A model for gel drying

Prediction of solvent solubility, diffusivity and permeability in glassy polymeric membranes

Achieving comprehensive improvements in the drying rate (DR) and the quality after drying of agricultural products is a major goal in the field of drying. To further shorten the drying time while improving product quality, this study introduced a Convolutional Neural Network (CNN) and MultiHead Attention (MHA) to enhance the prediction accuracy of the Long Short-Term Memory (LSTM) network regarding the properties of dried samples. These properties included DR, shrinkage rate (SR), and total color difference (ΔE). The CNN-LSTM-MHA network was proposed, developing a novel hot-air drying (HAD) scenario utilizing an intelligent temperature control system based on the real dynamics of material properties. The results of drying experiments with temperature-sensitive yuba showed that the CNN-LSTM-MHA network’s predictive accuracy was better than that of other networks, as evidenced by its coefficient of determination (R2: 0.9855–0.9999), root mean square error (RMSE: 0.0001–0.0099), and mean absolute error (MAE: 0.0001–0.0120). Comparative analysis with fixed-temperature drying indicated that CNN-LSTM-MHA-controlled drying significantly reduced drying time and enhanced the SR, color, rehydration ratio (RR), texture, protein content, fat content, and microstructure of yuba. Overall, the findings highlight the potential of CNN-LSTM-MHA-based intelligent drying as a viable strategy for yuba stick processing, providing insights for other food drying applications.

Diffusion coefficients of organics in high density polyethylene (HDPE)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTSelf-Diffusion of Dimethyl Sulfoxide and Dimethylformamide in Solutions and Gels of Cellulose Acetates by Pulsed Field Gradient NMRE. Ilyina and V. DaraganCite this: Macromolecules 1994, 27, 14, 3759–3763Publication Date (Print):July 1, 1994Publication History Published online1 May 2002Published inissue 1 July 1994https://pubs.acs.org/doi/10.1021/ma00092a013https://doi.org/10.1021/ma00092a013research-articleACS PublicationsRequest reuse permissionsArticle Views384Altmetric-Citations13LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts

In order to improve the drying rate and to reduce the energy consumption of vegetables and fruits, carrots chips are treated with ultrasonic with different frequency, time, and different temperature. The hot air drying rate of treated carrots chips is determined and, meanwhile, several quality parameters, such as the shrinkage and rehydration rate of samples with pretreatment are determined to compare with those of untreated samples. The results indicate that the drying rate of carrots chips can be improved by ultrasonic pretreatment, and 70 kHz for pretreatment frequency, 45 min for pretreatment time and 25°C for pretreatment temperature is the optimum treated parameters.

A model was developed to study the drying rate of biopolymer films. The diffusivity of water in this biopolymer film is an exponential function of the water concentration. This creates a situation where simply increasing gas velocity can decrease the actual drying rate.The model revealed that the main factor limiting the drying of the biopolymer film was a significant and rapid decrease in the diffusivity of water through the film as the film dried. To avoid this a pulsing scheme was proposed where the velocity of the drying gas would be varied during the experiment; this variation allowed for a compromise between a high overall drying rate and maintaining a high diffusivity within the film. It was found that the optimum combination of gas velocities was 0.8 and 0.6 m/s with a duration of 10 min at the high and low gas velocities.

A positron annihilation spectroscopy study of Fe-free α-Zr: Thermal equilibrium and irradiation effects

Diffusion calculations with two atomic models in h.c.p Zr-Nb diluted alloys

This article presents a model for the permeation of solvent mixtures through an elastomer in the particular case of pervaporation. An analytical expression for each solvent permeation rate is derived, in the limited case of a membrane that undergoes small swelling, without making any assumptions on the solvent diffusion coefficients and their dependence on solvent concentrations. Applying this analytical expression to different situations, we fitted most of the curves previously published on pervaporation experiments. In particular, we correlated the synergy developed by a mixture of two solvents in the permeation process with the sign of their Flory–Huggins interaction parameter χAB. This explains why, in most cases (χAB > 0), a molecule permeating easily through a membrane is mixed with a molecule permeating much less easily; the latter can see its permeation flux increase by a factor 10 or 100 because the swelling of the polymer induced by the more permeable molecule “opens the meshes of the network” allowing the less permeable molecule to pass through more easily. Within our analysis, the efficiency of the pervaporation process, expressed through the separation factor, is derived very simply as a function of the interaction coefficients and the viscosities of solvents and exhibits an exponential dependence on the volume fraction of either component as seen in most experiments. © 2002 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 41: 183–193, 2003

The swelling of model polymer networks with different cross-link densities is studied via molecular dynamics simulation. During the simulation, the solvent particles, consisting of one interaction center or six interaction centers, respectively, are transferred between two coupled simulation boxes. The gel box includes both network and solvent particles, whereas the solvent box contains solvent only. The particle transfer is controlled by the solvent chemical potential difference in the two boxes, which is calculated via the Widom test particle method for the one-site solvent and via Rosenbluth sampling for the chainlike solvent. The equilibrium swelling ratio of the network as well as the solvent diffusion coefficient under subcritical and supercritical conditions are computed as functions of the network cross-link density for a wide range of temperatures and pressures. In addition, the simulated swelling behavior is compared to a Flory-Huggins-type theory, which yields qualitative agreement for the systems studied here.

