scholarly journals Identification of Strategic Molecules for Future Circular Supply Chains Using Large Reaction Networks

2019 ◽  
Author(s):  
Jana Weber ◽  
Pietro Lio’ ◽  
Alexei Lapkin
Keyword(s):  
Supply Chains ◽  
Chemical Reactions ◽  
Search Algorithm ◽  
Reaction Pathways ◽  
Reaction Networks ◽  
Waste Streams ◽  
Renewable Feedstocks ◽  
Generic Problem ◽  
Synthesis Routes ◽  
Isolation Forest

Networks of chemical reactions represent relationships between molecules within chemical supply chains and promise to enhance planning of multi-step synthesis routes from bio-renewable feedstocks. This study aims to identify <i>strategic molecules</i>in chemical reaction networks that may potentially play a significant role within the future circular economy. We mine a commercially available database in order to assemble a network of chemical reactions. We describe molecules within the network by a portfolio of graph theoretical features, and identify strategic molecules with an isolation forest search algorithm. In this work we have identified a list of potential strategic molecules and indicated possibilities for reaction planning using these. This is exemplified by a potential supply chain of functional molecules from bio-waste streams that could be used as feedstocks without being converted to syngas. This work extends the methodology of analysis of reaction networks to the generic problem of development of new reaction pathways based on novel feedstocks.

scholarly journals Identification of Strategic Molecules for Future Circular Supply Chains Using Large Reaction Networks

2019 ◽  
Author(s):  
Jana Weber ◽  
Pietro Lio’ ◽  
Alexei Lapkin
Keyword(s):  
Supply Chains ◽  
Chemical Reactions ◽  
Search Algorithm ◽  
Reaction Pathways ◽  
Reaction Networks ◽  
Waste Streams ◽  
Renewable Feedstocks ◽  
Generic Problem ◽  
Synthesis Routes ◽  
Isolation Forest

Networks of chemical reactions represent relationships between molecules within chemical supply chains and promise to enhance planning of multi-step synthesis routes from bio-renewable feedstocks. This study aims to identify <i>strategic molecules</i>in chemical reaction networks that may potentially play a significant role within the future circular economy. We mine a commercially available database in order to assemble a network of chemical reactions. We describe molecules within the network by a portfolio of graph theoretical features, and identify strategic molecules with an isolation forest search algorithm. In this work we have identified a list of potential strategic molecules and indicated possibilities for reaction planning using these. This is exemplified by a potential supply chain of functional molecules from bio-waste streams that could be used as feedstocks without being converted to syngas. This work extends the methodology of analysis of reaction networks to the generic problem of development of new reaction pathways based on novel feedstocks.

scholarly journals Identification of strategic molecules for future circular supply chains using large reaction networks

2019 ◽  
Vol 4 (11) ◽  
pp. 1969-1981 ◽  
Author(s):  
Jana Marie Weber ◽  
Pietro Lió ◽  
Alexei A. Lapkin
Keyword(s):  
Supply Chains ◽  
Chemical Reactions ◽  
Reaction Networks ◽  
Renewable Feedstocks ◽  
Synthesis Routes

Networks of chemical reactions represent relationships between molecules within chemical supply chains and promise to enhance planning of multi-step synthesis routes from bio-renewable feedstocks.

scholarly journals More and Faster: Simultaneously Improving Reaction Coverage and Computational Cost in Automated Reaction Prediction Tasks

2020 ◽  
Author(s):  
Qiyuan Zhao ◽  
Brett Savoie
Keyword(s):  
Transition State ◽  
Domain Knowledge ◽  
Low Cost ◽  
Computational Cost ◽  
Chemical Degradation ◽  
Reaction Pathways ◽  
Reaction Networks ◽  
Complex Reaction ◽  
Success Rates ◽  
Reaction Prediction

