Discovery Of Reactions Research Articles

Glycopolymer Microarrays with Sub-Femtomolar Avidity for Glycan Binding Proteins Prepared by Grafted-To/Grafted-From Photopolymerizations.

We report a novel glycan array architecture that binds the mannose-specific glycan binding protein, concanavalin A (ConA), with sub-femtomolar avidity. A new radical photopolymerization developed specifically for this application combines the grafted-from thiol-(meth)acrylate polymerization with thiol-ene chemistry to graft glycans to the growing polymer brushes. The propagation of the brushes was studied by carrying out this grafted-to/grafted-from radical photopolymerization (GTGFRP) at >400 different conditions using hypersurface photolithography, a printing strategy that substantially accelerates reaction discovery and optimization on surfaces. The effect of brush height and the grafting density of mannosides on the binding of ConA to the brushes was studied systematically, and we found that multivalent and cooperative binding account for the unprecedented sensitivity of the GTGFRP brushes. This study further demonstrates the ease with which new chemistry can be tailored for an application as a result of the advantages of hypersurface photolithography.

Glycopolymer Microarrays with Sub‐Femtomolar Avidity for Glycan Binding Proteins Prepared by Grafted‐To/Grafted‐From Photopolymerizations

AbstractWe report a novel glycan array architecture that binds the mannose‐specific glycan binding protein, concanavalin A (ConA), with sub‐femtomolar avidity. A new radical photopolymerization developed specifically for this application combines the grafted‐from thiol–(meth)acrylate polymerization with thiol–ene chemistry to graft glycans to the growing polymer brushes. The propagation of the brushes was studied by carrying out this grafted‐to/grafted‐from radical photopolymerization (GTGFRP) at >400 different conditions using hypersurface photolithography, a printing strategy that substantially accelerates reaction discovery and optimization on surfaces. The effect of brush height and the grafting density of mannosides on the binding of ConA to the brushes was studied systematically, and we found that multivalent and cooperative binding account for the unprecedented sensitivity of the GTGFRP brushes. This study further demonstrates the ease with which new chemistry can be tailored for an application as a result of the advantages of hypersurface photolithography.

Unlocking the Potential of High-Throughput Experimentation for Electrochemistry with a Standardized Microscale Reactor.

Organic electrochemistry has emerged as an enabling and sustainable technology in modern organic synthesis. Despite the recent renaissance of electrosynthesis, the broad adoption of electrochemistry in the synthetic community, and especially in industrial settings, has been hindered by the lack of general, standardized platforms for high-throughput experimentation (HTE). Herein, we disclose the design of the HTe–Chem, a high-throughput microscale electrochemical reactor that is compatible with existing HTE infrastructure and enables the rapid evaluation of a broad array of electrochemical reaction parameters. Utilizing the HTe–Chem to accelerate reaction optimization, reaction discovery, and chemical library synthesis is illustrated using a suite of oxidative and reductive transformations under constant current, constant voltage, and electrophotochemical conditions.

Simultaneously improving reaction coverage and computational cost in automated reaction prediction tasks.

Automated reaction prediction has the potential to elucidate complex reaction networks for applications ranging from combustion to materials degradation, but computational cost and inconsistent reaction coverage are still obstacles to exploring deep reaction networks. Here we show that cost can be reduced and reaction coverage can be increased simultaneously by relatively straightforward modifications of the reaction enumeration, geometry initialization and transition state convergence algorithms that are common to many prediction methodologies. These components are implemented in the context of yet another reaction program (YARP), our reaction prediction package with which we report reaction discovery benchmarks for organic single-step reactions, thermal degradation of a γ-ketohydroperoxide, and competing ring-closures in a large organic molecule. Compared with recent benchmarks, YARP (re)discovers both established and unreported reaction pathways and products while simultaneously reducing the cost of reaction characterization by nearly 100-fold and increasing convergence of transition states. This combination of ultra-low cost and high reaction coverage creates opportunities to explore the reactivity of larger systems and more complex reaction networks for applications such as chemical degradation, where computational cost is a bottleneck.

