Category: 118-55-8

On June 2, 2020, Zhang, Kai; Zhong, Shifa; Zhang, Huichun published an article.Application of 118-55-8 The title of the article was Predicting Aqueous Adsorption of Organic Compounds onto Biochars, Carbon Nanotubes, Granular Activated Carbons, and Resins with Machine Learning. And the article contained the following:

predictive models are useful tools for aqueous adsorption research; however, existing (e.g., multi-linear regression [MLR]) models can only predict adsorption under specific equilibrium concentrations or for certain adsorption isotherm models. few studies have discussed data processing beyond applying different modeling algorithms to improve prediction accuracy. this work used a cosine similarity approach which focused on mining available data before developing models. the approach, to mine the most relevant data concerning the prediction target to develop models, considerably improved prediction accuracy. a machine-learning modeling process based on neural networks (NN); a group-selection data-splitting strategy for grouped adsorption data for adsorbent-adsorbate pairs under different equilibrium concentrations; and poly-parameter linear free energy relationships (pp-LFER) for aqueous adsorption of 165 organic compounds on 50 biochars, 34 C nanotubes, 35 granular activated C, and 30 polymeric resins, was developed. the final NN-LFER models, successfully applied to various equilibrium concentrations regardless of adsorption isotherm model, showed less prediction deviations than published models with root mean-square errors of 0.23-0.31 vs. 0.23-0.97 log units; the predictions were also improved by adding two key descriptors (surface area and pore volume) for the adsorbents. interpreting the NN-LFER models based on Shapley values suggested not considering adsorbent equilibrium concentration and properties in existing MLR models is a possible reason for their higher prediction deviations. The experimental process involved the reaction of Phenyl Salicylate(cas: 118-55-8).Application of 118-55-8

The Article related to biochar organic compound aqueous adsorption machine learning predictive model, carbon nanotube organic compound aqueous adsorption predictive model, granular activated carbon organic compound aqueous adsorption predictive model, resin organic compound aqueous adsorption predictive model and other aspects.Application of 118-55-8

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

On May 4, 2021, Mei, Baicheng; Zhou, Yuxing; Schweizer, Kenneth S. published an article.Formula: C13H10O3 The title of the article was Experimental test of a predicted dynamics-structure-thermodynamics connection in molecularly complex glass-forming liquids. And the article contained the following:

Understanding in a unified manner the generic and chem. specific aspects of activated dynamics in diverse glass-forming liquids over 14 or more decades in time is a grand challenge in condensed matter physics, phys. chem., and materials science and engineering. Large families of conceptually distinct models have postulated a causal connection with qual. different ‘order parameters’ including various measures of structure, free volume, thermodn. properties, short or intermediate time dynamics, and mech. properties. Construction of a predictive theory that covers both the noncooperative and cooperative activated relaxation regimes remains elusive. Here, we test using solely exptl. data a recent microscopic dynamical theory prediction that although activated relaxation is a spatially coupled local-nonlocal event with barriers quantified by local pair structure, it can also be understood based on the dimensionless compressibility via an equilibrium statistical mechanics connection between thermodn. and structure. This prediction is found to be consistent with observations on diverse fragile mol. liquids under isobaric and isochoric conditions and provides a different conceptual view of the global relaxation map. As a corollary, a theor. basis is established for the structural relaxation time scale growing exponentially with inverse temperature to a high power, consistent with experiments in the deeply supercooled regime. A criterion for the irrelevance of collective elasticity effects is deduced and shown to be consistent with viscous flow in low-fragility inorganic network-forming melts. Finally, implications for relaxation in the equilibrated deep glass state are briefly considered. The experimental process involved the reaction of Phenyl Salicylate(cas: 118-55-8).Formula: C13H10O3

The Article related to dynamics structure thermodn molecularly complex glass forming liquid, glass former supercooled liquid dynamics structure thermodn, supercooled liquid dynamics structure thermodn glass transition, activated relaxation, fragile-to-strong crossover, glass transition, molecular liquids, thermodynamics–dynamics connection and other aspects.Formula: C13H10O3

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