Catalyst Screening Research Articles

Screening of dual-atom catalysts for hydrogen evolution reaction on graphdiyne

Screening of dual-atom catalysts for hydrogen evolution reaction on graphdiyne

Limonene oxide isomerization: a broad study of acid catalyst effects

AbstractIn this work, a broad screening of possible catalysts for limonene oxide isomerization was performed. The catalysts included both Brønsted and Lewis acids as homogeneous or heterogeneous catalysts. The aim was to show the efficiency of different catalysts in the studied reaction and use one homogeneous (methanesulfonic acid) and two heterogeneous (zeolite beta-25, montmorillonite K10) catalysts to evaluate the influence of the acid site type on the selectivity. When the selected catalysts were used, almost total conversion up to 1 h was observed (2?50% of the catalyst was based on type, 80 °C, and 16.6 V% of the solution was limonene oxide in toluene). The strength of the acid/acid catalyst influenced the composition of the products. When a strong acid (methanesulfonic acid) was used, the products formed by dehydration (p-cymene) and isomerization of the double bond (carvenone) were detected in large amounts. Using the majority of catalysts, the main products were cis- and trans-dihydrocarvone, and the minor products were carveols and carvone. The water content of the acid catalyst strongly affected the selectivity. Limonene diol was formed as a hydration product, which decreased the selectivity for the desired products. We have described a wide spectrum of possible catalysts for limonene isomerization. Moreover, our study enables the simple choice of catalyst on the basis of the desired composition of the products.

Density Functional Theory Study on Screening and Key Metrics for Non-metallic Oxygen Reduction Catalysts.

This study systematically investigates the oxygen reduction reaction (ORR) catalytic activity of graphene doped with various non-metallic impurities. The non-metal elements include boron (B), silicon (Si), nitrogen (N), phosphorus (P), arsenic (As), oxygen (O), sulfur (S), selenium (Se), tellurium (Te), fluorine (F), chlorine (Cl), bromine (Br), and iodine (I). We found that adsorbates tend to adsorb on positively charged impurity atoms. We identified several substrates with good catalytic activity, all of which have an ORR overpotential of around 0.6 V. We further verified the thermodynamic stability of these substrates and found them to be very stable. We summarized the optimal adsorption energies for ORR intermediates O2H, O, and OH to be -1.9, -3.4, and -2.4 eV, respectively, and validated their reasonableness. Finally, we used simple linear functions to fit the relationship between the adsorption energies of O2H, O, and OH and the charge and magnetic moment of the adsorption site atoms. This model can roughly predict the ORR catalytic activity of doped graphene, facilitating the faster screening of excellent ORR catalysts.

Computational screening of single-cluster catalysts anchored on g-C3N4 for nitroreduction of 3-nitro-1,2,4-trizole-5-one (NTO)

3-nitro-1,2,4-triazole-5-one (NTO) is widely used as an insensitive explosive in high-safety weapon systems; however, it poses significant environmental risks due to its high solubility and anionic nature. Despite 3-amino-1,2,4-triazole-5-one (ATO) has been identified as the key intermediate during NTO degradation, developing highly active and selective catalysts for the NTO to ATO process remains challenging. Using computational screening with density functional theory (DFT), ab initio molecular dynamics (AIMD) simulations, and enhanced sampling approach, this study presents a rational design among metal trimer (M3, where M = Ag, Au, Cu, Ir, Os, Pt, Pd, Rh, and Ru) cluster anchored on N-vacancy and perfect graphitic carbon nitride (g-C3N4) as robust single-cluster catalysts (SCCs) with promising efficiency for NTO nitroreduction. Through a three-step process involving structural optimization, AIMD simulation, and enhanced sampling calculation, we found that Ru shows remarkable activity and selectivity for NTO nitroreduction, particularly in a solvent environment with a higher concentration of H. Notably, the Ru3@1CN SCC demonstrates the ability to directly reduce NTO to ATO in the first two steps. This work opens new avenues for NTO nitroreduction in contamination control and production of functionalized chemicals, providing valuable guidance for selective hydrogenation of other nitro compounds as well.

