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At least 577 records · Page 32

A Machine Learning Model for Predicting Composition of Catalytic Coprocessing Products from Molecular Beam Mass Spectra

Demand for the development of an automated and integrated refining process for biofuels has increased in recent years due to the lack of generalized process inspection tools. In bio-oil upgrading processes, all process variables are maintained based on the offline specification of intermediates and products. A lack of real-time product specifications in batch-wise monitoring can cause process failure and wasted resources. Therefore, there is a need for a fast and accurate intermediates/product specification tool that can be used for real-time specification to reduce waste and mitigate the risk of process failure. Here, to address this gap, we developed a machine learning (ML) model for predicting speciated bio-oil composition, including paraffin, iso-paraffins, olefins, naphthene, and aromatics. The model is trained using the mass spectra from upgraded products collected in the vapor phase before condensation and predicts the composition of the condensed product. Training ML models using raw mass spectra is challenging due to numerous overlapped peaks originating from different parent compounds. With this in mind, we propose a protocol that (i) transforms raw mass spectra to chemistry-inspired predefined features and (ii) trains decision tree-based models using these features. Our results show that the random forest model was robust against overfitting and had the highest accuracy compared to other models. Moreover, a stochastic ablation method determined the eight most significant features while maximizing the accuracy. Our protocol facilitates real-time compositional analysis of upgraded bio-oils and thus real-time process monitoring. Additionally, this protocol enables the rational design of efficient catalysts and the determination of optimal process conditions.

09 BIOMASS FUELS↗

Direct extraction of lithium from ores by electrochemical leaching

With the rapid increase in lithium consumption for electric vehicle applications, its price soared during the past decade. To secure a reliable and cost-effective supply chain, it is critical to unlock alternative lithium extraction resources beyond conventional brine. In this study, we develop an electrochemical method to directly leach lithium from α-phase spodumene. We find the H 2 O 2 promoter can significantly reduce the leaching potential by facilitating the electron transfer and changing the reaction path. Upon leaching, β-phase spodumene shows a typical phase transformation to HAlSi 2 O 6 , while leached α-phase remains its original crystal phase with a lattice shrinkage. To demonstrate the scale-up potential of electrochemical leaching, we design a catalyst-modified high-throughput current collector for high loading of suspended spodumene, achieving a leaching current of 18 mA and a leaching efficiency of 92.2%. Electrochemical leaching will revolutionize traditional leaching and recycling processes by minimizing the environmental footprint and energy consumption.

25 ENERGY STORAGE↗

The role of atomic carbon in directing electrochemical CO (2) reduction to multicarbon products

Electrochemical reduction of carbon-dioxide/carbon-monoxide (CO (2) R) to fuels and chemicals presents an attractive approach for sustainable chemical synthesis, but it also poses a serious challenge in catalysis. Understanding the key aspects that guide CO (2) R towards value-added multicarbon (C 2+ ) products is imperative in designing an efficient catalyst. Herein, we identify the critical steps toward C 2 products on copper through a combination of energetics from density functional theory and micro-kinetic modeling. We elucidate the importance of atomic carbon in directing C 2+ selectivity and how it introduces surface structural sensitivity on copper catalysts. Overall, this insight enables us to propose two simple thermodynamic descriptors that effectively identify C 2+ selectivity on metal catalysts beyond copper and hence it defines an intelligible protocol to screen for materials that selectively catalyze CO (2) to C 2+ products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrophobic pockets built in polymer micelles enhance the reactivity of Cu 2+ ions

We report the hydrophobicity-enhanced reactivity of Cu2+ ions as an ester hydrolase. Using a dipicolylamine (DPA) containing reversible addition–fragmentation chain transfer agent, the synthetic sequence, either hydrophobic or hydrophilic first in amphiphilic block copolymers of polystyrene-block-poly(N'N-dimethylacrylamide) (PS-b-PDMA), was varied to control the location of the binding motif, DPA, in the hydrophobic core or on the hydrated corona of polymer micelles. The hydrophobicity of Cu 2+ sites showed a significant impact (as large as 60 times more activity) on their catalytic efficiency towards ester hydrolase. With two different kinetic modes, including Michaelis–Menten and the reverse saturation kinetics models, the binding constant Kb of the substrates to Cu 2+ sites were quantitatively analyzed and we demonstrate that hydrophobicity favors the binding of the substrates to Cu2+ sites at polymer micelles with smaller sizes, however, K b decays exponentially with micellar diameters. Despite the diffusion barrier, hydrophobicity shows a profound impact on the catalytic rate constant kc that measures the single conversion rate of bound substrates to products. There is a 16–20 times kinetic enhancement in the hydrolase activity, completely endowed by the hydrophobic microenvironment of Cu 2+ sites compared to micelles with similar sizes. Our results indicate how the hydrophobicity of Cu 2+ -containing micelles can impact the catalytic efficiency and potentially illustrate a promising way toward the design of bioinspired catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface chlorination of IrO2(110) by HCl

