Exploration of Reaction Pathways and Chemical Transformation Networks

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

Policies and Motivations for the CO2 Valorization through the Sabatier Reaction Using Structured Catalysts. A Review of the Most Recent Advances

The current scenario where the effects of global warming are more and more evident, has motivated different initiatives for facing this, such as the creation of global policies with a clear environmental guideline. Within these policies, the control of Greenhouse Gase (GHG) emissions has been defined as mandatory, but for carrying out this, a smart strategy is proposed. This is the application of a circular economy model, which seeks to minimize the generation of waste and maximize the efficient use of resources. From this point of view, CO2 recycling is an alternative to reduce emissions to the atmosphere, and we need to look for new business models which valorization this compound which now must be considered as a renewable carbon source. This has renewed the interest in known processes for the chemical transformation of CO2 but that have not been applied at industrial level because they do not offer evident profitability. For example, the methane produced in the Sabatier reaction has a great potential for application, but this depends on the existence of a sustainable supply of hydrogen and a greater efficiency during the process that allows maximizing energy efficiency and thermal control to maximize the methane yield. Regarding energy efficiency and thermal control of the process, the use of structured reactors is an appropriate strategy. The evolution of new technologies, such as 3D printing, and the consolidation of knowledge in the structing of catalysts has enabled the use of these reactors to develop a wide range of possibilities in the field. In this sense, the present review presents a brief description of the main policies that have motivated the transition to a circular economy model and within this, to CO2 recycling. This allows understanding, why efforts are being focused on the development of different reactions for CO2 valorization. Special attention to the case of the Sabatier reaction and in the application of structured reactors for such process is paid

Kinetic Intersections as a Source of Information on Rate Coefficients

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Evaluation of an intensified continuous heat-exchanger reactor for inherently safer characteristics

The present paper deals with the establishment of a new methodology in order to evaluate the inherently safer characteristics of a continuous intensified reactor in the case of an exothermic reaction. The transposition of the propionic anhydride esterification by 2-butanol into a new prototype of ‘‘heatexchanger/ reactor’’, called open plate reactor (OPR), designed by Alfa Laval Vicarb has been chosen as a case study. Previous studies have shown that this exothermic reaction is relatively simple to carry out in a homogeneous liquid phase, and a kinetic model is available. A dedicated software model is then used not only to assess the feasibility of the reaction in the ‘‘heat-exchanger/reactor’’ but also to estimate the temperature and concentration profiles during synthesis and to determine optimal operating conditions for safe control. Afterwards the reaction was performed in the reactor. Good agreement between experimental results and the simulation validates the model to describe the behavior of the process during standard runs. A hazard and operability study (HAZOP) was then applied to the intensified process in order to identify the potential hazards and to provide a number of runaway scenarios. Three of them are highlighted as the most dangerous: no utility flow, no reactant flows, both stop at the same time. The behavior of the process is simulated following the stoppage of both the process and utility fluid. The consequence on the evolution of temperature profiles is then estimated for a different hypothesis taking into account the thermal inertia of the OPR. This approach reveals an intrinsically safer behavior of the OPR

DNA hybridization catalysts and catalyst circuits

Practically all of life's molecular processes, from chemical synthesis to replication, involve enzymes that carry out their functions through the catalysis of metastable fuels into waste products. Catalytic control of reaction rates will prove to be as useful and ubiquitous in DNA nanotechnology as it is in biology. Here we present experimental results on the control of the decay rates of a metastable DNA "fuel". We show that the fuel complex can be induced to decay with a rate about 1600 times faster than it would decay spontaneously. The original DNA hybridization catalyst [15] achieved a maximal speed-up of roughly 30. The fuel complex discussed here can therefore serve as the basic ingredient for an improved DNA hybridization catalyst. As an example application for DNA hybridization catalysts, we propose a method for implementing arbitrary digital logic circuits

Structural Material Property Tailoring Using Deep Neural Networks

Advances in robotics, artificial intelligence, and machine learning are ushering in a new age of automation, as machines match or outperform human performance. Machine intelligence can enable businesses to improve performance by reducing errors, improving sensitivity, quality and speed, and in some cases achieving outcomes that go beyond current resource capabilities. Relevant applications include new product architecture design, rapid material characterization, and life-cycle management tied with a digital strategy that will enable efficient development of products from cradle to grave. In addition, there are also challenges to overcome that must be addressed through a major, sustained research effort that is based solidly on both inferential and computational principles applied to design tailoring of functionally optimized structures. Current applications of structural materials in the aerospace industry demand the highest quality control of material microstructure, especially for advanced rotational turbomachinery in aircraft engines in order to have the best tailored material property. In this paper, deep convolutional neural networks were developed to accurately predict processing-structure-property relations from materials microstructures images, surpassing current best practices and modeling efforts. The models automatically learn critical features, without the need for manual specification and/or subjective and expensive image analysis. Further, in combination with generative deep learning models, a framework is proposed to enable rapid material design space exploration and property identification and optimization. The implementation must take account of real-time decision cycles and the trade-offs between speed and accuracy