Diatomic nitrogen-fixation electrocatalysts supported on graphitic carbon nitride achieve significantly low over potentials

The construction and screening of diatomic catalysts (DAC), as well as the exploration of intrinsic descriptors, are attracting increasing attention. In this work, using graphitic carbon nitride (g-CN) as the substrate, we assembled W, Mo, Cr, Mn, Fe, Co, and Ni atoms into DAC and conducted a systematic exploration of the catalytic capabilities of these systems for nitrogen reduction reaction (NRR) using first-principles calculations. Our research demonstrates that MoMn@g-CN exhibits outstanding catalytic activity and selectivity among the investigated 28 catalysts. The overpotential for NRR on MoMn@g-CN along the enzymatic pathway is merely 0.10 V, which is lower than most of the reported catalysts. By conducting in-depth electronic structure calculations, the catalytic mechanism of the DAC is investigated. N2 adsorption and activation are influenced by the σ-acceptor-π∗-donor mechanism. The enhanced activation of nitrogen molecules is attributed to the synergistic effect of two hetero-diatomic species. Moreover, we have identified an new intrinsic descriptor for NRR related to the electronegativity of the two transition metal atoms. This descriptor correlates with the volcano plot of NRR's limiting potential. Our findings can provide valuable insights for the design and high-throughput screening of DAC.

Enabling Unfavorable Hydroamination Reactions Using a Chemoselective N-O Bond Reduction.

Despite major advances, intramolecular alkene hydroamination reactions often face limitations. Herein, a redox-enabled process featuring oxidation of an amine to a hydroxylamine, a concerted hydroamination step, followed by catalytic reduction of N-oxide is shown to be broadly applicable. Catalyst screening and optimization showed that a K2OsO2(OH)4-pinacol complex rapidly and chemoselectively reduces the N-oxide cycloadduct in the presence of hydroxylamine and dimethyl sulfoxide. This selectivity was exploited to drive the equilibria toward complex products.

Catalyst screening for conversion of Chlorella sp. to aromatic fuel additives: A sustainable strategy for CO2 capture

Developing biofuels with characteristics similar to current fossil fuels and compatibility with existing petroleum infrastructure (drop-in biofuels) is gaining prominence, aligning with global efforts towards carbon-neutral economies and decarbonization of the transportation sector. The originality of the current study involves two directions: first, the use of Chlorella sp. microalgae, cultivated under simulated post-combustion gas, as a raw material for producing drop-in biofuel precursors; and second, an investigation of the catalytic activity of hierarchical zeolites in the deoxygenation and denitrogenation of volatile pyrolysis products, enhancing hydrocarbon content. To accomplish this, a micro-furnace-type temperature-programmable pyrolyzer coupled with chromatographic separation and mass spectrometry detection (Py-GC/MS) was utilized to assess the upgrading effectiveness of distinct zeolites (faujasite-type, MFI-type, and mordenite-type) on volatile pyrolysis products. All tested zeolites effectively reduced oxygenated and nitrogenated compounds in the volatile pyrolysis products, enhancing their suitability for producing renewable fuel. This supports sustainable development goals by promoting affordable, clean energy and climate action. HMor yielded the highest hydrocarbon content (98.5 %), followed by HZSM-5 (97.6 %) and HY (85.5 %). Catalytic upgrading significantly increased the concentration of aromatic hydrocarbons (at least 66.3 %), with MFI-type zeolites showing the highest selectivity for valuable BETX compounds (benzene, ethylbenzene, toluene, xylene). Hydrocarbons in the gasoline range, with up to 91.7 %, predominantly align with the needs of the transportation fuel market. The principal component analysis illustrates that using MFI-type zeolites promoted the lowest selectivity for PAHs, constituting precursors for coke formation, which is advantageous for ensuring a longer catalyst lifespan. Our results are promising and encourage the conversion of microalgal biomass into renewable fuel additives for formulating drop-in biofuels, as hydrocarbon-rich volatile pyrolysis products could be directly integrated into existing biorefineries. Thus, microalgal biomass cultivated using flue gas as the carbon source can be viewed as a versatile and promising resource for producing renewable fuel additives, contributing to developing a sustainable, low-carbon future.