<div> <div> <div> <p>Automated reaction prediction has the potential to elucidate complex reaction networks for applications ranging from combustion to materials degradation. Although substantial progress has been made in predicting specific reaction pathways and resolving mechanisms, the computational cost and inconsistent reaction coverage of automated prediction are still obstacles to exploring deep reaction networks without using heuristics. Here we show that cost can be reduced and reaction coverage can be increased simultaneously by relatively straight- forward modifications of the reaction enumeration, geometry initialization, and transition state convergence algorithms that are common to many emerging prediction methodologies. These changes are implemented in the context of Yet Another Reaction Program (YARP), our reaction prediction package, for which we report a head-to-head comparison with prevailing methods for two benchmark reaction prediction tasks. In all cases, we observe near perfect recapitulation of established reaction pathways and products by YARP, without the use of heuristics or other domain knowledge to guide reaction selection. In addition, YARP also discovers many new kinetically relevant pathways and products reported here for the first time. This is achieved while simultaneously reducing the cost of reaction characterization nearly 100-fold and increasing transition state success rates and intended rates over 2-fold and 10-fold, respectively, compared with recent benchmarks. This combination of ultra-low cost and high reaction-coverage creates opportunities to explore the reactivity of larger sys- tems and more complex reaction networks for applications like chemical degradation, where approaches based on domain heuristics fail. </p> </div> </div> </div>

scholarly journals Fermentation of Organic Residues to Beneficial Chemicals: A Review of Medium-Chain Fatty Acid Production

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1571
Author(s):  
Panagiota Stamatopoulou ◽  
Juliet Malkowski ◽  
Leandro Conrado ◽  
Kennedy Brown ◽  
Matthew Scarborough
Keyword(s):  
Organic Waste ◽  
Chain Elongation ◽  
Organic Substrates ◽  
Industrial Chemicals ◽  
Waste Streams ◽  
Fatty Acid Production ◽  
Medium Chain ◽  
Renewable Feedstocks ◽  
History Of ◽  
Complex Organic

Medium-chain fatty acids (MCFAs) have a variety of uses in the production of industrial chemicals, food, and personal care products. These compounds are often produced through palm refining, but recent work has demonstrated that MCFAs can also be produced through the fermentation of complex organic substrates, including organic waste streams. While “chain elongation” offers a renewable platform for producing MCFAs, there are several limitations that need to be addressed before full-scale implementation becomes widespread. Here, we review the history of work on MCFA production by both pure and mixed cultures of fermenting organisms, and the unique metabolic features that lead to MCFA production. We also offer approaches to address the remaining challenges and increase MCFA production from renewable feedstocks.

scholarly journals Rxn Rover: Automation of Chemical Reactions with User-Friendly, Modular Software

2022 ◽  
Author(s):  
Zachery Crandall ◽  
Kevin Basemann ◽  
Long Qi ◽  
Theresa L Windus
Keyword(s):  
Research And Development ◽  
Chemical Reactions ◽  
Waste Generation ◽  
Enabling Technology ◽  
Modular Software ◽  
Renewable Feedstocks ◽  
User Friendly ◽  
Technology Transformation

The automation of chemical reactions in research and development can be an enabling technology to reduce cost and waste generation in light of technology transformation towards renewable feedstocks and energy...

scholarly journals Automated exploration of DNA-based structure self-assembly networks

2021 ◽  
Vol 8 (10) ◽  
Author(s):  
L. Cazenille ◽  
A. Baccouche ◽  
N. Aubert-Kato
Keyword(s):  
Dna Sequences ◽  
Self Assembly ◽  
Search Space ◽  
Dna Origami ◽  
Reaction Pathways ◽  
Reaction Networks ◽  
Dna Structures ◽  
Search Spaces ◽  
Dna Strands ◽  
Domain Level

