Interaction Parameters Research Articles

Phase equilibria and thermodynamic analysis of liquid–liquid immiscibility in the system SiO2–Na2O–MoO3

AbstractPhase equilibrium experiments were carried out in the SiO2–Na2O–MoO3 system at 1200ºC and 1000ºC. We found that immiscible phase region in this system is narrower than that reported previously. By combining phase relationship and thermodynamic data and assuming associate species model, interaction parameters to describe enthalpy of mixing of SiO2–Na2O–MoO3 liquid were optimized by CALPHAD methodology. The thermodynamic database can be applied to thermodynamic calculations of silicate systems containing molybdenum, such as the vitrification process of high-level radioactive waste.

Dynamics of paramagnetic permanent chains and self-assembled clusters under a rapidly rotating magnetic field.

We study experimentally and theoretically the dynamics of permanent paramagnetic chains and mixed clusters formed by permanent paramagnetic chains and paramagnetic particles under the influence of a time-varying magnetic field. First, we examine the dynamics of permanent chains at high frequencies (∼50 to 1000Hz). These permanent chains exhibit continuous rotational motion with a frequency several orders of magnitude lower than that of the magnetic field. We develop a theoretical model that accurately describes the dependence of the rotational dynamics of chains on their length, as well as the amplitude and frequency of the external magnetic field in this high frequency regime. Next, we examine how cluster dynamics are affected by the presence of permanent chains. We show that the rotation of clusters composed of a high proportion of permanent chains is slowed down but remains qualitatively well described by the theoretical model we developed for homogeneous clusters of isotropic particles. We propose that the decrease in angular velocity for mixed clusters is due to the hardening of the cluster's 2D elastic modulus caused by the increase of the steric interaction parameter stemming from the presence of chemical links between particles in the chains.

Optimization of Crystal Structures in Polylithionite Concentrate: A Molecular Dynamics Approach to Lithium Extraction Efficiency.

Molecular dynamics (MD) techniques offer significant potential for optimizing mineral extraction processes by simulating economically or physically restrictive conditions at the laboratory level. Lithium, a crucial metal in the electromobility era, exemplifies the need for ongoing re-evaluation of extraction techniques. This research aims to simulate the crystal structures of mineral species present in a polylithionite mineral concentrate [KLi2Al(Si4O10)(F,OH)2] using crystallographic data obtained from X-ray diffraction analysis. This study focuses on optimizing these structures, validating them through density comparisons, and determining the interaction parameter between the identified phases and lithium oxide (Li2O). The X-ray diffraction analysis revealed five predominant mineral phases: quartz (SiO2), calcite [Ca(CO3)], pyrite (FeS2), cassiterite (SiO2), and a compound Pb6O2(BO3)2SO4. Structural data, including lattice parameters, space groups, and atomic coordinates, were used to construct the crystal structures with Materials Studio 8.0, employing the Crystal Builder module. Optimization was performed using the Forcite module with the Smart optimization algorithm and the Universal force field. The interaction parameter (χ) indicated an affinity between lithium oxide and pyrite, as well as between calcite and quartz.

QPOs from charged particles around magnetized black holes in braneworlds

Quasiperiodic oscillations (QPOs) are a powerful tool for testing gravity theories, probing gravitational and electromagnetic field properties, and obtaining constraints on the black hole and field parameters. This work considers charged particle dynamics near uniformly magnetized black holes in braneworlds. First, we obtain the solution of the Maxwell equation for magnetic fields and calculate the radial and angular magnetic field components. We derive and analyze the effective potential of charged particles for circular orbits and investigate the energy and angular momentum for the circular orbits. We also analyze the combined effects of magnetic interaction and braneworlds on the charged particles’ innermost stable circular orbits (ISCOs). We calculate the angular momentum of charged particles in Keplerian orbits in the presence of an external magnetic field and braneworlds. Also, we investigate frequencies of the particle oscillations along vertical and angular directions. We applied our studies on particle oscillations to the QPO studies in the relativistic precession model. Finally, we obtain constraints on magnetic interaction and braneworld parameters together with the black hole mass and QPO orbits using Monte Carlo Markov Chain (MCMC) simulation in the four-dimensional parameter space for the QPOs observed in the microquasars XTE J1550-564, GRO J1655-40 & GRS 1915-105, and at the center of galaxies M82 and Milky Way.