The ability to controllably chlorinate metal-oxide surfaces can provide opportunities for designing selective oxidation catalysts. In the present study, we investigated the surface chlorination of IrO2(110) by HCl using temperature programmed reaction spectroscopy (TPRS), x-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. We find that exposing IrO2(110) to HCl, followed by heating to 650 K in ultrahigh vacuum, produces nearly equal quantities of on-top and bridging Cl atoms on the surface, Clt and Clbr, where the Clbr atoms replace O-atoms that are removed from the surface by H2O formation. After HCl adsorption at 85 K, only H2O desorbs at low Cl coverages during TPRS, but HCl begins to desorb in increasing yields as the Cl coverage is increased above about 0.5 monolayer (ML). The desorption of Cl2 was not observed under any conditions, in good agreement with the high barrier for this reaction predicted by DFT. A maximum Cl coverage of 1 ML, with nearly equal coverages of Clt and Clbr atoms, could be generated by reacting HCl with IrO2(110) in UHV. Our results suggest that a kinetic competition between recombinative HCl and H2O desorption under the conditions studied limits the saturation Cl coverage to a value less than the 2 ML maximum predicted by thermodynamics. XPS further shows that the partitioning of Cl between the Clt and Clbr states can be altered by subjecting partially chlorinated IrO2(110) to reductive or oxidative treatments, demonstrating that the Cl site population can change dynamically in response to the gas environment. Our results provide insights for understanding the chlorination of IrO2(110) by HCl and can enable future experimental studies to determine how Cl-modification alters the surface chemical reactivity of IrO2(110) and potentially enhances selectivity toward partial oxidation chemistry.

Chemistry↗

Achieving industrial ammonia synthesis rates at near-ambient conditions through modified scaling relations on a confined dual site

The production of ammonia through the Haber–Bosch process is regarded as one of the most important inventions of the 20th century. Despite significant efforts in optimizing the process, it still consumes 1 to 2% of the worldwide annual energy for the high working temperatures and pressures. The design of a catalyst with a high activity at milder conditions represents another challenge for this reaction. Herein, we combine density functional theory and microkinetic modeling to illustrate a strategy to facilitate low-temperature and -pressure ammonia synthesis through modified energy-scaling relationships using a confined dual site. Our results suggest that an ammonia synthesis rate two to three orders of magnitude higher than the commercial Ru catalyst can be achieved under the same reaction conditions with the introduction of confinement. Such strategies will open pathways for the development of catalysts for the Haber–Bosch process that can operate at milder conditions and present more economically viable alternatives to current industrial solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An uncharacteristically low-potential flavin governs the energy landscape of electron bifurcation

Significance Nature has long been an inspiration for materials design, as it exemplifies exquisite control of both matter and energy. Electron bifurcation, a mechanism employed in biological systems to drive thermodynamically unfavorable and energetically challenging chemical reactions, is one such example. A key feature of bifurcating enzymes is the ability of a single redox cofactor to distribute a pair of electrons across two spatially separated electron transfer pathways. Here, we report on the empirical determination of both the one-electron potential and two-electron potential of the bifurcating flavin cofactor in the NADH-dependent ferredoxin-NADP + oxidoreductase I (NfnSL) enzyme. Insights arising from the defined energy landscape of this bifurcation site may underlie the design of synthetic catalysts capable of generating high-energy intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering competing elementary steps to correlate electrocatalyst chemical state with activity

