First-Principles Insights into the Mechanism of CO2 Hydrogenation Reactions by Fe-PNP Pincer Complex

Using the state of the art theoretical methods, we have provided a comprehensive mechanistic understanding of the CO2 hydrogenation into HCOOH, H2CO, and CH3OH by 2,6-bis(diisopropylphosphinomethyl)pyridine (PNP)-ligated Fe pincer complex, featuring one CO and two H as co-ligands. For the computational investigation, a verified structural model containing methyl groups in place of the experimental isopropyl groups was used. Three catalytic conversions involving hydrogenation of CO2 into formic acid (HCOOH), HCOOH into formaldehyde and methanol were studied in different solvent medium. Our modelled complex appears to be a viable base-free catalyst for the conversion of CO2 into HCOOH and HCOOH into H2CO, based on the free energy profiles, which show apparent activation energy barriers of 16.28 kcal/mol and 23.63 kcal/mol for the CO2 to HCOOH and HCOOH to H2CO conversion, respectively. However, the computed results show that, due to the huge energy span of H2CO to CH3OH conversion, complete hydrogenation of CO2 into methanol could not occur under moderate conditions. Morpholine co-catalyst, which can lower the hydrogenation barrier by taking part in a simultaneous H-atom donation-acceptance process, could have assisted in completing this step.

Impact of the Methylene Bridge Substitution in Chelating NHC-Phosphine Mn(I) Catalyst for Ketone Hydrogenation

Systematic modification of the chelating NHC-phosphine ligand (NHC = N-heterocyclic carbene) in highly efficient ketone hydrogenation Mn(I) catalyst fac-[(Ph2PCH2NHC)Mn(CO)3Br] has been performed and the catalytic activity of the resulting complexes was evaluated using acetophenone as a benchmark substrate. While the variation of phosphine and NHC moieties led to inferior results than for a parent system, the incorporation of a phenyl substituent into the ligand methylene bridge improved catalytic performance by ca. 3 times providing maximal TON values in the range of 15000-20000. Mechanistic investigation combining experimental and computational studies allowed to rationalize this beneficial effect as an enhanced stabilization of reaction intermediates including anionic hydride species fac-[(Ph2PC(Ph)NHC)Mn(CO)3H]- playing a crucial role in the hydrogenation process. These results highlight the interest of such carbon bridge substitution strategy being rarely employed in the design of chemically non-innocent ligands.

Machine Learning Assisted Exploration of High Entropy Alloy-Based Catalysts for Selective CO2 Reduction to Methanol

Catalytic conversion of CO₂ to carbon neutral fuels can be ecofriendly and allow for economic replacement of fossil fuels. Here, we have investigated high-throughput screening of high entropy alloy (Cu, Co, Ni, Zn, and Sn) based catalysts through machine learning (ML) for CO₂ hydrogenation to methanol. Stability and catalytic activity studies of these catalysts have been performed for all possible combinations, where different elemental, compositional, and surface microstructural features were used as input parameters. Adsorption energy values of CO₂ reduction intermediates on the CuCoNiZnMg- and CuCoNiZnSn-based catalysts have been used to train the ML models. Successful prediction of adsorption energies of the adsorbates using CuCoNiZnMg-based training data is achieved except for two intermediates. Hence, we show that activity and selectivity of these catalysts can be successfully predicted for CO₂ hydrogenation to methanol and have screened a series of high entropy-based catalysts (from 36750 considered catalysts) which could be promising for methanol synthesis.

Mechanistic exploration of CO2 conversion to dimethoxymethane (DMM) using transition metal (Co, Ru) catalysts: an energy span model

The conversion of CO₂ to DMM is an important transformation for various reasons. Co and Ru-based triphos catalysts have been investigated using density functional theory (DFT) calculations to understand the mechanistic pathways of the CO₂ to DMM conversion and the role of noble/non-noble metal-based catalysts. The reaction has been investigated sequentially through methylformate (MF) and methoxymethane (MM) intermediates as they are found to be important intermediates. For the hydrogenation of CO₂ and MF, the hydrogen sources such as H₂ and methanol have been investigated. The calculated reaction free energy barriers for all the possible pathways suggest that both hydrogen sources are important for the Co-triphos catalyst. However, in the case of the Ru-triphos catalyst, molecular H₂ is calculated to be the only hydrogen source. Various esterification and acetalization possibilities have also been explored to find the most favorable pathway for the conversion of CO₂ to DMM. We find that the hydride transfer to the CO₂ is the rate determining step (RDS) for the overall reaction. Our mechanistic investigation reveals that the metal center is the active part for the catalysis rather than the Brønsted acid and the redox triphos ligand plays an important role through the push-pull mechanism. The implemented microkinetic study shows that the reaction is also quite dependent on the concentration of the gaseous reactants and the rate constant increases exponentially above 363 K.