Comparison of Galvanostatic and Potentiostatic Accelerated Stress Tests of Bifunctional Pt-Ir Alloy Anode Catalysts for H2 Starvation Using Rde Technique

One of the main challenges to overcome for the wide implementation of PEMFCs is the improvement of their long-term durability. For instance, the blockage of the diffusion pathway by liquid water or rapid changes of load can lead to hydrogen starvation.[1] Due to the hydrogen starvation, the anode potential increases and accelerates the carbon oxidation reaction (COR) to further supply electrons and protons for the cathode ORR half-cell reaction, also referred to as cell reversal event.[2] Aggregation and particle detachment associated with the carbon corrosion occur, resulting in a drastic loss of the PEMFC performance.[3] Therefore, material innovation solutions are needed to overcome the cell reversal events. In this context, fast and simple accelerated stress tests and set-ups are needed. Currently, galvanostatic accelerated stress tests (G-AST) at single cell level are often used to evaluate the cell reversal tolerance (CRT) of catalyst materials, which is extremely time-consuming, costly and slow.[4] On the other hand, the rotating disc electrode (RDE) technique is widely used, simple, less expensive and fast for catalyst screening. However, the electrochemical measurements of activity and durability are usually carried out in the potentiostatic mode. The research question arises whether the RDE technique is capable of evaluating the CRT behaviour of novel catalyst materials using galvanostatic AST.This systematic work compared both galvanostatic and potentiostatic accelerated stress tests (G-AST and P-AST) protocols to evaluate the degradation behaviour of novel bifunctional Pt-Ir alloy catalyst materials for hydrogen starvation. The Pt-Ir alloy catalysts with 1:1 and 3:1 ratios were prepared by wet-impregnation route. Here, the PtIr and Pt3Ir catalysts supported on Vulcan XC72 show a mean particle size of 3-5 nm and total metal loading of 35-50 wt.%Pt+Ir obtained from TEM, TGA and EDX data. In a RDE set-up equipped with three-electrode configuration, all electrochemical measurements were performed in 0.1 M HClO4 and room temperature. At begin-of-life (BoL), the performance of the Pt-Ir catalysts was evaluated by measuring the ECSA via Hupd and CO stripping methods, HOR and OER polarization curves. It is noted that the HOR polarization curves were only fitted with the diffusion limiting current due to the fast kinetics of the HOR on platinum and iridium surfaces in acidic media. For the G-AST protocol, a current density of 0.5 mA/cm2 geo was held for 10h with a cut off at 2 VRHE. The time it takes to reach 2 VRHE is referred to as the fail time (FT) and signifies the loss of the protection mechanism of catalyst materials, namely the OER activity. Based on the results from the G-AST protocol, the same FT was used to perform the chronoamperometric measurements by holding the potential at 1.6 VRHE during the P-AST protocol.At the BoL, the Pt-Ir catalysts with 3-4 nm size show sufficient ECSA values (45-50 m2/gPt+Ir via Hupd) and improved OER activity (PtIr: 23±6 A/gPt+Ir and Pt3Ir: 8±1 A/gPt+Ir @1.5 VRHE) compared to the commercial Pt/V catalyst (79±4 m2/gPt via Hupd, 6±1 A/gPt @1.5 VRHE) and IrOx (47±6 A/gIr). During the G-AST, we observed that the FT increases with higher Ir content. In addition, the Pt3Ir/V catalyst shows a significant improvement of FT compared to the Pt/V. More precisely, during the G-AST protocol, the potential of 2 VRHE by applying a constant current density of 0.5 mA/cmgeo was already reached after 15min, while for the Pt3Ir/V catalyst this took at least 1 hour. Furthermore, our data shows that the G-AST protocol is more aggressive compared to the P-AST to evaluate the catalyst aging processes.Altogether, we showed the influence of galvanostatic and potentiostatic ASTs for rapid benchmarking of novel bifunctional cell reversal tolerant Pt-Ir alloy catalysts using the three-electrode RDE technique. This study can be helped to improve the electrochemical results obtained from the RDE to the catalyst coated membranes.[1] Marić, R. et al.Towards a Harmonized Accelerated Stress Test Protocol for Fuel Starvation Induced Cell Reversal Events in PEM Fuel Cells: The Effect of Pulse Duration. J. Electrochem. Soc., 2020, 167, 124520.DOI: https://doi.org/10.1149/1945-7111/abad68[2] Chen W. et al.: Thickness effects of anode catalyst layer on reversal tolerant performance in proton exchange membrane fuel cell. Int. J. Hydrog. Energy, 2021, 46, 8749.DOI: https://doi.org/10.1016/j.ijhydene.2020.12.041[3] Zhou X. et al.: High-Repetitive Reversal Tolerant Performance of Proton-Exchange Membrane Fuel Cell by Designing a Suitable Anode. ACS OMEGA, 2020, 5, 10099.DOI: https://dx.doi.org/10.1021/acsomega.0c00638[4] Peng Y. et al.: Pitfalls of a commonly used accelerated stress test for reversal tolerance testing of proton exchange membrane fuel cell anode layers. J. Power Sources, 2021, 500, 229986.DOI: https://doi.org/10.1016/j.jpowsour.2024.234087

Synthesis and Experimental Screening of Catalysts for H2S to H2 Decomposition Under Close-to-Industry Conditions

Synthesis and Experimental Screening of Catalysts for H2S to H2 Decomposition Under Close-to-Industry Conditions

High-Throughput UV-Induced Synthesis and Screening of Alloy Electrocatalysts.

The combination of different elements in alloy catalysts can lead to improved activity as it provides opportunities to tune the electronic structures of surface atoms. However, the synthesis and performance screening of alloy catalysts through a vast chemical space are cost- and labor-intensive. Herein, a UV-induced, high-throughput method is reported for the synthesis and screening of alloy electrocatalysts in a fast and low-cost manner. A platform that integrates 37 mini-reaction-cells enables simultaneous UV-induced photodeposition of alloy nanoparticles with up to 37 compositions. These mini-reaction-cells further allow a transfer-free, high-throughput electrochemical performance screening. Binary (PtPd, PtIr, PdIr), ternary (PtPdIr, PtRuIr) and quaternary (PtPdRuIr) alloys have been synthesized with the activity of the binary alloys (57 compositions) for hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR) being screened. The predicted high performance of identified alloy compositions are subsequently validated by standard measurements using a rotating disk electrode configuration. It is found that the as-synthesized alloy nanoparticles are rich in twin boundaries and thus possess lattice strain. Density functional theory calculation implies that the high ORR activity of the screened Pt0.75Pd0.25 alloy originates from the interplay between the differentiated adsorption sites because of alloying and the strain-induced modulation of the d-band center.

High‐Throughput Screening Technologies of Efficient Catalysts for the Ammonia Economy

AbstractDriven by the growing global demand for sustainable energy, ammonia is gaining recognition as a crucial energy carrier with the potential for widespread manufacturing. This has spurred the emergence of a “sustainable ammonia economy”. Efficient catalyst development is paramount to achieving this purpose. Although the traditional trial‐and‐error methods have led to substantial progress, they are inherently time‐consuming. In recent years, high‐throughput screening strategies are revolutionizing catalyst discovery, offering an efficient and cost‐effective approach for identifying high‐performance catalysts across various processes within the ammonia economy. This review explores recent advancements in these rapid catalyst screening techniques for ammonia‐based processes. By outlining the general screening principles and the key steps involved in the computational analysis of catalysts relevant to different stages of the ammonia economy, this review aims to provide fundamental insights for the development of novel catalysts using these accelerated methods.

