Esters-buliding-blocks

Tan, Tian published the artcilePrediction of infinite-dilution activity coefficients with neural collaborative filtering, Synthetic Route of 140-11-4, the main research area is prediction infinite dilution activity coefficient neural collaborative filtering.

Accurate prediction of infinite dilution activity coefficient (γ∞) for phase equilibrium and process design is crucial. In this work, an exptl. γ∞ dataset containing 295 solutes and 407 solvents (21,048 points) is obtained through data integrating, cleaning, and filtering. The dataset is arranged as a sparse matrix with solutes and solvents as columns and rows, resp. Neural collaborative filtering (NCF), a modern matrix completion technique based on deep learning, is proposed to fully fill in the γ∞ matrix. Ten-fold cross-validation is performed on the collected dataset to test the effectiveness of the proposed NCF, proving that NCF outperforms the state-of-the-art phys. model and previous machine learning model. The completed γ∞ matrix makes solvent screening and extension of UNIFAC parameters possible. Taking two typical hard-to-sep. systems (benzene/cyclohexane and Me cyclopentane/n-hexane mixtures) as examples, the NCF-developed database provides high-throughput screening for separation systems in terms of solvent selectivity and capacity.

AIChE Journal published new progress about Algorithm. 140-11-4 belongs to class esters-buliding-blocks, name is Benzyl acetate, and the molecular formula is C9H10O2, Synthetic Route of 140-11-4.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Galanopoulos, Christos published the artcileAn integrated methodology for the economic and environmental assessment of a biorefinery supply chain, Recommanded Product: Ethyl 4-oxopentanoate, the main research area is ethano ethyl levulinate electricity environmental assessment optimization simulation.

A supply chain network MILP model, developed by means of AIMMS software, and a process plant simulation model, developed by means of Aspen Plus, are combined for the optimization of a biorefinery network. Optimization of the supply chain network is initially addressed using literature process and economic data. The results are used as input in the Aspen Plus model where the tech. and economic performance of the biorefineries is calculated rigorously. The two computational tools are iteratively executed until convergence on number, locations and size of the biorefineries and on process yield to products and total costs is achieved. The final results are used to perform the Economic Value and Environmental Impact (EVEI) anal. of the overall biorefinery network. The methodol. is applied to a case study concerning the deployment of cereal straw in Germany to produce ethanol, Et levulinate and electricity. Optimization results reveal that the wheat straw supply network with four biorefineries is economically feasible and determines an environmental margin in terms of equivalent emissions savings of about 4 Mt of CO2 per yr.

Chemical Engineering Research and Design published new progress about Algorithm. 539-88-8 belongs to class esters-buliding-blocks, name is Ethyl 4-oxopentanoate, and the molecular formula is C7H12O3, Recommanded Product: Ethyl 4-oxopentanoate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Hosseini, Sayed Mostafa published the artcileMolecular thermodynamic modeling of surface tensions of some fatty acid esters and biodiesels, Name: Methyl octanoate, the main research area is mol thermodn surface tension fatty acid ester biodiesel.

This work addresses the mol. thermodn. and artificial neural network (ANN) modeling of surface tensions of several fatty acid esters and biodiesels. Two biodiesels were considered as pure fluid and the other as a binary mixture The mol. thermodn. model is based on the statistical mech. expression according to Fowler-Kirkwood-Buff approximation Regarding this, contributions to surface tension from the hard-chain repulsions, Lennard-Jones dispersion forces, and dipolar interactions were considered and assumed to be additive in the model development. The mol. thermodn. model used three mol. parameters reflecting the hard-core diameter, dispersive energy and segment number as well as the liquid densities for which the values were predicted from perturbed Yukawa-chain equation of state. Further, the model used dipole moment as an adjustable parameter for the accurate calculation of surface tensions. The model could predict 149 surface tension data points for 9 FAEs and 3 biodiesels in 268.6-393 K range with the average absolute relative deviation (AARD) of 1.82%. The degree of accuracy of proposed model has also been compared with some empirical equations. Concerning ANN modeling, a network comprising two hidden layers and 9 neurons for each layer has been trained, according to the constructive approach. The result of the training was quite good, the AARD of the pure fluid dataset of 137 points was found to be 0.44%.