Finding DNA sequences capable of folding into specific nanostructures is a hard problem, as it involves very large search spaces and complex nonlinear dynamics. Typical methods to solve it aim to reduce the search space by minimizing unwanted interactions through restrictions on the design (e.g. staples in DNA origami or voxel-based designs in DNA Bricks). Here, we present a novel methodology that aims to reduce this search space by identifying the relevant properties of a given assembly system to the emergence of various families of structures (e.g. simple structures, polymers, branched structures). For a given set of DNA strands, our approach automatically finds chemical reaction networks (CRNs) that generate sets of structures exhibiting ranges of specific user-specified properties, such as length and type of structures or their frequency of occurrence. For each set, we enumerate the possible DNA structures that can be generated through domain-level interactions, identify the most prevalent structures, find the best-performing sequence sets to the emergence of target structures, and assess CRNs' robustness to the removal of reaction pathways. Our results suggest a connection between the characteristics of DNA strands and the distribution of generated structure families.

scholarly journals Structural Chemistry of Akdalaite, Al10O14(OH)2, the Isostructural Aluminum Analogue of Ferrihydrite

Crystals ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 246 ◽  
Author(s):  
John B. Parise ◽  
Bingying Xia ◽  
Jack W. Simonson ◽  
William R. Woerner ◽  
Anna M. Plonka ◽  
...  
Keyword(s):  
Room Temperature ◽  
Structural Chemistry ◽  
Reaction Pathways ◽  
X Ray Diffraction ◽  
Complete Structure ◽  
X Ray ◽  
Chemical Company ◽  
Intermediate Phases ◽  
Needle Morphology ◽  
Synthesis Routes

As part of an effort to characterize clusters and intermediate phases likely to be encountered along solution reaction pathways that produce iron and aluminum oxide-hydroxides from Fe and Al precursors, the complete structure of Al10O14(OH)2 (akdalaite) was determined from a combination of single-crystal X-ray diffraction (SC-XRD) data collected at 100 K to define the Al and O positions, and solid-state nuclear magnetic resonance (NMR) and neutron powder diffraction (NPD) data collected at room temperature (~300 K) to precisely determine the nature of hydrogen in the structure. Two different synthesis routes produced different crystal morphologies. Using an aluminum oxyhydroxide floc made from mixing AlCl3 and 0.48 M NaOH, the product had uniform needle morphology, while using nanocrystalline boehmite (Vista Chemical Company Catapal D alumina) as the starting material produced hexagonal plates. Akdalaite crystallizes in the space group P63mc with lattice parameters of a = 5.6244(3) Å and c = 8.8417(3) Å (SC-XRD) and a = 5.57610(2) Å and c = 8.77247(6) Å (NPD). The crystal structure features Al13O40 Keggin clusters. The structural chemistry of akdalaite is nonideal but broadly conforms to that of ferrihydrite, the nanomineral with which it is isostructural.

scholarly journals Sustainable polyesters via direct functionalization of lignocellulosic sugars

2021 ◽  
Author(s):  
Lorenz Manker ◽  
Graham Dick ◽  
Adrien Demongeot ◽  
Maxime Hédou ◽  
Christèle Rayroud ◽  
...  
Keyword(s):  
Material Properties ◽  
Glyoxylic Acid ◽  
Waste Streams ◽  
Direct Transformation ◽  
Glass Transition Temperatures ◽  
Biologically Relevant ◽  
Renewable Feedstocks ◽  
Melt Polycondensation ◽  
Direct Functionalization ◽  
Lignocellulosic Sugars

The development of sustainable plastics from abundant renewable feedstocks has been limited by the complexity and efficiency of their production as well as their lack of competitive material properties. Here, we demonstrate the direct transformation of the hemicellulosic fraction of non-edible biomass into a diester plastic precursor at 83% yield (95% from commercial xylose) during integrated plant fractionation with glyoxylic acid. Melt polycondensation of the resulting xylose-based diester with a range of aliphatic diols led to high-molecular weight amorphous polyesters with combined high glass transition temperatures, tough mechanical properties, and strong gas barriers, which could be processed by injection-molding, thermoforming, and 3D-printing. These polyesters could then be chemically recycled from mixed plastic waste streams or digested under biologically relevant conditions. The transformation’s simplicity led to projected costs that were competitive with fossil alternatives and significantly reduced associated greenhouse gas emissions, especially if glyoxylic acid was sourced from CO2.

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