Computational Studies on the Mechanisms for Deaminative Amide Hydrogenation by Homogeneous Bifunctional Catalysts

The deaminative hydrogenation of amides is one of the most convenient pathways for the synthesis of amines and alcohols. The ideal source of reducing equivalents for this reaction is molecular hydrogen, though, in practice, this approach requires high pressures and temperatures, with many catalysts achieving only small turnover numbers and frequencies. Nonetheless, during the last ten years, this field has made major advances towards larger turnovers under milder conditions thanks to the development of bifunctional catalysts. These systems promote the heterolytic cleavage of hydrogen into proton and hydride by combining a basic ligand with an acidic metal centre. The present review focuses on the computational study of the reaction mechanism underlying bifunctional catalysis. This review is structured around the fundamental steps of this mechanism, namely the C=O and C–N hydrogenation of the amide, the C–N protonolysis of the hemiaminal, the C=O hydrogenation of the aldehyde, and the competition between hydrogen activation and catalyst deactivation. In line with the complexity of the mechanism, we also provide a perspective on the use of microkinetic models. Both Noyori- and Milstein-type catalysts are discussed and compared.

Machine Learning-Driven High-Throughput Screening of Alloy-Based Catalysts for Selective CO2 Hydrogenation to Methanol

The revolutionary development of machine learning and data science and exploration of its application in material science are huge achievements of the scientific community in the past decade. In this work, we have reported an efficient approach of machine learning-aided high-throughput screening for finding selective earth-abundant high-entropy alloy-based catalysts for CO₂ to methanol formation using a machine learning algorithm and microstructure model. For this, we have chosen earth-abundant Cu, Co, Ni, Zn, and Mg metals to form various alloy-based compositions (bimetallic, trimetallic, tetrametallic, and high-entropy alloys) for selective CO₂ reduction reaction toward CH₃OH. Since there are several possible surface microstructures for different alloys, we have used machine learning along with DFT calculations for high-throughput screening of the catalysts. In this study, the stability of various 8-atom fcc periodic (111) surface unit cells has been calculated using the atomic-size difference factor (δ) as well as the ratio taken from Gibbs free energy of mixing (Ω). Thinking about the simplicity and accuracy, microstructure models by considering the neighboring atoms of the adsorption sites and others as Cu atoms have been considered for different adsorption sites (on-top, bridge, and hollow-hcp). Moreover, the adsorption energies of the *H, *O, *CO, *HCO, *H₂CO, and *H₃CO intermediates have been predicted using the best fitted algorithm of the training set. The predicted adsorption energies have been screened based on the pure Cu adsorption energy. Furthermore, the screened catalysts have been correlated among different adsorption site microstructures. At the end, we were able to find seven active catalysts, among which two catalysts are CuCoNiZn-based tetrametallic, three catalysts are CuNiZn-based trimetallic, and two catalysts are CuCoZn-based trimetallic alloys. Hence, this work demonstrates not an ultimate but an efficient approach for finding new product-selective catalysts, and we expect that it can be convenient for other similar types of reactions in forthcoming days.

Identifying the preferential pathways of CO2 capture and hydrogenation to methanol over an Mn(I)-PNP catalyst: a computational study

CO2 hydrogenation to CH3OH is a crucial conversion for several purposes. Density functional theory (DFT) studies have been performed to explore the mechanistic pathways of newly reported CO2 capture and hydrogenation to methanol. The present study describes the multistep transformation of CO2 to methanol. In this case we have introduced 2-amino-1-propanol to capture CO2 and hydrogenation of the CO2 captured product (oxazolidinone) in the presence of an active Mn(i)-PNP based catalyst. All the plausible pathways for oxazolidinone hydrogenation to methanol have been explored in detail. Here, hydride and proton transfer steps are very important for oxazolidinone hydrogenation, whereas heterolytic H2 cleavage is the most important step for the regeneration of the catalyst. Our detailed study shows that C-N bond hydrogenation followed by C-O and C[double bond, length as m-dash]O bond hydrogenations or C-O bond hydrogenation followed by C-N and C[double bond, length as m-dash]O bond hydrogenations are the most favourable pathways for oxazolidinone hydrogenation to methanol with a total reaction free energy barrier of 36.9 kcal mol-1 for both the pathways in the presence of a Mn(i)-PNP catalyst.