Journal of Molecular Liquids published new progress about Algorithm. 111-11-5 belongs to class esters-buliding-blocks, name is Methyl octanoate, and the molecular formula is C9H18O2, Name: Methyl octanoate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Perez-Sanz, Fernando published the artcilegcProfileMakeR: an R package for automatic classification of constitutive and non-constitutive metabolites, Recommanded Product: Benzyl acetate, the main research area is gcProfileMakeR package automatic classification constitutive metabolites; R package; automatic classification; circadian clock; constitutive metabolome; floral organ identity; gcProfileMakeR; machine learning; non-constitutive metabolome.

Metabolomes comprise constitutive and non-constitutive metabolites produced due to physiol., genetic or environmental effects. However, finding constitutive metabolites and non-constitutive metabolites in large datasets is tech. challenging. We developed gcProfileMakeR, an R package using standard Excel output files from an Agilent Chemstation GC-MS for automatic data anal. using CAS numbers gcProfileMakeR has two filters for data preprocessing removing contaminants and low-quality peaks. The first function NormalizeWithinFiles, samples assigning retention times to CAS. The second function NormalizeBetweenFiles, reaches a consensus between files where compounds in close retention times are grouped together. The third function getGroups, establishes what is considered as Constitutive Profile, Non-constitutive by Frequency i.e., not present in all samples and Non-constitutive by Quality. Can be plotted with the plotGroup function. We used it to analyze floral scent emissions in four snapdragon genotypes. These included a wild type, Deficiens nicotianoides and compacta affecting floral identity and RNAi:AmLHY targeting a circadian clock gene. We identified differences in scent constitutive and non-constitutive profiles as well as in timing of emission. gcProfileMakeR is a very useful tool to define constitutive and non-constitutive scent profiles. It also allows to analyze genotypes and circadian datasets to identify differing metabolites.

Metabolites published new progress about Algorithm. 140-11-4 belongs to class esters-buliding-blocks, name is Benzyl acetate, and the molecular formula is C9H10O2, Recommanded Product: Benzyl acetate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Christov, Latchezar published the artcileExistence and stability of azeotropes in the terminal model of multicomponent copolymerization, Application of Dodecyl 2-methylacrylate, the main research area is azeotrope terminal model multicomponent copolymerization algorithm.

A simple numerical algorithm for calculating the azeotropic composition of multicomponent copolymers (if such a composition exists) is presented. The method is based on regular Markov chains in the frame of the terminal model of irreversible chain propagation in chain-growth copolymerization It requires as few calculations as just solving two systems of linear equations. The stability of the azeotropic composition in a batch reactor is discussed. A numerical procedure that can distinguish between a stable and an unstable azeotropic composition is proposed. 2021 Society of Industrial Chem.

Polymer International published new progress about Algorithm. 142-90-5 belongs to class esters-buliding-blocks, name is Dodecyl 2-methylacrylate, and the molecular formula is C16H30O2, Application of Dodecyl 2-methylacrylate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Rajkumar, Sundararajan published the artcileIntegration of artificial neural network, multi-objective genetic algorithm and phenomenological combustion modelling for effective operation of biodiesel blends in an automotive engine, Product Details of C23H46O2, the main research area is biodiesel blend artificial neural network phenomenol combustion.

Biodiesel usage is practically restricted as a blended supplement with fossil diesel. In the current study, the authors have attempted to arrive at the optimal biodiesel blend concentrations for an automotive engine. Here, the artificial neural network and genetic algorithm are coupled with phenomenol. combustion modeling for the efficient operation of biodiesel blends. The engine experiments are conducted with diesel and diesel-biodiesel blends namely jatropha, and karanja consisting of 120 data points each. This set of data are used for the ANN development and validation. A multi-layer perceptron network is trained by the exptl. data for predicting the engine parameters. The Nash Sutcliffe coefficient of efficiency values for the ANN predicted parameters are close to 1, indicating a close prediction. The ANN model predicted the engine output parameters with low values of mean square error, mean square relative error, mean absolute percentage error and standard error of prediction. Optimum values of biodiesel blend fraction, engine speed, brake mean effective pressure, injection pressure and timing are obtained using a multi-objective genetic algorithm. The optimized blend concentration is found to be ∼20% and ∼40% for satisfying the different objectives concerning the overall engine characteristics. Finally, the outputs for the optimized parameters are compared to the validated multi-zone model predictions within the maximum error of ∼3% and 7.9% for performance and emission parameters resp.

