The computational design of transition-metal catalysts remains a grand challenge in chemistry. Here, we used density functional theory (DFT) calculations, data science, and experiments to tackle the analysis and design of new catalysts for transfer hydroformylation because only a single known bisphosphine ligand combined with Rh has been reported to provide high reactivity. We first used experiments to screen commercially available and common bisphosphines, and this data was then combined with DFT calculations and data science to screen >600 bisphosphine ligands from our ReaLigands library and develop interpretable chemical space mapping. Following another round of DFT calculations, we identified several promising bisphosphine ligands that were subsequently synthesized and validated experimentally.

Linear α-olefins (1-alkenes) are critical comonomers for ethene copolymerization. A major impediment in the development of new homogeneous Fe catalysts for ethene oligomerization to produce comonomers and other important commercial products is the prediction of propagation versus termination rates that control the α-olefin distribution (e.g., 1-butene through 1-decene), which is often referred to as a K-value. Because the transition states for propagation versus termination are generally separated by less than a one kcal mol-1 difference in energy, this selectivity cannot be accurately predicted by either DFT or wavefunction methods (even DLPNO-CCSD(T)). Therefore, we developed a sub-kcal mol-1 accuracy machine learning model based on several hundred experimental selectivity values and straightforward 2D chemical and physical features that enables the prediction of α-olefin distribution K-values. As part of our model, we developed a new ad hoc feature that boosted the model performance. This machine learning model captures the effects of a broad range of ligand architectures and chemically nonintuitive trends in oligomerization selectivity. Our machine learning model was experimentally validated by prediction of a K-value for a new Fe phosphaneyl-pyridinyl-quinoline catalyst followed by experimental measurement that showed precise agreement. In addition to quantitative predictions, we demonstrate how this machine learning model can provide qualitative catalyst design using proximity of pairs type analysis.

Quantum-mechanical-based computational design of molecular catalysts requires accurate and fast electronic structure calculations to determine and predict properties of transition-metal complexes. For Zr-based molecular complexes related to polyethylene catalysis, previous evaluation of density functional theory (DFT) and wavefunction methods only examined oxides and halides or select reaction barrier heights. In this work, we evaluate the performance of DFT against experimental redox potentials and bond dissociation enthalpies (BDEs) for zirconocene complexes directly relevant to ethylene polymerization catalysis. We also examined the ability of DFT to compute the fourth atomic ionization potential of zirconium and the effect the basis set selection has on the ionization potential computed with CCSD(T). Generally, the atomic ionization potential and redox potentials are very well reproduced by DFT, but we discovered relatively large deviations of DFT-calculated BDEs compared to experiment. However, evaluation of BDEs with CCSD(T) suggests that experimental values should be revisited, and our CCSD(T) values should be taken as most accurate.

While catalytic hydroformylation is a well-establishedreaction,there are only a few reports of homogeneous catalyzed retro-hydroformylationwhere carbon monoxide and dihydrogen are eliminated from an aldehydeto generate an olefin. Our in-depth assessment of reaction pathwaysusing density functional theory and metadynamics calculations foraldehyde retro-hydroformylation by cyclopentadienyl phosphine-typeIr(III) catalysts has revealed two surprising and uniqueaspects of catalysis: (1) Catalytic cycle turnover is determined bythe rate of singlet-triplet spin state crossover; and (2) during catalysis,after C-H bond activation, a transient Ir-III-Hintermediate undergoes intramolecular proton transfer to give a dearomatized & eta;(4)-Cp-H diene ligand. This Ir-I intermediateprovides the key coordination unsaturation to enable decarbonylationand & beta;-hydride elimination reaction steps. Overall, these mechanisticinsights set the stage for the design of novel retro-hydroformylationmolecular catalysts.

Zirconocene catalysts are capable of inducing ethylene polymerization to generate a variety of polyethylene polymers with the incorporation of a co-monomer into the growing polyethylene chain. The amount of co-monomer incorporation depends on the rate of insertion of ethylene versus co-monomer. Previously, the design of zirconocene catalysts to control α-olefin co-monomer incorporation during ethylene polymerization catalysis generally focused on repulsive steric interactions. Here, we demonstrate through computational catalyst analysis and design that stabilizing noncovalent dispersion-type interactions can be used to significantly modulate 1-hexene incorporation during ethylene co-polymerization catalysis.