The overpotential in multielectron transfer heterogeneous electrocatalysis fundamentally arises from thermodynamic and kinetic disparities among elementary steps; however, deciphering coupled and competing steps has long remained a challenge. Here, we establish an electrochemical deconvolution paradigm based on key processes in electrocatalytic reactions, such as charge accumulation, electron/proton transfer, and intermediate evolution, to resolve competing elementary steps. Taking the oxygen evolution reaction as a prototypical reaction, we design a model catalyst featuring a precise isolated cation-anion vacancy pair and track the previously elusive electrochemical behavior of lattice oxygen by disentangling interference from adsorbed oxygen intermediates. Mechanistically, the lattice oxygen oxidation pathway originates from the spontaneous, nonelectrochemical deprotonation of replenished water molecules coordinated to unsaturated cation sites. Alternating current techniques further reveal that although lattice oxygen oxidation requires a higher potential than metal oxidation, it exhibits faster kinetics, providing insight into its superior catalytic activity. These findings establish a direct experimental correlation between the initial chemical state and the catalytic activity and prove surface-confined lattice oxygen cycling. Furthermore, expanding conventional potential-current analysis into a multidimensional framework enables disentanglement of thermodynamic and kinetic contributions of key elementary steps, thereby guiding the rational optimization of various complex multielectron transfer reactions.

OER↗

Bringing Inorganic Carbon to Life: Developing Model Metalloenzymes for C1 Conversion Reactions

The global carbon cycle is carefully balanced through the use of specialized enzymes in plants, algae, bacteria, and archaea. A primordial metabolic pathway for the conversion of inorganic carbon into cellular biomass uses a large, nickel-containing enzyme called carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS). This system fixes carbon dioxide (CO 2 ) into carbon monoxide (CO) at the CODH site. The carbon monoxide is then used to generate acetyl coenzyme A, a biological building block, through a key carbon-carbon bond forming step at the nickel site in ACS. Despite the significance of these processes in the context of energy conversion, the fundamental chemistry underlying these transformations has remained elusive, in part due to the complexity of the natural enzyme. To better understand the principles governing these biological processes, which represent one-carbon (C 1 ) activation reactions, this project will develop functional models of CODH and ACS based on modifications to a small metalloprotein scaffold. Comprehensive characterization of these systems using advanced spectroscopic and biophysical techniques will reveal key elements responsible for conferring high levels of activity to the model systems, with implications for gaining insight into the mechanisms of the natural enzymes. Moreover, the principles learned from this research can be used to guide design of robust catalysts for efficient conversion of CO 2 and CO into liquid fuels.

10 SYNTHETIC FUELS↗

C-C Coupling Mechanism on Cu(100) A Molecular Dynamics Study at 298K

The electrochemical reduction of carbon dioxide (CO2) into valuable fuels such as C1 (syngas, methane) and C2 (ethylene, ethanol) products is a key strategy for achieving a carbon-neutral economy. Computational studies of C-C coupling, a critical step in CO2 reduction, are essential for designing more efficient catalysts. However, simulating these processes under realistic electrochemical conditions, including temperature and solvent effects, is computationally demanding. In this work, we develop a machine learning-based atomistic potential to study CO2 reduction on Cu(100) surfaces, accounting for temperature and explicit water solvent effects. We compute thermodynamic free energies of the possible C-C coupling pathways, CO*+CO*→OCCO*, CO*+CHO*→OCCHO*, CO*+COH*→OCCOH*, CHO*+COH*→OHCCOH*, COH*-COH*→HOCCOH*, and CHO*-CHO*→OHCCHO*. Our results quantify the thermodynamic tendencies of these reactions and reveal that, in addition to the well-established CO* + CO* → OCCO* pathway, CHO* is a critical intermediate in the formation of C2 products on Cu(100). Furthermore, we demonstrate that the machine learning approach offers a cost-efficient framework for studying CO2 reduction on diverse catalysts under realistic electrochemical conditions.

machine learning↗

Descriptors for Cu facets for CO2 reduction reaction activity

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO2R) reduction to valuable hydrocarbons and oxygenates. Herein, leveraging density functional theory calculations of the CO adsorption energy ΔE_CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE_CO and the recently experimentally measured CO2R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining the ab initio thermodynamics of the early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically preferred step, and notably shows a volcano trend with the experimental currents where the maximum CO2R current corresponds to the moderate CHO* formation energy. Importantly, we show that increasing the step and kink density of the Cu termination not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. We also explain why (741) is exceptional with high CO2R activity as measured experimentally due to its relatively low activity toward the hydrogen evolution reaction compared with the other Cu surfaces. Beyond the general CO adsorption energy that only shows a linear trend with CO2R activity, we show that the reaction CO* → CHO* free energy is a descriptor that displays a volcano relationship with the overall CO2R activity on Cu facets.