Energy (Oxford, United Kingdom) published new progress about Algorithm. 929-77-1 belongs to class esters-buliding-blocks, name is Methyl docosanoate, and the molecular formula is C23H46O2, Product Details of C23H46O2.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Verma, Akalesh Kumar published the artcileRepurposing potential of FDA-approved and investigational drugs for COVID-19 targeting SARS-CoV-2 spike and main protease and validation by machine learning algorithm, Recommanded Product: 2-((5-Nitrothiazol-2-yl)carbamoyl)phenyl acetate, the main research area is drug repurposing COVID 19 coronavirus spike glycoprotein protease inhibitor; 2019nCov; antiviral drugs; cordycepin; coronavirus; drug repurposing.

The present study aimed to assess the repurposing potential of existing antiviral drug candidates (FDA-approved and investigational) against SARS-CoV-2 target proteins that facilitates viral entry and replication into the host body. To evaluate mol. affinities between antiviral drug candidates and SARS-CoV-2 associated target proteins such as spike protein (S) and main protease (Mpro), a mol. interaction simulation was performed by docking software (MVD) and subsequently the applicability score was calculated by machine learning algorithm. Furthermore, the STITCH algorithm was used to predict the pharmacol. network involving multiple pathways of active drug candidate(s). Pharmacophore features of active drug(s) mol. was also determined to predict structure-activity relationship (SAR). The mol. interaction anal. showed that cordycepin has strong binding affinities with S protein (-180) and Mpro proteins (-205) which were relatively highest among other drug candidates used. Interestingly, compounds with low IC50 showed high binding energy. Furthermore, machine learning algorithm also revealed high applicability scores (0.42-0.47) of cordycepin. It is worth mentioning that the pharmacol. network depicted the involvement of cordycepin in different pathways associated with bacterial and viral diseases including tuberculosis, hepatitis B, influenza A, viral myocarditis, and herpes simplex infection. The embedded pharmacophore features with cordycepin also suggested strong SAR. Cordycepin’s anti-SARS-CoV-2 activity indicated 65% (E-gene) and 42% (N-gene) viral replication inhibition after 48 h of treatment. Since, cordycepin has both preclin. and clin. evidences on antiviral activity, in addition the present findings further validate and suggest repurposing potential of cordycepin against COVID-19.

Chemical Biology & Drug Design published new progress about Algorithm. 55981-09-4 belongs to class esters-buliding-blocks, name is 2-((5-Nitrothiazol-2-yl)carbamoyl)phenyl acetate, and the molecular formula is C12H9N3O5S, Recommanded Product: 2-((5-Nitrothiazol-2-yl)carbamoyl)phenyl acetate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Bradford, Shanshan Y. C. published the artcileTemperature artifacts in protein structures bias ligand-binding predictions, Recommanded Product: Benzyl acetate, the main research area is temperature artifacts ligand binding prediction protein structure.

X-ray crystallog. is the gold standard to resolve conformational ensembles that are significant for protein function, ligand discovery, and computational methods development. However, relevant conformational states may be missed at common cryogenic (cryo) data-collection temperatures but can be populated at room temperature To assess the impact of temperature on making structural and computational discoveries, we systematically investigated protein conformational changes in response to temperature and ligand binding in a structural and computational workhorse, the T4 lysozyme L99A cavity. Despite decades of work on this protein, shifting to RT reveals new global and local structural changes. These include uncovering an apo helix conformation that is hidden at cryo but relevant for ligand binding, and altered side chain and ligand conformations. To evaluate the impact of temperature-induced protein and ligand changes on the utility of structural information in computation, we evaluated how temperature can mislead computational methods that employ cryo structures for validation. We find that when comparing simulated structures just to exptl. cryo structures, hidden successes and failures often go unnoticed. When using structural information in ligand binding predictions, both coarse docking and rigorous binding free energy calculations are influenced by temperature effects. The trend that cryo artifacts limit the utility of structures for computation holds across five distinct protein classes. Our results suggest caution when consulting cryogenic structural data alone, as temperature artifacts can conceal errors and prevent successful computational predictions, which can mislead the development and application of computational methods in discovering bioactive mols.

