS, XAS and fuel cell stability studies, we concluded that the locations of the Pt nanoparticles over the polyaniline layer on the carbon surface depend on the surface density of the polyaniline over the carbon surface. The Pt nanoparticles in the 50 wt% polyaniline catalyst are wrapped by the polyaniline polymer but do not sit directly on the carbon surface, while Pt nanoparticles in the 33 wt% polyaniline catalyst sit on the carbon surface and are densely surrounded by the polyaniline polymer. The results show that the mass activity loss is 12.5% while the ECSA (electrochemically active surface area) loss is 37.1% after 30k cycles of accelerating stress test for the 33 wt% polyaniline catalyst, far exceeding the DOE 2020 target for MEA (i.e., mass activity loss < 50%, and ECSA loss < 40%). Overall, the polyaniline has a synergistic effect on mitigating the surface migration and slowing down the Ostwald ripening to stabilize the Pt nanoparticles in fuel cells. The novel strategy to stabilize Pt nanoparticles using polyaniline opens a new pathway in the development of highly stable catalysts: relying on the functionalization group on the carbon support, instead of just focusing on the catalyst itself.
MgO(111) Nanocatalyst for Biomass Conversion: A Study of Carbon Coating Effects on Catalyst Faceting and Performance
Solid base metal oxide catalysts such as MgO offer utility in a wide variety of syntheses from pharmaceuticals to fuels. The (111) facet of MgO shows enhanced, unique properties relative to the other facets. Carbon coatings have emerged as a promising modification to impart metal oxide catalyst stability. Here, we report the synthesis, characterization, and catalytic properties of commercial MgO, MgO(111), and carbon coated derivatives thereof for 2-pentanone condensation. The dimer and trimer products of this reaction can be used as precursors for biofuels upon oxygen removal and thus have relevance in environmental sustainability. Additionally, MgO(111) maintained impressive selectivity towards the dimer product after carbon coating, whereas the other catalysts experienced a decrease in conversion and selectivity as a consequence of the carbon coating. Our findings highlight the catalytic efficacy of MgO(111), provide insight into carbon coating for catalyst stability, and pave the way for continued mechanistic investigations.
A Hybrid Pathway to Biojet Fuel via 2,3-Butanediol
Production of biomass-derived sustainable alternative jet fuels (SAJF) has been considered as an important approach to decarbonize the aviation industry but still possesses various challenges in technology advancement, particularly in achieving high carbon efficiency. Here we report a hybrid pathway to SAJF from 2,3-butanediol (2,3-BDO), integrating biologically converting biomass to 2,3-BDO with catalytically upgrading of 2,3-BDO to jet-range hydrocarbons. This pathway is demonstrated to have a high carbon recovery to liquid hydrocarbons from corn stover (25–28%) (74–82% of the theoretical maximum efficiency). The catalytic conversion steps involve 2,3-BDO to C3+ olefins, oligomerization, and hydrogenation where the first two steps are the focus of this study. Under optimum reaction conditions (523 K, 115 kPa, 1.0 h-1 weight hourly space velocity), 2,3-BDO conversion and C3+ olefin selectivity are >97% and 94–98% during 40 h time on stream, respectively. To demonstrate the adaptability of this technology with bio-derived 2,3-BDO, we also investigated the impact of water and other organic coproducts (acetoin and acetic acid) inherited from the fermentation broth on the catalyst performance and product selectivities. We have shown that the catalyst can handle a significant amount of water in the liquid feed (40 wt% water/60 wt% 2,3-BDO) and maintain catalyst stability for ~40 h. Acetoin can be converted to similar C3+ olefins as 2,3-BDO with complete conversion of acetoin. Co-feeding 10 wt% acetoin with 2,3-BDO is found to have no impact on 2,3-BDO conversion, C3+ olefin selectivity, and catalyst stability. The utilization of organic coproduct like acetoin can help to improve overall carbon conversion efficiency when using real biomass-derived 2,3-BDO. On the other hand, the presence of 10 wt% acetic acid is shown to drastically inhibit methyl ethyl ketone (MEK) hydrogenation and butene oligomerization as revealed by the increased MEK and butene selectivities, implying the importance of separating organic acids when feeding bio-derived 2,3-BDO. The formed C3–C6 olefins from 2,3-BDO are further oligomerized over Amberlyst-36 catalyst to longer-chain hydrocarbons with >70 wt% jet-range hydrocarbons including predominantly iso-olefins/iso-paraffins. The overall carbon efficiency for the jet-range hydrocarbons is 19–22%, exceeding most of the reported biojet pathways, which makes it a promising approach for SAJF production.