machine learning↗

Comparison of Approaches for CO 2 Sequestration as Solid Carbon Products

The growing global climate crisis linked to the rising atmospheric CO 2 levels calls for urgent and innovative solutions. Fixing CO 2 as valuable solid carbon products, such as carbon nanofibers or nanotubes (CNFs or CNTs), offers a promising way to potentially achieve net-negative CO 2 emissions. However, direct CO 2 -to-solid carbon faces significant thermodynamic and kinetic constraints, especially under mild reaction conditions. This mini-review compares three emerging approaches for CO 2 conversion into solid carbon: 1) using molten salt at high temperatures to produce CNFs or CNTs, 2) converting CO 2 to amorphous carbon with pyrophoric liquid metals at near room temperature, and 3) employing an electrocatalytic-thermocatalytic tandem process to produce CNFs at relatively mild temperatures. We examine the underlying principles, thermodynamic driving forces, and recent advances of each approach, and discuss the challenges and opportunities in catalyst development, reactor design, and energy management. We aim to highlight CO 2 fixation, facilitate net-negative CO 2 emissions, and stimulate more innovations for both environmental and economic benefits.

99 GENERAL AND MISCELLANEOUS↗

Activation of propane on Ag–PdO(101) model surfaces

Oxidation of alkanes remains a central challenge in catalysis due to the high activation barriers of C–H bonds and the thermodynamic favorability of complete oxidation. Palladium oxide (PdO), particularly its (101) facet, is known for its high reactivity in alkane oxidation, which is attributed to its coordinatively unsaturated palladium (Pd) and O atoms. In this study, we investigate the effect of silver (Ag) incorporation on the oxidation behavior of propane over PdO(101) using temperature-programmed reaction spectroscopy (TPRS) under controlled conditions. While pristine PdO(101) exhibits complete oxidation of propane with CO₂ and H₂O desorption at high temperatures (approximately 475 K), Ag incorporation induces a new CO₂ desorption peak at significantly lower temperatures (approximately 330 K). This shift is attributed to the formation of new active sites at the Ag–PdO(101) interface. Quantitative analysis reveals that low-temperature activity correlates with Ag coverage, while overall CO₂ production decreases, suggesting a redistribution of reactivity rather than an increase in active surface area. Activation energy estimations using the Redhead method confirm that C–H bond activation becomes more facile at the interface, with a 46 kJ/mol reduction compared to pristine PdO(101). These findings demonstrate that incorporating a less reactive metal such as Ag into PdO surfaces not only modifies the reaction energetics but also enables the design of bimetallic catalysts with improved selectivity for partial oxidation reactions.

Chemistry↗

Theoretical investigation of gas-surface interactions

The goal of this project was to develop computational tools for the calculation of the electronic structure of molecules containing heavy atoms, and to use these tools in the study of catalytic processes, with the overall objective of gaining an understanding of the catalytic process which could be used to design more efficient catalysts. The main catalytic system of interest was the combustion of hydrogen on platinum surfaces. Under this project, a flexible Dirac-Hartree-Fock (DHF) program has been developed, a code to calculate DHF correlation energies at the second-order Moeller-Plesset perturbation (PP2) level is almost complete, and code to include correlation at the MCSCF and MCSCF/MP2 level is planned. The tools so far developed have been validated and used to calibrate some more approximate methods, and applied to investigate the importance of relativistic effects in the bonding of hydrogen to platinum.

Dyall, Kenneth G.↗

Using ethanol and isopropanol as biomass model compounds for understanding bond scission mechanisms over Cu/Mo 2 N catalysts

The conversion of biomass compounds into fuels and chemicals is an important step towards a more sustainable future. This work combines results from model surfaces and powder catalysts to demonstrate Cu-modified mo- lybdenum nitride (Cu/Mo 2 N) as a selective catalyst for dehydrogenation of the biomass model compounds, ethanol and isopropanol. Results from model surfaces showed that while Mo2N led to unselective decomposition via both dehydrogenation and dehydration, the addition of Cu increased the dehydrogenation activity and selectivity. DFT calculations showed how Cu influenced the structures of active sites, adsorbate interactions, and thus the product selectivity. Batch reactor studies on corresponding powder catalysts confirmed the trend that Cu modification increased dehydrogenation activity, and in situ X-ray absorption spectroscopy elucidated the Cu oxidation state under reaction conditions. Further, this work demonstrates a strategy for promoting dehydrogenation over Mo 2 N-based catalysts, as well as the feasibility of using model surfaces to guide the design of industrially relevant catalysts.