Chemical Science published new progress about Algorithm. 140-11-4 belongs to class esters-buliding-blocks, name is Benzyl acetate, and the molecular formula is C9H10O2, Recommanded Product: Benzyl acetate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Kim, Mi Hye published the artcilePeroxiredoxin 2 deficiency reduces white adipogenesis due to the excessive ROS generation, Safety of 2′,7′-Dichloro-3-oxo-3H-spiro[isobenzofuran-1,9′-xanthene]-3′,6′-diyl diacetate, the main research area is peroxiredoxin deficiency white adipogenesis ROS generation; adipose tissue/adipocytes; apoptosis; cell death; oxidative stress.

The Prx2 is present in the cytoplasm and cell membranes and demonstrates ROS scavenging activity. We focused on Prx2 involvement in regulating adipogenesis and lipid accumulation and demonstrated that Prx2 expression was upregulated during adipocyte differentiation. In addition, the silencing of Prx2 (shPrx2) inhibited adipogenesis by modulating adipogenic gene expression, and cell death was enhanced via increased ROS production in shPrx2-3T3-L1 cells. These results demonstrate that shPrx2 triggers adipocyte cell death and weakens adipocyte function via ROS production Taken together, our data suggest the participation of Prx2 in adipocyte function and differentiation. Our results also imply that the downregulation of Prx2 activity could help prevent obesity. Overall, findings support the development of ROS-based therapeutic solutions for the treatment of obesity and obesity-related metabolic disorders. Reactive oxygen species (ROS) act as signaling mols. to regulate various cell functions. Numerous studies have demonstrated ROS to be essential for the differentiation of adipocytes. Peroxiredoxins (Prxs) are a ubiquitous family of antioxidant enzymes in mammalian cells.

Cell Biology International published new progress about Adipocyte. 2044-85-1 belongs to class esters-buliding-blocks, name is 2′,7′-Dichloro-3-oxo-3H-spiro[isobenzofuran-1,9′-xanthene]-3′,6′-diyl diacetate, and the molecular formula is C24H14Cl2O7, Safety of 2′,7′-Dichloro-3-oxo-3H-spiro[isobenzofuran-1,9′-xanthene]-3′,6′-diyl diacetate.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics

Boscan, Freddy published the artcileIncorporation of Very Insoluble Monomers in Waterborne Coatings, Application In Synthesis of 142-90-5, the main research area is waterborne coating insoluble monomer.

The benefits of polymerizing very insoluble monomers in aqueous media, avoiding the use of energy-intensive procedures, by implementing two novel synthesis techniques based on the emulsifier combination in emulsion polymerization and on miniemulsification by phase inversion temperature are investigated. The performance of standalone polymers consisting of monomers, namely lauryl methacrylate, isobornyl acrylate, and 1H,1H,2H,2H-perfluorodecyl acrylate, and of formulated binders with these monomers incorporated either through blending or in situ polymerization, is evaluated with special emphasis on their water-barrier properties (e.g., uptake, whitening, immersion, and vapor resistance) and on their chem. resistance. The performance of the standalone polymers is found to be similar to that of polymers prepared by high-shear miniemulsion polymerization, while the performance of the formulated binders is generally superior to a com. coating formulation based on a binder recommended for water resistance.

Macromolecular Materials and Engineering published new progress about Adhesives. 142-90-5 belongs to class esters-buliding-blocks, name is Dodecyl 2-methylacrylate, and the molecular formula is C16H30O2, Application In Synthesis of 142-90-5.

Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics