Organic Reactivity Research Articles

Synthesis and luminescence properties of carbon quantum dots with core@shell structures

The luminescence stability of carbon quantum dots (CQDs) in air impedes their extensive applications. Ample –NH2 groups on the surface of a green carbon quantum dots (GCQDs) had high organic reactivity, the surface of GCQDs was modified with allyl functional groups through a simple surface substitution reaction (named as GCQD-A). The surface of the GCQD-A was continuously formed a thin organic shell by free radical copolymerization reaction with methyl methacrylate and styrene respectively, and they were named as GCQD@PMMA and GCQD@PS respectively. The allyl functional groups on the surface of GCQD-A, the shell composition of GCQD@PMMA and GCQD@PS were characterized by their 1H nuclear magnetic resonance (1H NMR) data and infrared adsorption spectra. The luminescence stabilities for GCQD@PMMA and GCQD@PS in air were greatly improved compared with that for the GCQDs. The work can provide a novel method to get stable luminescence of CQDs in air, and it will extend their application areas in solid state.

Beyond Strain Release: Delocalization-Enabled Organic Reactivity.

The release of strain energy is a fundamental driving force for organic reactions. However, absolute strain energy alone is an insufficient predictor of reactivity, evidenced by the similar ring strain but disparate reactivity of cyclopropanes and cyclobutanes. In this work, we demonstrate that electronic delocalization is a key factor that operates alongside strain release to boost, or even dominate, reactivity. This delocalization principle extends across a wide range of molecules containing three-membered rings such as epoxides, aziridines, and propellanes and also applies to strain-driven cycloaddition reactions. Our findings lead to a "rule of thumb" for the accurate prediction of activation barriers in such systems, which can be easily applied to reactions involving many of the strained building blocks commonly encountered in organic synthesis, medicinal chemistry, polymer science, and bioconjugation. Given the significance of electronic delocalization in organic chemistry, for example in aromatic π-systems and hyperconjugation, we anticipate that this concept will serve as a versatile tool to understand and predict organic reactivity.

Revisiting nucleophilicity: an index for chemical reactivity from a CDFT approach.

Understanding and predicting the nucleophilic reactivity are paramount in elucidating organic chemical reactions and designing new synthetic pathways. In this study, we propose a nucleophilicity index within the framework of Conceptual Density Functional Theory (CDFT). Through rigorous theoretical formulations, we introduce an original quantum reactivity descriptor that captures the nucleophilic propensity of molecules based on their electronic structure and chemical environment. Subsequently, this proposed index is applied to a series of nucleophiles (pyrrolidines derivatives), spanning a diverse range of chemical functionalities. Our computational assessments reveal insightful correlations between the predicted nucleophilicity index and experimental observations of nucleophilic behavior. Thereby, they offer a promising avenue for advancing the understanding of organic reactivity and guiding synthetic efforts. Experimentally, Mayr's experimental parameters accounting for nucleophilicity were selected for the pyrrolidines. This study used DFT calculations at the B3LYP/Aug-cc-pVTZ level of theory using the Gaussian 16 program. Geometry optimization was thus performed, and the methodology employed for the computation of quantum reactivity descriptor is presented. Solvent effect was also taken into account using IEFPCM, and empirical dispersion correction (GD3) was employed.

Organic Reactivity Made Easy and Accurate with Automated Multireference Calculations.

In organic reactivity studies, quantum chemical calculations play a pivotal role as the foundation of understanding and machine learning model development. While prevalent black-box methods like density functional theory (DFT) and coupled-cluster theory (e.g., CCSD(T)) have significantly advanced our understanding of chemical reactivity, they frequently fall short in describing multiconfigurational transition states and intermediates. Achieving a more accurate description necessitates the use of multireference methods. However, these methods have not been used at scale due to their often-faulty predictions without expert input. Here, we overcome this deficiency with automated multiconfigurational pair-density functional theory (MC-PDFT) calculations. We apply this method to 908 automatically generated organic reactions. We find 68% of these reactions present significant multiconfigurational character in which the automated multiconfigurational approach often provides a more accurate and/or efficient description than DFT and CCSD(T). This work presents the first high-throughput application of automated multiconfigurational methods to reactivity, enabled by automated active space selection algorithms and the computation of electronic correlation with MC-PDFT on-top functionals. This approach can be used in a black-box fashion, avoiding significant active space inconsistency error in both single- and multireference cases and providing accurate multiconfigurational descriptions when needed.