09 BIOMASS FUELS↗

Catalyst Deactivation and Its Mitigation during Catalytic Conversions of Biomass

Biofuel or biochemical production from biomass, especially lignocellulosic biomass, is the most promising option to replace fossil-based products to achieve sustainability. However, biomass is currently under-utilized because biomass conversion technologies have faced significant challenges to compete with incumbent petroleum technologies. Advancement in catalysis plays a central role in increasing the readiness of biomass conversion technologies. In this respect, improving catalyst stability is one of the well-known grand challenges for biomass conversion catalysis, which impedes the scaling up and commercialization of many biomass conversion techniques. In comparison to conventional processing of fossil fuels (petroleum, coal, and natural gas), biomass conversion is largely challenged by three unique properties of biomass-derived feedstocks—high water and oxygen content, high degree and reactivity of oxygen functionalization, and high contamination by minerals and heteroatoms—which all cause greater catalyst deactivation in different ways. Therefore, research on catalyst deactivation mitigation and catalyst regeneration is extremely important for the development of biomass conversion technologies. This review aims to highlight studies on catalyst deactivation and mitigation for catalytic processes in biomass conversion, with emphasis on the deactivation caused by the three unique characteristics of biomass-derived feedstocks. Further, this work will provide information on correlating the characteristics of biomass-derived streams, their potential impact on catalyst lifetime, and a potential mitigation approach, which could guide a more rational design of a robust catalyst and processes for biomass conversion.

09 BIOMASS FUELS↗

Scalable Gas Diffusion Electrode Fabrication for Electrochemical CO 2 Reduction Using Physical Vapor Deposition Methods

Electrochemical CO 2 reduction (ECR) promises the replacement of fossil fuels as the source of feedstock chemicals and seasonal storage of renewable energy. While much progress has been made in catalyst development and electrochemical reactor design, few studies have addressed the effect of catalyst integration on device performance. Using a microfluidic gas diffusion electrolyzer, we systematically studied the effect of thickness and the morphology of electron beam (EB) and magnetron-sputtered (MS) Cu catalyst coatings on ECR performance. We observed that EB-Cu outperforms MS-Cu in current density, selectivity, and energy efficiency, with 400 nm thick catalyst coatings performing the best. Additionally, the superior performance of EB-Cu catalysts is assigned to their faceted surface morphology and sharper Cu/gas diffusion layer interface, which increases their hydrophobicity. Tests in a large-scale zero-gap electrolyzer yielded similar product selectivity distributions with an ethylene Faradaic efficiency of 39% at 200 mA/cm 2 , demonstrating the scalability for industrial ECR applications.

36 MATERIALS SCIENCE↗

Discovering Ni/Cu Single-Atom Alloy as a Highly Active and Selective Catalyst for Direct Methane Conversion to Ethylene: A First-Principles Kinetic Study

Direct methane conversion to liquid fuels or value-added chemicals is a promising technology to utilize natural resources without resorting to further petroleum extraction. However, discovering efficient catalysts for this reaction is challenging due to either coke formation or unfavorable C-H bond activation. Herein, we design single-atom alloy (SAA) catalysts to simultaneously eliminate the above two bottlenecks based on mechanism-guided strategies: (1) the active single atom enables favorable C-H bond breaking and (2) the less reactive host metal facilitates C-C coupling and thus avoids strong binding of carbonaceous species. Employing electronic structure theory calculations, we screened the stability of multiple SAAs with 3d-5d transition metals atomically dispersed on a copper surface in terms of avoiding dopant aggregation and segregation. We then evaluated reactivities of the stable SAAs as catalysts for direct methane conversion to C2 products, including methane dehydrogenation and C-C coupling mechanisms. Combining selectivity analysis with kinetic modeling, we predicted that nickel dispersed on copper, i.e., Ni/Cu SAA, is a highly active and selective catalyst that can efficiently transform methane to ethylene. This work designs efficient SAA catalysts for direct methane activation and provides chemical insights into engineering compositions of SAAs to tune their catalytic performances.

Kothakonda, Manish↗