One approach to selectively generate 1-hexene is through ethylene trimerization using highly active Cr N-phosphinoamidine catalysts ((P,N)Cr). Depending on the ligand, (P,N)Cr catalysts can either generate nearly pure 1-hexene or form 1-hexene with significant mixtures of other C6 mass products, for example methylenecyclopentane. Here we report DFT transition-state modeling examining 1-hexene catalysis pathways as well as pathways that lead to alternative C6 mass products. This provided qualitative and semi-quantitative modeling of the experimental 1-hexene purity values for several (P,N)Cr catalysts. Consistent with previous computational studies, the key 1-hexene purity-determining transition states were determined to be β-hydrogen transfer structures from the metallacycloheptane intermediate. The origin of selectivity for these (P,N)Cr catalysts can be attributed to steric effects in the transition-state structure with coordinated ethylene that leads to C6 impurities.

The use of data science tools to provide the emergence of nontrivial chemical features for catalyst designis an important goal in catalysis science. Additionally, there is currently no general strategy forcomputational homogeneous, molecular catalyst design. Here we report the unique combination of anexperimentally verified DFT-transition-state model with a random forest machine learning model in acampaign to design new molecular Cr phosphine imine (Cr(P,N)) catalysts for selective ethyleneoligomerization, specifically to increase 1-octene selectivity. This involved the calculation of 1-hexene:1-octene transition-state selectivity for 105 (P,N) ligands and the harvesting of 14 descriptors, which werethen used to build a random forest regression model. This model showed the emergence of several keydesign features, such as Cr–N distance, Cr–α distance, and Cr distance out of pocket, which were then usedto rapidly design a new generation of Cr(P,N) catalyst ligands that are predicted to give >95% selectivityfor 1-octene

Cr phosphine catalysts are uniquely suited for industrial selective ethylene trimerization to 1-hexene. We recently introduced a Cr N-phosphinoamidine catalyst ((P,N)Cr) transition-state model for selectivity, and here, we use density functional theory calculations to address catalyst reactivity for ethylene trimerization. This is particularly important because there are currently no empirical parameters or design principles that provide prediction of high catalyst activity while maintaining trimerization selectivity. Specifically, using transition states and the energetic span model, we examined the ethylene trimerization catalytic cycle with the bidentate (P,N)Cr catalyst 1a and compared this highly productive catalyst to the surprisingly inactive tridentate (P,N,N)Cr catalyst. For (P,N)Cr 1a, this analysis revealed that for the high-spin Cr-I/III chromacycle mechanism, there are multiple Cr-I ethylene-coordinated resting states and multiple turnover-controlling transition states, which is consistent with previous experimental rate studies and can account for a partial rate order in ethylene. Based on the calculated energy landscape, the calculated 1-hexene productivity of 6.5 mol s(-1) and mass of 2.0 x 10(6) g h(-1) is close to the experimental value. This analysis also revealed that the tridentate (P,N,N)Cr catalyst has a much larger energy span and is similar to 10(7) slower, which results from the stabilization of the energy landscape around the chromacyclopentane intermediate. In addition to this reactivity/inactivity comparison, we also calculated and compared the reactivity of several other experimentally reported 1-hexene Cr tridentate catalysts. Based on the catalytic energy spans, our calculations were able to qualitatively and semi-quantitatively replicate relative catalyst reactivity.