Accelerated optimization of pure metal and ligand compositions for light-driven hydrogen production
Photocatalytic hydrogen production is a promising alternative to traditional hydrogen production. To implement photocatalytic hydrogen production the development of efficient, sustainable, and stable catalysts is necessary, and overcoming the current challenges surrounding high dimensional search spaces requires both computational and experimental efforts. Utilizing photo driven processes, stable colloidal metal catalysts can be formed in situ for efficient hydrogen production from water. When considering colloidal catalysts, stability is typically a concern solved through the addition of supports or ligands. In this work, poly(ethylene glycol) methyl ether thiol acts as a stabilizing ligand eliminating the need for catalyst supports while providing stable and active nanoparticle catalysts for more than 45 hours of reaction time and illumination. These systems utilize molecular photosensitizers, water reduction catalysts, stabilizing ligands, water, a sacrificial reductant, and organic solvents, posing new challenges pertaining to the optimization of multi-variable systems. Design of experiments (DOE) is applied to accelerate the understanding of variable interactions and is used as a tool to rapidly optimize the compositions of Au, Cu, Ni, and Fe containing systems. Through a collaboration leveraging computation and experimentation (both high throughput and characterizations), optimized performance peaks were obtained for each of these metals alongside distinct mapping of expected activity associated with photosensitizer, metal, and ligand concentration variations. With the highly digitized workflow, this study allowed for comparative generalizations to be made regarding photo driven hydrogen production for all four metals.
Performance and long-term stability of CO 2 conversion to formic acid using a three-compartment electrolyzer design
The electrochemical reduction of CO 2 to formate and formic acid has attracted a great amount of academic and commercial interest over the past five years. A number of experimental studies have generated data on the Faradaic performance and stability of various candidate catalyst materials in producing formate or formic acid. However, most of the data has been conducted at low current densities and over short time periods, typically hours to days. There is a critical need in providing long-term catalyst stability as well as electrolyzer-based operating data, which are needed for the commercial scale-up and operation of this technology, especially at high current densities. In this paper, the electrochemical CO 2 conversion to pure formic acid was conducted using a three-compartment design electrolyzer, demonstrating electrolyzer catalyst and performance stability for over 1000 h at current densities up to 200 mA cm -2 . Depending on the operation conditions, the electrolyzer directly produced a 6.03 to 12.92 wt% (1.3 to 2.8 M) formic acid product at Faradaic efficiencies ranging between 73.0 to 91.3%. Data on electrolyzer performance, including formic acid product generation rate, energy efficiency, and energy consumption are reported at three different current densities, 100, 200, and 250 mA cm -2 . Finally, a long term 1000 h electrolyzer stability run at 200 mA cm -2 is presented, providing information on the operating conditions required in obtaining stable electrolyzer performance. All the data will be extremely useful in the commercial scale-up of this technology.
Predicting Catalyst Surface Stability Under Reaction Conditions Using Deep Reinforcement Learning and Machine Learning Potentials
Catalysts are critical for most large-scale energy intensive chemical transformation processes, such as energy storage, liquid fuel production, and the formation of chemical building blocks. The catalyst composition, structure, and morphology impact the performance under reaction conditions and influences properties like activity and selectivity. Many industrial catalysts offer imperfect activity/selectivity, or contain expensive metals. Further, catalysts can deactivate over time as the morphology changes or harsh reactive environments alter the surface structure. Methods to automatically model and predict the kinetics of how catalyst surfaces will restructure would enable engineers to design around these challenges, improve performance, increase longevity. This project investigated a specific type of machine learning model, deep reinforcement learning, machine learning models to act as surrogates for the physical system, and compared the results of these approaches with a specialized high-throughput experimental synthesis and measurement platform.