Development of a sampling protocol for collecting leaf surface material for multiphase chemistry studies.

Plant leaves and water drops residing on them interact with atmospheric oxidants, impacting the deposition and emission of trace gases and mediating leaf damage from air pollution. Characterizing the chemical composition and reactivity of the water-soluble material on leaf surfaces is thus essential for improving our understanding of atmosphere-biosphere interactions. However, the limited knowledge of sources and nature of these chemicals challenges sampling decisions. This work investigates how sampling variables and environmental factors impact the quantity and composition of water-soluble material sampled from wet leaves and proposes a flexible protocol for its collection. The ratio of solvent volume-to-leaf area, the solvent-to-leaf contact time, and environmental parameters - including the occurrence of rain, plant location and its metabolism - drive solute concentration in leaf soaks. Despite minor variations, UV-vis absorption spectra of leaf soaks are comparable to authentic raindrops collected from the same tree and share features with microbial dissolved organic matter - including overall low aromaticity, low chromophore content, and low average molecular weight. In addition to guiding the development of a sampling protocol, our data corroborate recent hypotheses on the amount, origin, nature, and reactivity of water-soluble organics on wet leaves, providing new directions of research into this highly interdisciplinary topic.

Quinacridone dyes: versatile molecules and materials for photo- and photoelectrochemical processes

We discuss the versatility of quinacridone pigment in photocatalysis, embracing water splitting, carbon dioxide reduction and organic synthesis. Applications include homogeneous catalysis, nanoparticles, covalent organic frameworks, photoelectrodes.

Synthesis of pyridine and furan based arylated ketones through palladium catalyst with DFT study of their static and frequency dependent NLO response

A series of pyridine and furan based ketones have been synthesized by Suzuki coupling of 2,6-pyridinedicarbonyl dichloride, furan-2-carbonyl chloride with various aryl boronic acids in existence of catalyst Pd(PPh3)4 and cesium carbonate in presence of toluene at 100 °C. The compounds were synthesized in good to high yields. Various functional moities were well tolerated under developed conditions of reaction. DFT studies are used to illustrate insight of geometrical, electronic, reactivity descriptor parameters optical & nonlinear optical properties and nonlinear refractive index of all synthesized compounds (3a-3g and 4a-4h). 3c is kinetically less stable and moderately reactive among all these compounds. A highest βo (1576.39 au) and nonlinear refractive index values are obtained for compound 3a where the strong electron withdrawing group (chloro-acyl group) is present at ortho position of the pyridine ring. According to the push pull mechanism, electronic displacement between electron donating and withdrawing groups through extended conjugation is responsible for change in nonlinear optical properties of the compound. Computational studies provide detail information about the synthesized compounds and their applicability in the field of organic reactivity, electronics, and optoelectronics for future work.

Comprehensive effect of water matrix on catalytic ozonation of chloride contained saline wastewater

Chloride ion (Cl−) is one of the most common anions in wastewater and saline wastewater, but its elusive effects on organics degradation are not clear yet in many cases. In this paper, the effect of Cl− on organic compounds degradation is intensively studied in catalytic ozonation of different water matrix. It was found that the effect of Cl− is almost completely reflected by transforming ·OH to reactive chlorine species (RCS), which is simultaneously competitive with organics degradation. The competition between organics and Cl− for ·OH directly determines the ratio of their consumption rate of ·OH, which depends on their concentration and reactivity with ·OH. Especially, the concentration of organics and solution pH may change greatly during organics degradation process, which will correspondingly influence the transformation rate of ·OH to RCS. Therefore, the effect of Cl− on organics degradation is not immutable, and may dynamically change. As the reaction product between Cl− and ·OH, RCS was also expected to affect the degradation of organics. But we found that Cl· had no significant contribution to the degradation of organics in catalytic ozonation, which may due to its reaction with ozone. Catalytic ozonation of a series of benzoic acid (BA) with different substituents in chloride contained wastewater was also investigated, and the results showed that the electron-donating substituents can weaken the inhibition of Cl− on BAs degradation, because they increase the reactivity of organics with ·OH, O3 and RCS.

Multistep retrosynthesis combining a disconnection aware triple transformer loop with a route penalty score guided tree search.