The Cold Fusion Phenomenon – Nuclear Reactions in the CF Materials at Around Room Temperature

Since the discovery of nuclear reactions in PdDx alloys at around room temperature in 1989, there have been accumulated very many experimental data sets showing existence of nuclear reactions in solid materials composed of transition metals and occluded hydrogen isotopes (let us call them the CF materials, for short) resulting in various nuclear products such as neutrons, tritium, transmuted nuclei, and others accompanied with large excess energies at relatively low temperatures up to 1000°C (let us call these whole events the cold fusion phenomenon (CFP), for short). As the cause of these nuclear reactions in the CFP, we have to accept the existence of the interactions between nuclei in the CF material through the nuclear force (let us call this interaction the nuclear-force interaction, for short) recognized its existence in the nucleus in the nuclear physics. We can classify the CF materials, i.e. materials where CFP occurs, into three groups: (1) metallic material including transition-metal hydrides (e.g. NiHx, AuHx) and deuterides (e.g. PdDx, TiDx), (2) carbonic material including hydrogen graphite (HCx) and XLPE (cross-linked polyethylene) and (3) biological material including microorganisms, microbial cultures and biological tissues or organs. We will explain the characteristics of the CFP observed in each group in this paper. The nuclear reactions in the CF material gives rise to production of new particles from neutron, triton, and new nuclei with proton numbers Z up to 83 accompanying enormous excess energy. In addition to these events, there occurs the stabilization of unstable nuclei, including the decay-time shortening of radioactive nuclei, which is especially interesting to apply it to treat hazardous nuclear waste produced by the nuclear power plant. Finally, we give an overview of the CFP in relation to the solid state-nuclear physics and the solid state-nuclear chemistry where the nuclear-force interaction may play important roles to explain the riddles found but not given appropriate explanations in these old sciences hitherto.

Spearheading the Electrification of Chemical Manufacturing with Smart Organic Electrosynthesis

Chemical innovation and new molecule development are at the heart of pharmaceutical technologies that commit to the delivery of the finest treatments for challenging diseases. Organic electrosynthesis offers multiple advantages within the industry, enabling the synthesis of new molecules and offering opportunities for more sustainable manufacturing processes through reduced waste streams, near-ambient operating conditions, and a reduced number of reaction steps. However, despite these advantages, electrochemical process development in pharma is often hindered by lengthy and complex optimization approaches, which are required to ensure the purity and selectivity necessary for successful manufacturing. In fact, developing and optimizing electrochemical reactions repeatedly requires extensive experimental campaigns to elucidate reactive behavioral trends and the effect of relevant process variables (e.g. reactant concentrations, electrode potential, temperature, pressure, flow rates) on reaction performance.Machine-learning (ML) predictive algorithms can be used to predict reaction performance, removing the need for exhaustive experimentation in reaction discovery and process development. However, most ML-enabled systems require the use of large datasets (i.e. 100’s-1000’s of points) to deliver accurate predictions, while gathering experimental points is expensive in human and material resources. The challenge of building large datasets can be averted by developing an innovative framework around the use of supervised machine learning (SL) and active learning (AL) tools. SL models can use small datasets to predict system performance for a significantly larger number of experimental conditions. However, prediction accuracy is heavily reliant on the presence of statistically significant points in the training dataset, which can be challenging to pinpoint. To circumvent this issue, we couple SL with AL algorithms, enabling informed and smart decisions on the experimental campaign design, ultimately reducing the number of experiments required to achieve reliable predictions of reaction behavior.Addressing fundamental questions regarding the limitations of a disruptive AL-enhanced ML predictive approach, we elucidate the pathway for the design and implementation of intelligent experimental campaigns in organic electrosynthesis. The insights from this work innovate on the future of reaction engineering and process optimization, while lowering the barrier to implementation of more sustainable electrochemical processes in pharmaceuticals and other sectors of the chemical industry. Figure 1

Well-defined organometallic Copper(III) complexes: Preparation, characterization and reactivity

• Organocopper(III) are key intermediates in a variety of copper-catalyzed cross-coupling reactions. • Four types of well-defined organocopper(III) complexes were summarized. • Development of organocopper(III) complexes will boost the new reaction discovery. Organocopper(III) species were generally considered as the key intermediates in a variety of copper-catalyzed cross-coupling reactions, aerobic oxidations, as well as enzyme-catalyzed oxidation reactions. The preparation and characterization of thermal stable organocopper(III) complexes, as well as investigation of their elementary bond-forming reductive elimination is missing in the chemistry map for a longtime, and is urgently needed, since these studies would deepen our understanding about the fundamentals of the copper catalysis and boost the new reaction discovery. In this review, the preparation and characterization of four types of well-defined copper(III) complexes including copper(III) complexes without copper-carbon bond, organocopper(III) complexes with rigid macrocyclic ligands, organocopper(III) complexes with fluoroalkylated ligands and other organocopper(III) complexes were summarized. In addition, the reactivities as well as bond-forming reductive elimination elementary reactions of a few organocopper(III) complexes were also discussed.