One of the remaining "grand challenges" in chemistry is the development of a next generation, less expensive, cleaner process that can allow the vast reserves of methane from natural gas to augment or replace oil as the source of fuels and chemicals. Homogeneous (gas/liquid) systems that convert methane to functionalized products with emphasis on reports after 1995 are reviewed. Gas/solid, bioinorganic, biological, and reaction systems that do not specifically involve methane functionalization are excluded. The various reports are grouped under the main element involved in the direct reactions with methane. Central to the review is classification of the various reports into 12 categories based on both practical considerations and the mechanisms of the elementary reactions with methane. Practical considerations are based on whether or not the system reported can directly or indirectly utilize O2 as the only net coreactant based only on thermodynamic potentials. Mechanistic classifications are based on whether the elementary reactions with methane proceed by chain or nonchain reactions and with stoichiometric reagents or catalytic species. The nonchain reactions are further classified as CH activation (CHA) or CH oxidation (CHO). The bases for these various classifications are defined. In particular, CHA reactions are defined as elementary reactions with methane that result in a discrete methyl intermediate where the formal oxidation state (FOS) on the carbon remains unchanged at -IV relative to that in methane. In contrast, CHO reactions are defined as elementary reactions with methane where the carbon atom of the product is oxidized and has a FOS less negative than -IV. This review reveals that the bulk of the work in the field is relatively evenly distributed across most of the various areas classified. However, a few areas are only marginally examined, or not examined at all. This review also shows that, while significant scientific progress has been made, greater advances, particularly in developing systems that can utilize O2, will be required to develop a practical process that can replace the current energy and capital intensive natural gas conversion process. We believe that this classification scheme will provide the reader with a rapid way to identify systems of interest while providing a deeper appreciation and understanding, both practical and fundamental, of the extensive literature on methane functionalization. The hope is that this could accelerate progress toward meeting this "grand challenge."

Molecular, Fe-catalyzed ethylene oligomerization provides access to a range of linear α-olefins (LAOs) that are used to produce polyethylene, lubricants, surfactants, and other commercial products. This work provides an experimental example of an Fe pendant donor diimine ((PDD)Fe) catalyzed ethylene oligomerization that showcases very high olefin oligomer purity without branching and provides K (propagation/(propagation + termination)) values of LAOs fractions, which show larger K values as a function of carbon chain length. This experimental example provided an anchor point to try to identify a practical density functional theory (DFT) protocol to model ethylene oligomerization branching, propagation/termination, and K values. Using M06-L DFT calculations, we successfully modeled the very high oligomerization purity for the (PDD)Fe catalyst, compared to the lower purity for the Fe tridentate pyridine bisimine (PBI)Fe catalyst, which showed enhanced regioselectivity for migratory insertion between Fe–H intermediates and LAOs. Modeling propagation/termination and K values were significantly more challenging with most oxidation and spin states incorrectly predicting a significant preference for oligomerization termination. Therefore, caution should be used when trying to model these types of quantitative catalysis values.

Computational design of molecular homogeneous organometallic catalysts followed by experimental realization remains a significant challenge. Here, we report the development and use of a density functional theory transition-state model that provided quantitative prediction of molecular Cr catalysts for controllable selective ethylene trimerization and tetramerization. This computational model identified a general class of phosphine monocyclic imine (P,N)-ligand Cr catalysts where changes in the ligand structure control 1-hexene versus 1-octene selectivity. Experimental ligand and catalyst synthesis as well as reaction testing quantitatively confirmed predictions.

We describe the results of our combined experimental and computational investigation of structurally analogous (N-phosphinoamidinate)metal(N(SiMe3)2) precatalysts ((PN)M; M = Mn2+, Fe2+, Co2+, and Ni2+; d5–d8) in the isomerization–hydroboration of 1-octene, cis-4-octene, or trans-4-octene (1a–c) with HBPin. As part of this investigation, the synthesis and crystallographic characterization of diamagnetic (PN)Ni, ((PN)NiH)2, (PN)NiH(L) (L = pyridine or DMAP), and (PN)Ni(NHdipp) (dipp = 2,6-iPr2C6H3) are reported. Divergent catalytic reactivity and selectivity was noted for members of the (PN)M series; (PN)Mn and (PN)Ni afforded poor hydroboration yields, whereas the use of (PN)Fe or (PN)Co afforded high conversion and selectivity for the terminal borylation product, (n-octyl)BPin (2a). DFT calculations involving (PN)M as well as stoichiometric reactivity studies featuring (PN)Ni confirmed that (PN)MH intermediates generated upon reaction of (PN)M with HBPin represent viable catalytic species whereby formati...