Computer-aided synthesis planning (CASP) aims to automatically learn organic reactivity from literature and perform retrosynthesis of unseen molecules. CASP systems must learn reactions sufficiently precisely to propose realistic disconnections, while avoiding overfitting to leave room for diverse options, and explore possible routes such as to allow short synthetic sequences to emerge. Herein we report an open-source CASP tool proposing original solutions to both challenges. First, we use a triple transformer loop (TTL) predicting starting materials (T1), reagents (T2), and products (T3) to explore various disconnection sites defined by combining systematic, template-based, and transformer-based tagging procedures. Second, we integrate TTL into a multistep tree search algorithm (TTLA) prioritizing sequences using a route penalty score (RPScore) considering the number of steps, their confidence score, and the simplicity of all intermediates along the route. Our approach favours short synthetic routes to commercial starting materials, as exemplified by retrosynthetic analyses of recently approved drugs.

Advancement in supramolecular control of organic reactivity induced by cucurbit[n]urils

Advancement in supramolecular control of organic reactivity induced by cucurbit[n]urils

Author Correction: A generalized-template-based graph neural network for accurate organic reactivity prediction

Author Correction: A generalized-template-based graph neural network for accurate organic reactivity prediction

Copper-Catalyzed Regioselective Iodoformylation of Terminal Alkynes to Access Versatile Electrophiles (E)-β-Iodo-α,β-Unsaturated Aldehydes.

Herein, we describe a method for synthesizing (E)-β-iodo-α,β-unsaturated aldehydes via the iodoformylation of terminal alkynes with TMSCF3 and NaI. This synthetic method uses inexpensive and easy-to-handle chemical feedstocks and employs a commercially available CuI catalyst. It can transform a broad range of terminal alkynes into bis-electrophile (E)-β-iodo-α,β-unsaturated aldehydes with excellent chemoselectivity, regioselectivity, and stereoselectivity. Moreover, it was demonstrated that this protocol has abundant organic reactivity.

A generalized-template-based graph neural network for accurate organic reactivity prediction

A generalized-template-based graph neural network for accurate organic reactivity prediction

Advanced Reduction Processes for Degradation of Refractory Organics in Landfill Leachate

Hydroxyl radicals generated from advanced oxidation processes (AOPs) are broadly applied to mitigation of refractory organics in landfill leachate. However, following treatment by AOPs, the wastewater still contains highly oxidized organics that are recalcitrant to further chemical oxidation, thereby providing a challenge to established wastewater-treatment technologies. This study aimed to validate whether advanced reduction processes (ARPs), an emerging chemical degradation process driven by highly reductive hydrated electrons (eaq−), can effectively decompose persistent and complex organics in a Fenton pretreated landfill leachate. Results showed that ARPs poorly cleave C-C bonds in the Fenton pretreated leachate organic matter (LOM) due to low reactivity of the mixed organics toward eaq−. However, eaq− and ultraviolet (UV) irradiation during the ARP treatment could attack certain chromophores to reduce UV254 absorbance by 53%. The transformation particularly occurred to the low-molecular-weight (<10 kDa) and hydrophobic LOM fractions. Meanwhile, the carboxylic content declined after the ARP treatment, whereas the phenolic concentration remained constant, suggesting that eaq− principally reacted with electron withdrawing groups rather than electron donating moieties on the Fenton pretreated LOM. This study highlights that ARPs can serve as a promising post-treatment after AOPs for treatment of refractory organic wastes in landfill leachate.

Sulfur radical formation from the tropospheric irradiation of aqueous sulfate aerosols

The sulfate anion radical (SO4•-) is known to be formed in the autoxidation chain of sulfur dioxide and from minor reactions when sulfate or bisulfate ions are activated by OH radicals, NO3 radicals, or iron. Here, we report a source of SO4•-, from the irradiation of the liquid water of sulfate-containing organic aerosol particles under natural sunlight and laboratory UV radiation. Irradiation of aqueous sulfate mixed with a variety of atmospherically relevant organic compounds degrades the organics well within the typical lifetime of aerosols in the atmosphere. Products of the SO4•- + organic reaction include surface-active organosulfates and small organic acids, alongside other products. Scavenging and deoxygenated experiments indicate that SO4•- radicals, instead of OH, drive the reaction. Ion substitution experiments confirm that sulfate ions are necessary for organic reactivity, while the cation identity is of low importance. The reaction proceeds at pH 1-6, implicating both bisulfate and sulfate in the formation of photoinduced SO4•-. Certain aromatic species may further accelerate the reaction through synergy. This reaction may impact our understanding of atmospheric sulfur reactions, aerosol properties, and organic aerosol lifetimes when inserted into aqueous chemistry model mechanisms.