Deconstruction of Lignin: From Enzymes to Microorganisms.

Lignocellulosic residues are low-cost abundant feedstocks that can be used for industrial applications. However, their recalcitrance currently makes lignocellulose use limited. In natural environments, microbial communities can completely deconstruct lignocellulose by synergistic action of a set of enzymes and proteins. Microbial degradation of lignin by fungi, important lignin degraders in nature, has been intensively studied. More recently, bacteria have also been described as able to break down lignin, and to have a central role in recycling this plant polymer. Nevertheless, bacterial deconstruction of lignin has not been fully elucidated yet. Direct analysis of environmental samples using metagenomics, metatranscriptomics, and metaproteomics approaches is a powerful strategy to describe/discover enzymes, metabolic pathways, and microorganisms involved in lignin breakdown. Indeed, the use of these complementary techniques leads to a better understanding of the composition, function, and dynamics of microbial communities involved in lignin deconstruction. We focus on omics approaches and their contribution to the discovery of new enzymes and reactions that impact the development of lignin-based bioprocesses.

Mechanistic investigation of Rh(i)-catalysed asymmetric Suzuki–Miyaura coupling with racemic allyl halides

Understanding how catalytic asymmetric reactions with racemic starting materials can operate would enable new enantioselective cross-coupling reactions that give chiral products. Here we propose a catalytic cycle for the highly enantioselective Rh(i)-catalysed Suzuki–Miyaura coupling of boronic acids and racemic allyl halides. Natural abundance 13C kinetic isotope effects provide quantitative information about the transition-state structures of two key elementary steps in the catalytic cycle, transmetallation and oxidative addition. Experiments with configurationally stable, deuterium-labelled substrates revealed that oxidative addition can happen via syn- or anti-pathways, which control diastereoselectivity. Density functional theory calculations attribute the extremely high enantioselectivity to reductive elimination from a common Rh complex formed from both allyl halide enantiomers. Our conclusions are supported by analysis of the reaction kinetics. These insights into the sequence of bond-forming steps and their transition-state structures will contribute to our understanding of asymmetric Rh–allyl chemistry and enable the discovery and application of asymmetric reactions with racemic substrates. A major drive in current chemistry research is to develop asymmetric versions of widely used carbon–carbon bond-forming reactions, such as Suzuki-Miyaura cross-couplings. Now, the origins of diastereo- and enantioselectivity in a Rh-catalysed cross-coupling of boronic acid and racemic allyl halides have been established.

Identifying Barrierless Mechanisms for Benzene Formation in the Interstellar Medium Using Permutationally Invariant Reaction Discovery.

Complex chemical reaction environments, such as those found in combustion engines, the upper atmosphere, or the interstellar medium, can contain large numbers of different reactive species participating in similarly large numbers of different chemical reactions. In such settings, identifying the most-likely multistep reaction mechanisms which lead to the production of a particular defined product species is an extremely challenging problem, requiring search and evaluation over a large number of different possible candidate mechanisms while also addressing the permutational challenges posed when considering a large number of reaction routes available to sets of identical molecular species. In this article, the problem of generating candidate reaction mechanisms which form a defined product from a diverse set of reactive molecules is cast as a discrete optimization of a permutationally invariant cost function describing similarity between the target product and the product generated by a trial reaction mechanism. This approach is demonstrated by generating 2230 candidate reaction mechanisms which form benzene from diverse sets of reactive molecules which have been experimentally identified in the interstellar medium. By screening this set of autogenerated mechanisms, using dispersion-corrected DFT to evaluate reaction energies and activation barriers, we identify several candidate barrierless reaction mechanisms (both previously proposed and new) for benzene formation which may operate in the low temperatures found in the interstellar medium and could be investigated further to supplement existing microkinetic models.