The first examples of stoichiometric dehydrogenative B-H/C(sp3 )-H benzylic borylation reactions, which are of relevance to catalytic methylarene (di)borylation, are reported. These unusual transformations involving a (κ2 -P,N)Pt(η3 -benzyl) complex, and either pinacolborane or catecholborane, proceed cleanly at room temperature. Density functional calculations suggest that borylation occurs via successive σ-bond metathesis steps, whereby a PtII -H intermediate engages in C(sp3 )-H bond activation-induced dehydrogenation.

A crystallographically characterized three-coordinate, formally 14 electron Pt(II) complex 1 featuring terminal amido ligation is reported. Computational analysis revealed relatively weak π donation from the amide lone pair to platinum and supports a 14-electron assignment for 1. Stoichiometric reactivity studies confirmed the viability of net O-H and C-H addition across, as well as isonitrile insertion into, the terminal platinum-amido linkage of 1.

An understanding of the factors that govern the rate of chemical reactions has proven elusive for many students who begin a survey course in the chemical sciences. Inquiry-based curricula built upon an understanding of common student misconceptions related to chemical kinetics have proven to be a more effective means by which to develop student understanding than traditional lecture formats. To facilitate teacher-guided discussion regarding the subject of catalysis, we have developed a simple and safe demonstration, whereby the hydrogen and oxygen components evolved upon electrolysis of water are recombined at room temperature with the aid of a platinum/ruthenium catalyst. This demonstration is designed to draw students' attention toward the dramatic change in reaction rate that can be affected by catalyst involvement and to provoke dialog regarding the mechanistic changes that accompany reaction catalysis.

The selective, oxidative functionalization of ethane, a significant component of shale gas, to products such as ethylene or ethanol at low temperatures and pressures remains a significant challenge. Herein we report that ethane is efficiently and selectively functionalized to the ethanol ester of H2SO4, ethyl bisulfate (EtOSO3H) as the initial product, with the Pt(II) "Periana-Catalytica" catalyst in 98% sulfuric acid. A subsequent organic reaction selectively generates isethionic acid bisulfate ester (HO3S-CH2-CH2-OSO3H, ITA). In contrast to the modest 3-5 times faster rate typically observed in electrophilic CH activation of higher alkanes, ethane CH functionalization was found to be ~100 times faster than that of methane. Experiment and quantum-mechanical calculations reveal that this unexpectedly large increase in rate is the result of a fundamentally different catalytic cycle in which ethane CH activation (and not platinum oxidation as for methane) is now turnover limiting. Facile Pt(II)-Et functionalization was determined to occur via a low energy β-hydride elimination pathway (which is not available for methane) to generate ethylene and a Pt(II)-hydride, which is then rapidly oxidized by H2SO4 to regenerate Pt(II)-X2. A rapid, non-Pt-catalyzed reaction of formed ethylene with the hot, concentrated H2SO4 solvent cleanly generate EtOSO3H as the initial product, which further reacts with the H2SO4 solvent to generate ITA.

, 1232 (2014); 343 Science et al. Brian G. Hashiguchi Ethane, and Propane to Alcohol Esters Main-Group Compounds Selectively Oxidize Mixtures of Methane, This copy is for your personal, non-commercial use only. clicking here. colleagues, clients, or customers by , you can order high-quality copies for your If you wish to distribute this article to others here. following the guidelines can be obtained by Permission to republish or repurpose articles or portions of articles ): March 26, 2014 www.sciencemag.org (this information is current as of The following resources related to this article are available online at http://www.sciencemag.org/content/343/6176/1232.full.html version of this article at: including high-resolution figures, can be found in the online Updated information and services, http://www.sciencemag.org/content/suppl/2014/03/12/343.6176.1232.DC1.html can be found at: Supporting Online Material http://www.sciencemag.org/content/343/6176/1232.full.html#ref-list-1 , 5 of which can be accessed free: cites 38 articles This article http://www.sciencemag.org/cgi/collection/chemistry Chemistry subject collections: This article appears in the following