Cycloaddition Reactivities Analyzed by Energy Decomposition Analyses and the Frontier Molecular Orbital Model.

This Account describes our quest to understand and predict organic reactivity, a principal goal of physical and theoretical organic chemistry. The focus is on the development and testing of models for the prediction of cycloaddition reactivities and selectivities. We describe the involvement of the Houk group, and other groups, in the evolution of theoretical models that can achieve ever greater accuracy as well as provide practical heuristic models for understanding and prediction.Is the venerable frontier molecular orbital (FMO) model, the basis of Kenichi Fukui's 1981 Nobel Prize, still useful, or must it be replaced with more advanced models? In particular, models such as Conceptual Density Functional, the Pauli Exclusion Model, and the recent popularity of Electrostatic Potential Plots and Dispersion Energies have not only added to our understanding, but they have also created uncertainty about whether the simple FMO heuristic model has a place in 21st century discussions. This Account addresses this issue and asserts the value of the FMO model.Beginning with brief descriptions of selected models for cycloaddition reactivity starting with early donor-acceptor (nucleophile-electrophile) charge-transfer concepts, this Account reviews Fukui's frontier molecular orbital model, Salem and Klopman's orbital, electrostatic and Pauli repulsion model, the conceptual DFT model by Parr and later by Domingo and others, the recent Houk and Bickelhaupt Distortion/Interaction Activation Strain model, and the Bickelhaupt-Hamlin's Pauli-repulsion lowering model.Computations and analyses of four well-studied Diels-Alder cycloadditions, both normal and inverse electron-demand types, are presented. Most were studied earlier in our published work but are presented here with new insights from calculations with modern methods. Depending on the types of substrates (cycloaddends), the dominant factors controlling reactivity can be orbital interactions, electrostatics and polarization, or Pauli repulsion and dispersion effects, or a combination of all of these.By comparing orbital interactions, especially the frontier molecular orbital interactions, with the other factors that influence reactivity, we show why the FMO model is such a powerful─and theoretically meaningful─heuristic for understanding and predicting reactivity. We also present a method to understand Pauli repulsion effects on activation barriers, ρ(1.1). The use of a new reaction coordinate, the extent of Pauli repulsion along the reaction path, is advocated to emphasize the role of repulsive occupied orbital interactions on reactivity.Fukui's frontier molecular orbital model is effective because FMO interactions parallel all the quantities that influence reactivity. The FMO model continues to provide a practical model to understand and guide experiments.

Exploring Deep Learning of Quantum Chemical Properties for Absorption, Distribution, Metabolism, and Excretion Predictions.

Quantum mechanical (QM) descriptors of small molecules have wide applicability in understanding organic reactivity and molecular properties, but the substantial compute cost required for ab initio QM calculations limits their broad usage. Here, we investigate the use of deep learning for predicting QM descriptors, with the goal of enabling usage of near-QM accuracy electronic properties on large molecular data sets such as those seen in drug discovery. Several deep learning approaches have previously been benchmarked on a published data set called QM9, where 12 ground-state properties have been calculated for molecules with up to nine heavy atoms, limited to C, H, N, O, and F elements. To advance the work beyond the QM9 chemical space and enable application to molecules encountered in drug discovery, we extend the QM9 data set by creating a QM9-extended data set covering an additional ∼20,000 molecules containing S and Cl atoms. Using this extended set, we generate new deep learning models as well as leverage ANI-2x models to provide predictions on larger, more diverse molecules common in drug discovery, and we find the models estimate 11 of 12 ground-state properties reasonably. We use the predicted QM descriptors to augment graph convolutional neural network (GCNN) models for selected ADME end points (rat microsomal clearance, hepatic clearance, total clearance, and P-glycoprotein efflux) and found varying degrees of performance improvement compared to nonaugmented GCNN models, including pronounced improvement in P-glycoprotein efflux prediction.