Discovery of novel chemical reactions by deep generative recurrent neural network

The “creativity” of Artificial Intelligence (AI) in terms of generating de novo molecular structures opened a novel paradigm in compound design, weaknesses (stability & feasibility issues of such structures) notwithstanding. Here we show that “creative” AI may be as successfully taught to enumerate novel chemical reactions that are stoichiometrically coherent. Furthermore, when coupled to reaction space cartography, de novo reaction design may be focused on the desired reaction class. A sequence-to-sequence autoencoder with bidirectional Long Short-Term Memory layers was trained on on-purpose developed “SMILES/CGR” strings, encoding reactions of the USPTO database. The autoencoder latent space was visualized on a generative topographic map. Novel latent space points were sampled around a map area populated by Suzuki reactions and decoded to corresponding reactions. These can be critically analyzed by the expert, cleaned of irrelevant functional groups and eventually experimentally attempted, herewith enlarging the synthetic purpose of popular synthetic pathways.

Photocatalyzed Dual-Oxidative Trifluoromethylthio-Trifluoromethylation of Alkenes with CF 3 SO 2 Na

A novel photocatalyzed trifluoromethylthio-trifluoromethylation of alkenes has been developed, using CF3SO2Na as both CF3 and SCF3 source. This photocatalyzed dual-oxidative strategy, which combine...

BIAN-NHC Ligands in Transition-Metal-Catalysis: A Perfect Union of Sterically Encumbered, Electronically Tunable N-Heterocyclic Carbenes?

The discovery of NHCs (NHC = N-heterocyclic carbenes) as ancillary ligands in transition-metal-catalysis ranks as one of the most important developments in synthesis and catalysis. It is now well-recognized that the strong σ-donating properties of NHCs along with the ease of scaffold modification and a steric shielding of the N-wingtip substituents around the metal center enable dramatic improvements in catalytic processes, including the discovery of reactions that are not possible using other ancillary ligands. In this context, although the classical NHCs based on imidazolylidene and imidazolinylidene ring systems are now well-established, recently tremendous progress has been made in the development and catalytic applications of BIAN-NHC (BIAN = bis(imino)acenaphthene) class of ligands. The enhanced reactivity of BIAN-NHCs is a direct result of the combination of electronic and steric properties that collectively allow for a major expansion of the scope of catalytic processes that can be accomplished using NHCs. BIAN-NHC ligands take advantage of (1) the stronger σ-donation, (2) lower lying LUMO orbitals, (3) the presence of an extended π-system, (4) the rigid backbone that pushes the N-wingtip substituents closer to the metal center by buttressing effect, thus resulting in a significantly improved control of the catalytic center and enhanced air-stability of BIAN-NHC-metal complexes at low oxidation state. Acenaphthoquinone as a precursor enables facile scaffold modification, including for the first time the high yielding synthesis of unsymmetrical NHCs with unique catalytic properties. Overall, this results in a highly attractive, easily accessible class of ligands that bring major advances and emerge as a leading practical alternative to classical NHCs in various aspects of catalysis, cross-coupling and C-H activation endeavors.

Adverse Drug Reaction Discovery Using a Tumor-Biomarker Knowledge Graph.

Adverse drug reactions (ADRs) are a major public health concern, and early detection is crucial for drug development and patient safety. Together with the increasing availability of large-scale literature data, machine learning has the potential to predict unknown ADRs from current knowledge. By the machine learning methods, we constructed a Tumor-Biomarker Knowledge Graph (TBKG) which contains four types of node: Tumor, Biomarker, Drug, and ADR using biomedical literatures. Based on this knowledge graph, we not only discovered potential ADRs of antitumor drugs but also provided explanations. Experiments on real-world data show that our model can achieve 0.81 accuracy of three cross-validation and the ADRs discovery of Osimertinib was chosen for the clinical validation. Calculated ADRs of Osimertinib by our model consisted of the known ADRs which were in line with the official manual and some unreported rare ADRs in clinical cases. Results also showed that our model outperformed traditional co-occurrence methods. Moreover, each calculated ADRs were attached with the corresponding paths of “tumor-biomarker-drug” in the knowledge graph which could help to obtain in-depth insights into the underlying mechanisms. In conclusion, the tumor-biomarker knowledge-graph based approach is an explainable method for potential ADRs discovery based on biomarkers and might be valuable to the community working on the emerging field of biomedical literature mining and provide impetus for the mechanism research of ADRs.

Automation isn't automatic.

Automation has become an increasingly popular tool for synthetic chemists over the past decade. Recent advances in robotics and computer science have led to the emergence of automated systems that execute common laboratory procedures including parallel synthesis, reaction discovery, reaction optimization, time course studies, and crystallization development. While such systems offer many potential benefits, their implementation is rarely automatic due to the highly specialized nature of synthetic procedures. Each reaction category requires careful execution of a particular sequence of steps, the specifics of which change with different conditions and chemical systems. Careful assessment of these critical procedural requirements and identification of the tools suitable for effective experimental execution are key to developing effective automation workflows. Even then, it is often difficult to get all the components of an automated system integrated and operational. Data flows and specialized equipment present yet another level of challenge. Unfortunately, the pain points and process of implementing automated systems are often not shared or remain buried deep in the SI. This perspective provides an overview of the current state of automation of synthetic chemistry at the benchtop scale with a particular emphasis on core considerations and the ensuing challenges of deploying a system. Importantly, we aim to reframe automation as decidedly not automatic but rather an iterative process that involves a series of careful decisions (both human and computational) and constant adjustment.

Blood Relations: Transfusion and the Making of Human Genetics by Jenny Bangham

Reviewed by: Blood Relations: Transfusion and the Making of Human Genetics by Jenny Bangham Boel Berner (bio) Blood Relations: Transfusion and the Making of Human Genetics By Jenny Bangham. Chicago: University of Chicago Press, 2020. Pp. 328. Blood Relations: Transfusion and the Making of Human Genetics By Jenny Bangham. Chicago: University of Chicago Press, 2020. Pp. 328. The 1952 British film Emergency Call tells the tear-jerking story of a five-year-old girl suffering life-threatening blood loss after an accident. An intense medical and police search ensues to find donors with her extremely rare blood group (there are three)—and one of them turns out to be Black. But blood has no color other than red, the film's doctor affirms: "White, Black, brown, yellow; human blood's the same the world over." And the girl survives. Jenny Bangham's book Blood Relations analyzes the postwar scientific and medical themes captured in the film. Bangham expertly traces the connections between the search for new and rare blood groups, the mapping of ostensibly race-neutral genetic differences in populations across the world, and the crucial role of bureaucratic networks with detailed information about donors and blood groups. She thus sheds new light on the twentieth-century history of genetics. Her book starts with the 1939 British war effort to secure a reliable blood supply for transfusions. This meant setting up local blood depots and systems for blood typing almost a million donors. British geneticists seized this information and created linkages between their laboratories and the blood depots. Blood circulated through society, via donors to recipients and research institutions. So did paper—protocols, registries, index cards, and labels—enabling ground-breaking analyses of blood group inheritance and human diversity. Bangham then backtracks to capture the pre-history of these efforts, from Landsteiner's discovery of strange agglutination reactions in 1900, via studies certifying that blood groups are stable across a person's lifetime and inherited in a Mendelian pattern, to blood group analysis for criminal and paternity cases in the interwar years. These scientific advances made it possible to trace the distribution of blood groups across populations, a practice with clear racist undertones in many countries. British researchers in the 1930s strove to avoid this bias and change eugenics into human genetics oriented towards finding, for example, the genetic patterns behind diseases. The institutionalized systems set up in Britain during the war provided material for extensive studies. Bangham tells the previously [End Page 908] untold story of these endeavors and their growing national and international importance after World War II. Using a wealth of archival material, she portrays the multifaceted assemblage of human and non-human elements required to study human genetics: bodies, populations, and the precious raw materials of blood cells and antisera. Scientific advance, she argues, is not merely theory and laboratory work. It also involves mundane things like mail delivery vans, administration, pipettes, and freezers. Bangham's narrative stays close to the scientific actors involved and their often impressive capacity to build networks of contacts and financial support. But she also problematizes the decisions involved in some of the research, most interestingly in the postwar British studies to map blood groups across the world in a purportedly non-racist way. It involved a vast scheme of blood collection from local populations overseas and masses of samples and protocols being sent for analysis to the London institute led by Arthur Mourant. However, as Bangham's careful analysis shows, even this endeavor had a hidden racist bias. Mourant used systems of classification based on pre-war stereotypes to sort people into population categories. He relied upon local informers' selection of which individuals to bleed and their hunches of what ethnic groups these individuals belonged to. Therefore, the value of these vast studies has been contested. By the 1960s, too, genetics had evolved. The tools and materials of human genetics were increasingly decoupled from the collection of therapeutic human blood—the very relationship on which British geneticists had built their wartime and postwar achievements. Present-day genetics, too, as Bangham notes by the end of her original and well-written study, comes with a promise of a neutral way to...

Oxidative cross-coupling processes inspired by the Chan-Lam reaction.