Machine learning assisted screening of nitrogen-doped graphene-based dual-atom hydrogen evolution electrocatalysts

Nitrogen doped graphene-based dual-atom catalysts (NG-DACs) usually exhibit high reactivity for hydrogen evolution reaction (HER). The experimental design of efficient DACs-based HER catalysts, however, is time-consuming and expensive. In this work, a density functional theory combined with machine learning (DFT-ML) strategy is adopted towards the rapid screening of NG-DACs HER catalyst. The adsorption energies of HER intermediates on NG-DACs obtained by DFT calculations and their elemental features were used for the ML database construction. The prediction performance of three ML algorithms was evaluated, and gradient boosted regression (GBR) is found exhibit the best prediction accuracy. Using the HER energetics on Pt (111) as reference, quick screening of the NG-DACs with high HER activity was achieved, resulting to twenty-four potential catalysts. Further selection and validation of the ML-screened catalysts were performed by the hydrogen adsorption Gibbs free energy analysis. Accordingly, four promising NG-DACs HER catalysts were predicted using the proposed DFT-ML based catalyst prediction framework. The DFT-ML strategy offers an promising approach for the screening of new HER electrocatalysts.

Theoretical Establishment and Screening of Double-Atom Catalysts Supported on Biphenylene for an Efficient Electrocatalytic Nitrogen Reduction Reaction

Theoretical Establishment and Screening of Double-Atom Catalysts Supported on Biphenylene for an Efficient Electrocatalytic Nitrogen Reduction Reaction

Screening of Silver-Based Single-Atom Alloy Catalysts for NO Electroreduction to NH3 by DFT Calculations and Machine Learning.

Exploring NO reduction reaction (NORR) electrocatalysts with high activity and selectivity toward NH3 is essential for both NO removal and NH3 synthesis. Due to their superior electrocatalytic activities, single-atom alloy (SAA) catalysts have attracted considerable attention. However, the exploration of SAAs is hindered by a lack of fast yet reliable prediction of catalytic performance. To address this problem, we comprehensively screened a series of transition-metal atom doped Ag-based SAAs. This screening process involves regression machine learning (ML) algorithms and a compressed-sensing data-analytics approach parameterized with density-functional inputs. The results demonstrate that Cu/Ag and Zn/Ag can efficiently activate and hydrogenate NO with small Φmax(η), a grand-canonical adaptation of the Gmax(η) descriptor, and exhibit higher affinity to NO over H adatoms to suppress the competing hydrogen evolution reaction. The NH3 selectivity is mainly determined by the s orbitals of the doped single-atom near the Fermi level. The catalytic activity of SAAs is highly correlated with the local environment of the active site. We further quantified the relationship between the intrinsic features of these active sites and Φmax(η). Our work clarifies the mechanism of NORR to NH3 and offers a design principle to guide the screen of highly active SAA catalysts.

Synthesis of Novel Pseudo-Enantiomeric Phase-Transfer Catalysts from Cinchona Alkaloids and Application to the Hydrolytic Dynamic Kinetic Resolution of Racemic 3-Phenyl-2-oxetanone.

Naturally occurring Cinchona alkaloids such as quinidine (QD)/cinchonine (CN) and their diastereomers, quinine (QN)/cinchonidine (CD), have been recognized as pseudo-enantiomeric pairs. Utilizing these pseudo-enantiomeric alkaloids as chiral resources provides complementary enantioselectivity in many asymmetric reactions. During the screening of Cinchona alkaloid phase-transfer catalysts (PTCs) in the hydrolytic dynamic kinetic resolution of racemic 3-phenyl-2-oxetanone (1) to tropic acid (2), we found that the introduction of a 4-trifluoromethylphenyl group at the vinyl terminus of BnQN significantly reduced the enantioselectivity to 41% enantiomeric excess (ee). The optimized structure of tetrahedral intermediates (TI, PTC + 1 + OH-) of hydrolysis obtained by density functional theory (DFT) calculations shows that the orientation of the quinoline and benzene rings of QD class PTC are nearly parallel to each other and to construct a greatly extended π-electron cloud surface, allowing good π-π interaction with the benzene ring of 1.

