Complex Organic Reactions Research Articles

Approaching Coupled Cluster Accuracy with Density Functional Theory Using the Generalized Connectivity-Based Hierarchy.

This Perspective reviews connectivity-based hierarchy (CBH), a systematic hierarchy of error-cancellation schemes developed in our group with the goal of achieving chemical accuracy using inexpensive computational techniques ("coupled cluster accuracy with DFT"). The hierarchy is a generalization of Pople's isodesmic bond separation scheme that is based only on the structure and connectivity and is applicable to any organic and biomolecule consisting of covalent bonds. It is formulated as a series of rungs involving increasing levels of error cancellation on progressively larger fragments of the parent molecule. The method and our implementation are discussed briefly. Examples are given for the applications of CBH involving (1) energies of complex organic rearrangement reactions, (2) bond energies of biofuel molecules, (3) redox potentials in solution, (4) pKa predictions in the aqueous medium, and (5) theoretical thermochemistry combining CBH with machine learning. They clearly show that near-chemical accuracy (1-2 kcal/mol) is achieved for a variety of applications with DFT methods irrespective of the underlying density functional used. They demonstrate conclusively that seemingly disparate results, often seen with different density functionals in many chemical applications, are due to an accumulation of systematic errors in the smaller local molecular fragments that can be easily corrected with higher-level calculations on those small units. This enables the method to achieve the accuracy of the high level of theory (e.g., coupled cluster) while the cost remains that of DFT. The advantages and limitations of the method are discussed along with areas of ongoing developments.

Optimization-based simultaneous modelling of stoichiometries and kinetics in complex organic reaction system

Efficient understanding and modelling of kinetics in complex organic reaction systems are crucial in the development cycle. The dynamic experimental measurements can be analyzed automatically by the data-driven method in a stepwise modelling approach: after the preliminary screening of candidate stoichiometries, they are formed into different stoichiometric groups, and the reaction data were regressed for each stoichiometric group so that the best fitting kinetic model could be selected. However, the stepwise modelling approach brings about the computational difficulty for complex reaction systems due to the combinatorial nature of forming stoichiometric groups. In this article, a novel optimization-based method, simultaneously combining stoichiometry grouping and kinetics fitting, is proposed to build the kinetic model of a homogeneous organic reaction system. Through reformulation of the original nonlinear optimization model, a mixed integer linear programming model is developed to identify the reaction stoichiometries and kinetic parameters with improved efficiency. Two computational examples are presented to demonstrate the accuracy and effectiveness of the simultaneous modelling methodology.

Key Features of TEMPO-Containing Polymers for Energy Storage and Catalytic Systems

The need for environmentally benign portable energy storage drives research on organic batteries and catalytic systems. These systems are a promising replacement for commonly used energy storage devices that rely on limited resources such as lithium and rare earth metals. The redox-active TEMPO (2,2,6,6-tetramethylpiperidin-1-oxyl-4-yl) fragment is a popular component of organic systems, as its benefits include remarkable electrochemical performance and decent physical properties. TEMPO is also known to be an efficient catalyst for alcohol oxidation, oxygen reduction, and various complex organic reactions. It can be attached to various aliphatic and conductive polymers to form high-loading catalysis systems. The performance and efficiency of TEMPO-containing materials strongly depend on the molecular structure, and thus rational design of such compounds is vital for successful implementation. We discuss synthetic approaches for producing electroactive polymers based on conductive and non-conductive backbones with organic radical substituents, fundamental aspects of electrochemistry of such materials, and their application in energy storage devices, such as batteries, redox-flow cells, and electrocatalytic systems. We compare the performance of the materials with different architectures, providing an overview of diverse charge interactions for hybrid materials, and presenting promising research opportunities for the future of this area.

Cooperative Stereoinduction in Asymmetric Photocatalysis.

Stereoinduction in complex organic reactions often involves the influence of multiple stereocontrol elements. The interaction among these can often result in the observation of significant cooperative effects that afford different rates and selectivities between the matched and mismatched sets of stereodifferentiating chiral elements. The elucidation of matched/mismatched effects in ground-state chemical reactions was a critically important theme in the maturation of modern stereocontrolled synthesis. The development of robust methods for the control of photochemical reactions, however, is a relatively recent development, and similar cooperative stereocontrolling effects in excited-state enantioselective photoreactions have not previously been documented. Herein, we describe a tandem chiral photocatalyst/Brønsted acid strategy for highly enantioselective [2 + 2] photocycloadditions of vinylpyridines. Importantly, the matched and mismatched chiral catalyst pairs exhibit different reaction rates and enantioselectivities across a range of coupling partners. We observe no evidence of ground-state interactions between the catalysts and conclude that these effects arise from their cooperative behavior in a transient excited-state assembly. These results suggest that similar matched/mismatched effects might be important in other classes of enantioselective dual-catalytic photochemical reactions.

Functionalized hybrid magnetic catalytic systems on micro- and nanoscale utilized in organic synthesis and degradation of dyes.

Herein, a concise review of the latest developments in catalytic processes involving organic reactions is presented, focusing on magnetic catalytic systems (MCSs). In recent years, various micro- and nanoscale magnetic catalysts have been prepared through different methods based on optimized reaction conditions and utilized in complex organic synthesis or degradation reactions of pharmaceutical compounds. These biodegradable, biocompatible and eco-benign MCSs have achieved the principles of green chemistry, and thus their usage is highly advocated. In addition, MCSs can shorten the reaction time, effectively accelerate reactions, and significantly upgrade both pharmaceutical synthesis and degradation mechanisms by preventing unwanted side reactions. Moreover, the other significant benefits of MCSs include their convenient magnetic separation, high stability and reusability, inexpensive raw materials, facile preparation routes, and surface functionalization. In this review, our aim is to present at the recent improvements in the structure of versatile MCSs and their characteristics, i.e., magnetization, recyclability, structural stability, turnover number (TON), and turnover frequency (TOF). Concisely, different hybrid and multifunctional MCSs are discussed. Additionally, the applications of MCSs for the synthesis of different pharmaceutical ingredients and degradation of organic wastewater contaminants such as toxic dyes and drugs are demonstrated.

Retrosynthesis prediction using grammar-based neural machine translation: An information-theoretic approach

Retrosynthetic prediction is one of the main challenges in chemical synthesis because it requires a search over the space of plausible chemical reactions that often results in complex, multi-step, branched synthesis trees for even moderately complex organic reactions. Here, we propose an approach that performs single-step retrosynthesis prediction using SMILES grammar-based representations in a neural machine translation framework. Information-theoretic analyses of such grammar-representations reveal that they are superior to SMILES representations and are better-suited for machine learning tasks due to their underlying redundancy and high information capacity. We report the top-1 prediction accuracy of 43.8% (syntactic validity 95.6%) and maximal fragment (MaxFrag) accuracy of 50.4%. Comparing our model’s performance with previous work that used character-based SMILES representations demonstrate significant reduction in grammatically invalid predictions and improved prediction accuracy. Fewer invalid predictions for both known and unknown reaction class scenarios demonstrate the model’s ability to learn the underlying SMILES grammar efficiently.

An integrated console for capsule-based, automated organic synthesis.

The current laboratory practices of organic synthesis are labor intensive, impose safety and environmental hazards, and hamper the implementation of artificial intelligence guided drug discovery. Using a combination of reagent design, hardware engineering, and a simple operating system we provide an instrument capable of executing complex organic reactions with prepacked capsules. The machine conducts coupling reactions and delivers the purified products with minimal user involvement. Two desirable reaction classes – the synthesis of saturated N-heterocycles and reductive amination – were implemented, along with multi-step sequences that provide drug-like organic molecules in a fully automated manner. We envision that this system will serve as a console for developers to provide synthetic methods as integrated, user-friendly packages for conducting organic synthesis in a safe and convenient fashion.

Efficient Treatment of Wood Vinegar via Microbial Electrolysis Cell With the Anode of Different Pyrolysis Biochars

Microbial electrolysis cell (MEC) had a good performance during the treatment of bio-refractory wastewater. This study focused on wood vinegar (from biomass pyrolysis) treatment via MECs with biochar anode. The results indicated that MECs with coconut shell biochar as the anode had an obvious beneficial effect for treating wood vinegar. When wood vinegar was used as the substrate of MECs, COD removal reached up to 71.4%, and effluent COD was 359.0 mg COD/L. GC-MS analysis showed that furfurals present in the wood vinegar were thoroughly degraded after MEC treatment. One interesting finding is that hydrocarbons accounted for a large portion of the compounds in the effluent, which may be the comprehensive result of complex organic reactions, including decarboxylation reactions, dehydration reaction, etc. The dominant microbial populations in MEC with biochar anode mainly included Geobacter, Macellibacteroides, Oscillibacter, Sedimentibacter, Comamonas and Lachnoclostridium. In particular, Lachnoclostridium (3.34%), a new family of exoelectrogens, may be correlated with the degradation of wood vinegar. This study demonstrated that pyrolysis biochar could be incorporated as a high-efficiency MEC anode material, and MECs with the inclusion of biochar could provide a feasible way for the treatment of recalcitrant wood vinegar.

Applications of isodesmic‐type reactions for computational thermochemistry

AbstractIn computational thermochemistry, “isodesmic‐type” reactions play a significant role for obtaining accurate thermochemical quantities using low‐cost methods that can be applied to large systems. This review touches on some of the examples. For instance, a series of relative bond dissociation energies (BDEs) have been devised to calculate absolute BDEs with near‐chemical‐accuracy (~5 kJ mol−1) using density functional theory (DFT) methods. To facilitate the applicability of isodesmic‐type reactions, the connectivity‐based hierarchy (CBH) has been developed to automate the systematic generation of isodesmic‐type reaction schemes, and applied to large organic and biomolecular systems. The related netCBH scheme yields accurate reaction energies in complex organic reactions, achieving coupled‐cluster quality results at DFT cost. Isodesmic‐type reactions have been used to obtain heats of formation for medium‐sized fullerenes, with uncertainties of ~20 kJ mol−1 up to C180. In comparison, the literature C60 heat of formation has an uncertainty of 100 kJ mol−1. Importantly, it fills the gap in which heats of formation for those larger fullerenes are not available. These studies showcase how isodesmic‐type reactions propel the accuracy of quantum chemistry computations to a level that rivals or even betters modern experimental determinations, particularly for systems that are difficult to study experimentally.This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Electronic Structure Theory > Combined QM/MM Methods Theoretical and Physical Chemistry > Thermochemistry

Revealing the Adsorption and Decomposition of EP-PTCDI on a Cerium Oxide Surface.

Cerium oxide has constantly attracted intense attention during the past decade both in research and industry as an appealing catalyst or a noninert support for catalysts, for instance, in the water-gas shift reaction and hydrogenation of the ketone group. Herein, the cerium oxide surface has been chosen to investigate the adsorption and decomposition behaviors of the N,N′-bis(1-ethylpropyl)-perylene-3,4,9,10-tetracarboxdiimide (EP-PTCDI) molecule by photoelectron spectroscopy. As expected, EP-PTCDI molecules self-assemble on the cerium oxide surface comprising both trivalent and tetravalent cerium at room temperature. Interestingly, the EP-PTCDI molecule exhibits selective adsorption on cerium oxide after the heating treatment. It was found that the ketone group of EP-PTCDI first undergoes hydrogenation after annealing to 400 °C, which is probably related to the fact that high temperature annealing provides sufficient thermal energy to trigger the reaction between the ketone group and trivalent cerium. Furthermore, EP-PTCDI molecules are discovered to start to decompose hierarchically on the ceria substrate from annealing at 400 °C due to the strong molecule–substrate interaction and the effective catalysis by the trivalent cerium, whereas the decomposition sequence of functional groups is revealed to be, first, the ethyl propyl group (−C5H9), followed by the hydrogenated ketone (alcohols) group. Finally, our study may provide a new platform for the fundamental understanding of complex organic reactions on the cerium oxide surface.

IN VITRO ANTI-INFLAMMATORY ACTIVITY OF METHANOLIC EXTRACT AND DIFFERENT FRACTIONS OF CENTELLA ASIATICA LEAVES BY PROTEIN DENATURATION

Inflammation might be a complex organic reaction to a hazardous stimulant such as pathogens, or injured tissues and mainly causes itching, swelling, skin redness, warm and slight pain. Herbal drugs are widespread in India for their effectiveness, easy availability at low cost and provide low toxicity as compared to modern drugs. Centella asiatica is one of the oldest Ayurvedic medicinal plants, used in treatment of various skin diseases. The aim of our present research was to evaluate the in vitro anti-inflammatory activity of methanolic extract and different fractions of C. asiatica leaves. In protein denaturation method, the percentage inhibition for methanolic extract was observed to be 40.22%. The petroleum ether and n-butanol fraction of methanolic extract of C. asiatica were observed to exhibits 54.12 and 44.42% inhibition, respectively. Diclofenac sodium was used as a standard drug. In comparison with other fractions petroleum ether and n-butanol fractions showed best activity. The preliminary phytochemical studies of n-butanol fractions and n-butanol fractions showed the presence of terpenoids, flavonoids etc., which are used in the treatment of inflammation. Thus, we can call the latter as intense anti-inflammatory agent.

The quantum chemical study of the mechanism of the epoxidation reaction of limonene and geraniol with peracetic and perbenzoic acids

Aim. To compare the mechanism of the epoxidation reaction of terpenes Geraniol and Limonene with peracetic acid and perbenzoic acid based on the quantum chemical study. Materials and methods . For the calculation the density functional theory (approximation UBH & HLYP/6-31G (d) Gaussian 09) method was applied. The specified density functional allows to correctly describing biradical structures; it is rather economic in terms of the computer time cost, which allows its use in the study of sufficiently complex organic compounds and reactions. Results and discussion . The quantum chemical study of mechanisms of the epoxidation reaction of such terpenes as Geraniol and Limonene with peracetic and perbenzonic acids using the density functional theory (approximation UBH & HLYP/6-31G (d) Gaussian 09 program) has been conducted. It has been shown that epoxidation of geraniol with both peroxyacids occurs preferably by the double bond C 6 =C 7 due to stabilization of the corresponding transition state as a result of formation of hydrogen bond between the allyl hydroxyl group and the oxygen atom of the peroxy acid. Epoxidation of Limonene with perbenzoic and peracetic acids occurs via the cyclic double bond characterized by the lowest activation barrier, and it is consistent with the regioselectivity of the process generally known and experimentally proven. Conclusions . The results obtained are consistent with the experimental data, confirming the correctness of the use of this UBH & HLYP/6-31G (d) approach to study the regiochemical pecularities of the epoxidation process of alkenes containing several isolated double bonds.

Electroorganic Oxidation of Pyridones

Electroorganic synthesis can be utilized as a green alternative in complex organic synthesis reactions for pharmaceutical compounds, mitigating or eliminating complex stoichiometric oxidants during organic synthesis. An electrochemical oxidation reaction can make a synthetic transformation more cost effective and more efficient when compared to traditional oxidation processes. Recently, literature has indicated that in waste water treatment applications, benzene and phenols are completely oxidized, resulting in CO2 formation, but interestingly also resulting in some partial oxidation products of quinones and catechols. Following a similar scheme to intentionally produce partial electrochemical oxidation products and oxidation intermediates can yield interesting new chemistries. In this work, we will focus on heterocyclic electrochemistry and their partial oxidations specifically for pyridones. Pyridones and pyridines are considered for their possible use in biological reactions or in mimicking bioorganic processes. Various electrochemical oxidations with pyridones as an organic substrate are being explored, specifically N-alkyl pyridones. Herein, focus will be on examining various cyclic voltammograms for different supporting electrolyte systems while comparing one and two electrochemical cell systems. Reaction rates and possible electrochemical mechanisms will be developed similarly to literature on electrochemical sensors. Furthermore, the electrochemical analysis will be derived and compared to the reaction products characterized by LC-MS.

"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models.

There is an intuitive analogy of an organic chemist's understanding of a compound and a language speaker's understanding of a word. Based on this analogy, it is possible to introduce the basic concepts and analyze potential impacts of linguistic analysis to the world of organic chemistry. In this work, we cast the reaction prediction task as a translation problem by introducing a template-free sequence-to-sequence model, trained end-to-end and fully data-driven. We propose a tokenization, which is arbitrarily extensible with reaction information. Using an attention-based model borrowed from human language translation, we improve the state-of-the-art solutions in reaction prediction on the top-1 accuracy by achieving 80.3% without relying on auxiliary knowledge, such as reaction templates or explicit atomic features. Also, a top-1 accuracy of 65.4% is reached on a larger and noisier dataset.

Solving the Density Functional Conundrum: Elimination of Systematic Errors To Derive Accurate Reaction Enthalpies of Complex Organic Reactions.

The failure of available density functional methods to compute accurate reaction enthalpies of common organic reactions is well documented. Herein, we demonstrate that the disparate results from different functionals stem from the systematic errors in the underlying elementary reactions that represent the changes in the bonding environment between reactants and products. We develop a rigorous protocol to correct for these systematic errors and obtain dramatically improved results with deviations of only 1-2 kcal/mol for most functionals.

Simple Design of an Enzyme-Inspired Supported Catalyst Based on a Catalytic Triad

Summary Enzyme active sites afford an intricate interplay of functional groups to mediate complex organic and inorganic reactions. Many hydrolytic enzymes use a catalytic triad comprising three different functional residues—(Ser(-OH), Hist(-imidazole), Asp(-CO 2 H))—that catalyze the hydrolysis of numerous unique substrates. Inspired by this design, we have developed a simple one-step synthesis for preparing a new supported catalytic system in which the three reactive groups of the catalytic triad (alcohol, imidazole, and carboxylate) are incorporated into a single functional unit. These artificial active sites can be coupled to a solid-phase support (Merrifield resin) by copper(I)-catalyzed azide-alkyne cycloaddition "click chemistry," and their effectiveness as esterolysis catalysts was demonstrated. Furthermore, tuning the local hydrophobicity of the resin particles with an approach analogous to the native enzyme hydrophobic pocket increased the catalytic efficiency. Quantum mechanics and molecular dynamics computational modeling were used to probe the catalytic effect and suggested a concerted two-step mechanism and hydrophobic nanoenvironment similar to that of hydrolytic enzymes.

A Complex Catalytic Reaction Caught in the Act: Intermediates and Products Sampling Online by Liquid μ-Beam Mass Spectrometry and Theoretical Modeling.

Liquid-beam IR-laser desorption mass spectrometry has been used to monitor the reactants, intermediates, and products of a complex organic signature reaction in real time on multiple timescales directly from the liquid phase. The reaction was chosen because it has advantages in medicinal chemistry applications, and the three-component, modular construction provides a means to generate molecular diversity rapidly. Under Lewis acid catalysis, a vinylogous Mannich reaction was monitored as it generated a δ-amino-α-silyloxy-α,β-unsaturated ester, which upon hydrolysis to the corresponding α-keto ester spontaneously reacted in a [3+2] cycloannulation to the final pyrrolo[2,1-b]benzoxazole. The kinetic data were compared with predictions of quantum chemical calculations to elucidate and verify or exclude reaction pathways and mechanisms for a possible rational optimization of the reaction. The simplicity and rapid response of this approach make it a very powerful technique for online characterization of chemical reactions on timescales spanning several orders of magnitude. This enables full control over chemical reactions, thereby maximizing the product yield. This combined experimental and theoretical approach opens up a new route for the study of novel chemistry in liquid-phase reactions.

Imaging single-molecule reaction intermediates stabilized by surface dissipation and entropy.

Chemical transformations at the interface between solid/liquid or solid/gaseous phases of matter lie at the heart of key industrial-scale manufacturing processes. A comprehensive study of the molecular energetics and conformational dynamics that underlie these transformations is often limited to ensemble-averaging analytical techniques. Here we report the detailed investigation of a surface-catalysed cross-coupling and sequential cyclization cascade of 1,2-bis(2-ethynyl phenyl)ethyne on Ag(100). Using non-contact atomic force microscopy, we imaged the single-bond-resolved chemical structure of transient metastable intermediates. Theoretical simulations indicate that the kinetic stabilization of experimentally observable intermediates is determined not only by the potential-energy landscape, but also by selective energy dissipation to the substrate and entropic changes associated with key transformations along the reaction pathway. The microscopic insights gained here pave the way for the rational design and control of complex organic reactions at the surface of heterogeneous catalysts.

Mechanistic rationalization of unusual sigmoidal kinetic profiles in the Machetti-De Sarlo cycloaddition reaction.

Unusual sigmoidal kinetic profiles in the Machetti-De Sarlo base-catalyzed 1,3-dipolar cycloaddition of acrylamide to N-methylnitroacetamide are rationalized by detailed in situ kinetic analysis. A dual role is uncovered in which a substrate acts as a precursor to catalyze its own reaction. Such kinetic studies provide a general protocol for distinguishing among different mechanistic origins of induction periods in complex organic reactions.

Reaction sampling and reactivity prediction using the stochastic surface walking method.

The prediction of chemical reactivity and thus the design of new reaction systems are the key challenges in chemistry. Here, we develop an unbiased general-purpose reaction sampling method, the stochastic surface walking based reaction sampling (SSW-RS) method, and show that the new method is a promising solution for reactivity prediction of complex reaction systems. The SSW-RS method is capable of sampling both the configuration space of the reactant and the reaction space of pathways, owing to the combination of two recently developed theoretical methods, namely, the stochastic surface walking (SSW) method for potential energy surface (PES) exploration and the double-ended surface walking (DESW) method for building pathways. By integrating with first principles calculations, we show that the SSW-RS method can be applied to investigate the kinetics of complex organic reactions featuring many possible reaction channels and complex hydrogen-bonding networks, as demonstrated here using two examples, epoxypropane hydrolysis in aqueous solution and β-d-glucopyranose decomposition. Our results show that simultaneous sampling of the soft hydrogen-bonding conformations and the chemical reactions involving hard bond making/breaking can be achieved in the SSW-RS simulation, and the mechanism and kinetics can be predicted without a priori information on the system. Unexpected new chemistry for these reactions is revealed and discussed. In particular, despite many possible pathways for β-d-glucopyranose decomposition, the SSW-RS shows that only β-d-glucose and levoglucosan are kinetically preferred direct products and the 5- or 7-member ring products should be secondary products derived from β-d-glucose or levoglucosan. As a general tool for reactivity prediction, the SSW-RS opens a new route for the design of rational reactions.