The Cu-catalyzed oxidative cross-coupling of N- and O-nucleophiles with aryl boronic acids (the Chan-Lam reaction) remains among the most useful approaches to prepare aniline and phenol derivatives. The combination of high chemoselectivity, mild reaction conditions, and the ability to use simple Cu-salts as catalysts makes this process a valuable alternative to aromatic substitutions and Pd-catalyzed reactions of aryl electrophiles (Buchwald-Hartwig coupling). Despite the widespread use of Chan-Lam reactions in synthesis, the analogous carbon-carbon bond forming variant of this process had not been developed prior to our work. This feature article describes our discovery and application of Cu-catalyzed oxidative coupling reactions of activated methylene derivatives or carboxylic acids with nucleophiles including aryl boronic esters and amines.

Carbo- and Heterocycle Syntheses via Reactions between Two Multiple Bonds; Involving Heteroatom-Substituted Unsaturated Bonds

Cyclization reactions between two multiple bonds have been fascinating processes that allow the discovery of new reactions and the construction of carbo- and/or heterocycles. Among multiple bonds, heteroatom-substituted olefins have different reactivity from those having heteroatom on the allylic or homoallylic position, but the reactions have been reported few cases until the 2000s. Lately, the reactions between multiple bonds and heteroatom-substituted olefins have been reported, and this review explains them by the reaction class.

The Cold Fusion Phenomenon – Nuclear Reactions in the CF Materials at Around Room Temperature

Since the discovery of nuclear reactions in PdD_x alloys at around room temperature in 1989, there have been accumulated very many experimental data sets showing existence of nuclear reactions in solid materials composed of transition metals and occluded hydrogen isotopes (let us call them the <i>CF materials</i>, for short) resulting in various nuclear products such as neutrons, tritium, transmuted nuclei, and others accompanied with large excess energies at relatively low temperatures up to 1000°C (let us call these whole events the <i>cold fusion phenomenon</i> (<I>CFP</I>), for short). As the cause of these nuclear reactions in the CFP, we have to accept the existence of the interactions between nuclei in the CF material through the nuclear force<i> </i>(let us call this interaction the<i> nuclear-force interaction,</i> for short) recognized its existence in the nucleus in the nuclear physics. We can classify the CF materials, i.e. materials where CFP occurs, into three groups: (1) metallic material including transition-metal hydrides (e.g. NiH_x, AuH_x) and deuterides (e.g. PdD_x, TiD_x), (2) carbonic material including hydrogen graphite (HC_x) and XLPE (cross-linked polyethylene) and (3) biological material including microorganisms, microbial cultures and biological tissues or organs. We will explain the characteristics of the CFP observed in each group in this paper. The nuclear reactions in the CF material gives rise to production of new particles from neutron, triton, and new nuclei with proton numbers <I>Z</I> up to 83 accompanying enormous excess energy. In addition to these events, there occurs the stabilization of unstable nuclei, including the decay-time shortening of radioactive nuclei, which is especially interesting to apply it to treat hazardous nuclear waste produced by the nuclear power plant. Finally, we give an overview of the CFP in relation to the solid state-nuclear physics and the solid state-nuclear chemistry where the nuclear-force interaction may play important roles to explain the riddles found but not given appropriate explanations in these old sciences hitherto.

The non-adiabatic nanoreactor: towards the automated discovery of photochemistry.

The ab initio nanoreactor has previously been introduced to automate reaction discovery for ground state chemistry. In this work, we present the nonadiabatic nanoreactor, an analogous framework for excited state reaction discovery. We automate the study of nonadiabatic decay mechanisms of molecules by probing the intersection seam between adiabatic electronic states with hyper-real metadynamics, sampling the branching plane for relevant conical intersections, and performing seam-constrained path searches. We illustrate the effectiveness of the nonadiabatic nanoreactor by applying it to benzene, a molecule with rich photochemistry and a wide array of photochemical products. Our study confirms the existence of several types of S0/S1 and S1/S2 conical intersections which mediate access to a variety of ground state stationary points. We elucidate the connections between conical intersection energy/topography and the resulting photoproduct distribution, which changes smoothly along seam space segments. The exploration is performed with minimal user input, and the protocol requires no previous knowledge of the photochemical behavior of a target molecule. We demonstrate that the nonadiabatic nanoreactor is a valuable tool for the automated exploration of photochemical reactions and their mechanisms.