Unlocking the Anion Effect on Steerable Production of 5‐Hydroxymethylfurfural

AbstractHomogeneous metal salt catalysts play a pivotal role in industrial production of 5‐hydroxymethylfurfural (HMF). Herein, we first proposed the anion effect on steerable production of HMF using metal salts with different anions as catalyst in a biphasic system of tetrahydrofuran (THF)/NaCl aqueous solution (NaCl aq). Notably, the anions affected the catalytic activity of the metal salts, leading to an order of magnitude difference in the HMF yields, i.e., AlBr3 (74.0 mol %)>AlCl3 (60.8 mol %)>Al2(SO4)3 (35.2 mol %)>Al(NO3)3 (14.9 mol %). The anion effect on steerable production of HMF could be attributed to the proximity effect and electron tension. Anions form close‐range interactions with glucose molecules by proximity effect to promote electron transfer, facilitating the isomerization of glucose to fructose. Besides, anions induce a reduction of the electron cloud density of glucose carbon atoms, generating electron tension that rapidly transforms glucose from the ground state to the transition state, thereby increasing the HMF yield. Based on the revelation of anions effect and evaluation of techno‐economic process, we expect to provides theoretical guidance for high‐throughput screening of metal salt catalysts in industrial biorefinery.

Theoretical Catalyst Screening of Multielement Alloy Catalysts for Ammonia Synthesis Using Machine Learning Potential and Generative Artificial Intelligence

Theoretical Catalyst Screening of Multielement Alloy Catalysts for Ammonia Synthesis Using Machine Learning Potential and Generative Artificial Intelligence

Unlocking the Anion Effect on Steerable Production of 5-Hydroxymethylfurfural.

Homogeneous metal salt catalysts play a pivotal role in industrial production of 5-hydroxymethylfurfural (HMF). Herein, we first proposed the anion effect on steerable production of HMF using metal salts with different anions as catalyst in a biphasic system of tetrahydrofuran (THF)/NaCl aqueous solution (NaCl aq). Notably, the anions affected the catalytic activity of the metal salts, leading to an order of magnitude difference in the HMF yields, i.e., AlBr3 (74.0 mol %)>AlCl3 (60.8 mol %)>Al2(SO4)3 (35.2 mol %)>Al(NO3)3 (14.9 mol %). The anion effect on steerable production of HMF could be attributed to the proximity effect and electron tension. Anions form close-range interactions with glucose molecules by proximity effect to promote electron transfer, facilitating the isomerization of glucose to fructose. Besides, anions induce a reduction of the electron cloud density of glucose carbon atoms, generating electron tension that rapidly transforms glucose from the ground state to the transition state, thereby increasing the HMF yield. Based on the revelation of anions effect and evaluation of techno-economic process, we expect to provides theoretical guidance for high-throughput screening of metal salt catalysts in industrial biorefinery.

Leveraging machine learning to expedite screening of single-atom catalysts in electrochemical nitrate reduction to ammonia

The electrochemical reduction of nitrate to ammonia, which is a potentially valuable process for pollution mitigation and NH3 production, faces challenges in developing high-performance catalysts. By integrating machine learning (ML) and density functional theory (DFT), we successfully established ML models using thousands of calculated properties (formation energy, NO3– adsorption, and Gibbs free energy of the critical step) from the literature and predicted the catalytic performance of 1891 previously unknown single-atom catalysts (SACs) for the nitrate reduction reaction (NO3RR), employing a four-step screening strategy (stability, NO3– adsorption, activity, and selectivity) and identifying 10 promising materials. We then verified the properties of these SACs, which exceeded the benchmark materials, thereby validating the ML model, and elucidated the origin of their high NO3RR activity based on their inner electronic structures. This study not only presents prominent candidates and novel descriptors for NO3RR but also establishes an efficient, rapid, and cost-effective methodology for the discovery and design of more valuable SACs.

Cage-Shaped Borate Catalysts Bearing Precisely Controlled Lewis Acidity and Their Application in Glycosylations.

Cage-shaped borates, whose Lewis acidity can be precisely modulated by the structural attributes of the triphenolic ligands, were employed as catalysts for glycosylation. Each cage-shaped borate displayed distinctive reactivity; thus, screening of the borate catalysts enabled controllable activation of glycosyl fluorides under mild conditions. Practical glycosylation was achieved by fine-tuning the Lewis acidity tailored to the substrate reactivity, thereby providing a versatile method applicable to the synthesis of complex glycans.