We consider the problems of improving the accuracy in non-destructive testing of the solvent diffusion coefficient in thin samples made from capillary-porous materials by optimizing the solvent doses administered during the active part of the experiment.

Ensuring non-destructive testing of products in industry is an urgent task. Most of the modern methods for determining the diffusion coefficient in porous materials have been developed for bodies of a given configuration and size. This leads to the need for finished products destruction to make experimental samples from them. The purpose of this study is the development of a dynamic method that allows operatively determine the diffusion coefficient in finished products from porous materials without destroying them. The method is designed to investigate the solvents diffusion coefficient in building constructions from materials having a porous structure: brick, concrete and aerated concrete, gypsum, cement, gypsum or silicate solutions, gas silicate blocks, heat insulators, etc. A mathematical model of the method is constructed. The influence of the design and measuring device operating parameters on the method accuracy is studied. The application results of the developed method for structural porous products are presented.

Interaction of oxygen functionalized multi-walled carbon nanotube nanofluids with copper

Diffusion of solvent and coagulant in the fiber during coagulation process was simulated, taking the change of fiber radius and diffusion coefficient into account.Changes of fiber radius and diffusion coefficient were found to follow the next equations by experimental results for model filaments with large diameter.For the diffusion coefficient. D(x)at distance x=x, where Ds, and Dg are diffusion coefficients in solution phase and in gel phase respectively, Lc the distance between the capillary and the point where coagulation is completed, being given by the following equation. where R is average fiber radius, v the take-up velocity of the filament.For the fiber radius R(x) at x=x where R0 and Rb are fiber radius at x=0 and x=Lb respectively, Lb the distance between the capillary and the point where diffusion equilibrium is reached and is given by the following equation. where D is average diffusion coefficient.Assuming that changes of fiber radius and diffusion coefficient are predicted by the above equations, concentration change in the fiber during coagulation process was simulated using an electronic computer and the results were found to agree well with the experimental results.

The purpose of this project is to advance the improvement of LLNL thermochemical computational models that form the underlying basis or input for laboratory hydrodynamic simulations. Our general work approach utilizes, by design, tight experimental-theoretical research interactions that allow us to not empirically, but rather more scientifically improve LLNL computational results. The ultimate goal here is to confidently predict through computer models, the performance and safety parameters of currently maintained, modified, and newly designed stockpile systems. To attain our goal we make relevant experimental measurements on candidate detonation products constrained under static high-pressure and temperature conditions. The reduced information from these measurements is then used to construct analytical forms that describe the potential surface (repulsive energy as a function of interatomic separation distance) of single and mixed fluid or detonation product species. These potential surface shapes are also constructed using input from well-trusted shock wave physics and assorted thermodynamic data available in the open literature. Our potential surfaces permit one to determine the equations of state (P,V,T), the equilibrium chemistry, phase, and chemical interactions of detonation products under a very wide range of extreme pressure temperature conditions. Using our foundation of experimentally refined potential surfaces we are in a position to calculate, with confidence, the energetic output and chemical speciation occurring from a specific combustion and/or detonation reaction. The thermochemical model we developed and use for calculating the equilibrium chemistry, kinetics, and energy from ultrafast processes is named 'Cheetah'. Computational results from our Cheetah code are coupled to laboratory ALE3D hydrodynamic simulation codes where the complete response behavior of an existing or proposed system is ultimately predicted. The Cheetah thermochemical code is also used by well over 500 U.S. government DoD and DOE community users who calculate the chemical properties of detonated high explosives, propellants, and pyrotechnics. To satisfy the growing needs of LLNL and the general user community we continue to improve the robustness of our Cheetah code. The P-T range of current speed of sound experiments will soon be extended by a factor of four and our recently developed technological advancements permit us to, for the first time, study any chemical specie or fluid mixture. New experiments will focus on determining the miscibility or coexistence curves of detonation product mixtures. Our newly constructed ultrafast laser diagnostics will permit us to determine what chemical species exist under conditions approaching Chapman-Jouguet (CJ) detonation states. Furthermore we will measure the time evolution of candidate species and use our chemical kinetics data to develop new and validate existing rate laws employed in future versions of our Cheetah thermochemical code.