Spectroscopic, computational and mechanistic studies on regio- and stereoselectivity of the 1,3-dipolar cycloaddition reaction in the synthesis of dispiro[indoline-3,2′-pyrrolidine-3′,3"-indolines] festooned with pyrene moiety

• Novel polyheterocyclic pyrene-grafted dispiro-pyrrolidine oxindolines have synthesized. • 1D and 2D-NMR spectroscopy found to be excellent tool for confirmation of the regio- and stereochemistry of the cycloadducts. • The regioselectivity were studied by evaluating global and local electrophilicity and nucleophilicity descriptors. • local descriptors Parr functions proposed by Domingo is promising indices to explain the regioselectivity of cycloaddition processes. An efficient and catalyst-free multicomponent sequence for synthesizing fused new polyheterocyclic pyrene-grafted dispiro-pyrrolidine oxindolines through 1,3-dipolar cycloaddition reaction mediated by non-stabilized azomethine ylides is reported herein. The regio- and stereochemistry of the cycloadducts were determined on the basis of one-dimensional (1D) and two-dimensional (2D) homonuclear and heteronuclear correlation NMR spectroscopy. The mechanism of the cycloaddition reaction, as well as regioselectivity were discussed by evaluating global and local electrophilicity and nucleophilicity descriptors at B3LYP/6-31G level of theory. The findings suggested that the polarity and charge transfer flow between azomethine ylides (dipole) and 5-chloro-3-(2-oxo-2-(pyren-1-yl)ethylidene)indolin-2-ones (dipolarophiles) was consistent with the global reactivity descriptors and substitutional pattern. These outcomes based on local descriptors Parr functions proposed by Domingo were found to be quite promising indices for the study of organic reactivity and to explain the regioselectivity of cycloaddition processes.

Luminescence color regulation of carbon quantum dots by surface modification

Labelling various biological molecules with multi-color carbon quantum dots (CQDs) in the same scene has great potential application for investigating the relationship between those molecules. It is still a great challenge to regulate the color of CQDs. Ample –NH2 groups on the surface of green carbon quantum dots (GCQDs) were characterized and confirmed by 1H nuclear magnetic resonance (1H NMR) data. As–NH2 groups had high organic reactivity, the surface of GCQDs was designed and modified with several organic functional groups through a simple surface modification strategy of organic reactions. The surface band gap states of GCQDs were tuned gradually by the corresponding modified functional groups, and the emission colors of GCQDs were tuned from green to yellow-green, then to orange, and finally to red. All the emission spectra for these multicolor carbon quantum dots (M-CQDs) were excitation independent, and the lifetimes for the M-CQDs were mainly determined by the second electron decay process from the surface defect band states. The red-shift colors for the M-CQDs were ascribed to the emissions from their surface defect band states, and the luminescence mechanism had been investigated. This work opens up a novel synthesis strategy to regulate the emission colors of carbon quantum dots.

Characterization of student problem solving and development of a general workflow for predicting organic reactivity

A central practice in the discipline of organic chemistry is the ability to solve certain fundamental problems, including predicting reactivity, proposing mechanisms, and designing syntheses. These problems are encountered frequently by both students and practitioners, who need to utilize vast amounts of content knowledge in specific ways to generate reasonable solutions. To gain insight into how one of these major problem types can be solved, we have investigated student approaches to complex predict-the-product problems through the detailed analysis of think-aloud interviews. This work led to the creation of a general workflow model that describes the reasoning pathways of students with varying levels of expertise when attempting to predict organic reactivity. The problems used in this study were designed to be non-trivial and potentially ambiguous to elicit “true” problem solving and discourage a purely memorization-based approach, even from more experienced organic chemists. Rich descriptions of undergraduate and graduate student interviews are provided, and student thought processes are characterized in terms of common problem-solving actions. These actions were developed into the workflow model using an iterative method that combined results from our analysis with the experiences of instructors and feedback from both undergraduate focus groups and graduate students. The workflow serves as both a potential instructional tool and a model for student thinking. This model is general enough to be applied to both successful and unsuccessful solution pathways by both novice undergraduates and more expert-like graduate students. Characteristics of more successful and more experienced problem solvers are investigated, and concrete strategies that can be recommended to students are discussed. The results of this study complement existing work on other fundamental problem types in organic chemistry and suggest a variety of teaching interventions to develop students into more successful organic problem solvers.