Quantitative Macromolecular Modeling Assay of Biopolymer-Based Hydrogels

The rubber elasticity theory has been lengthily applied to several polymeric hydrogel substances and upgraded from idealistic models to consider imperfections in the polymer network. The theory relies solely on hyperelastic material models in order to provide a description of the elastic polymer network. While this is also applicable to polymer gels, such hydrogels are rather characterized by their water content and visco-elastic mechanical properties. In this work, we applied rubber elasticity constitutive models through hyperelastic parameter identification of hydrogels based on their stress–strain response to compression. We further performed swelling experiments and determined the intrinsic properties, i.e., density, of the specimens and their components. Additionally, we estimated their equilibrium swelling and employed it in the swelling-equilibrium theory in order to determine the polymer–solvent interaction parameter of each hydrogel with regard to cross-linking. Our results show that the average mesh size obtained from the rubber elasticity theory can be regarded as a concentration-dependent characteristic length of the hydrogel’s network and couples the non-linear elastic response to the specimens’ inherent visco-elasticity through hysteresis as a quantifier of energy dissipation under large deformation.

Analytic continuation in the coupling constant for resonances in ${}^9_{\Lambda}$Be

Abstract The application scope of the analytic continuation in the coupling constant (ACCC) can be extended to the exchange parameters of the effective nucleon-nucleon interaction in microscopic cluster model. Based on such exchange parameter dependent ACCC (abbreviated as EPD-ACCC), we study the ${}_{\Lambda}^9$Be system in the framework of $\alpha+\alpha+\Lambda$ microscopic cluster model. The resonant states of $\alpha+\alpha+\Lambda$ are obtained through EPD-ACCC. Meanwhile, the complex scaling method (CSM) is applied as a comparison. A good agreement between these two theoretical approaches is obtained. This work demonstrate a reliable method EPD-ACCC for estimating the multi-cluster resonances in light hypernuclei.

Flow of a biomagnetic fluid embedded by magnetic dipole over a continuously moving sheet

AbstractThis paper is concerned with the investigation of steady, two‐dimensional, and laminar boundary layer flow of a biomagnetic fluid over a continuously moving sheet in the presence of a magnetic dipole. The magnetic field resulting from the dipole is contemplated to be strong enough to saturate the biofluid. The magnetization of the fluid is regarded to be a linear function of temperature. The solution procedure involves the reduction of a nonlinear system of coupled PDEs into ODEs that comprise five parameters. The transformed ODEs along with the boundary conditions are then solved numerically by introducing an efficient numerical technique based on the finite difference algorithm. The velocity, as well as temperature profiles within the boundary layer, are illustrated at specified values of free stream velocity (), wall velocity () and ferrohydrodynamic interaction parameter (). The demonstration of the Nusselt number and friction factor are achieved for various governing parameters. Considering a specified Prandtl number () and normalized velocity difference , higher values of the friction factor are obtained for increasing and than that of . Whereas for the Nusselt number, we attain higher values for decreasing and . Moreover, an increase in the velocity ratio results in a decrease in both heat transfer rate as well as friction factor. Furthermore, as increases, the heat transfer rate decreases yet we get higher values for higher and . In the case of friction factor, it increases with increasing and gives higher values for lower and higher . We have also depicted the streamlines for the 2‐D boundary layer flow of the biomagnetic fluid for different . The graphical results manifest that the flow field is greatly impacted by the ferrohydrodynamic field, which could be of interest in medical as well as bioengineering implementations, like, magnetic drug delivery in blood cells, separating RBCs as well as controlling the flow of blood during surgical procedures.

Synthesis of Polyether Block Copolymers from 1,2-Epoxybutane and AEOn and Comparative Study of Physicochemical and Application Properties before and after the Synthesis.

In this study, the AEOnBO2 series of block polyoxybutenol ethers was synthesized by combining the AEO series of polyoxyethylene and preparing 1,2-epoxybutane (BO) block polyether using a semicontinuous method. The synthesis was performed by HPLC, MALDI-TOF-MS, FT-IR, and 1H NMR for structural analysis. The interaction parameters and surface tension of the systems before and after synthesis were studied using surface tension meter. The diffusion process of the systems before and after synthesis was studied using a KRÜSS bubble pressure tensiometer. The surfactant properties of AEOn and AEOnBO2 were evaluated by static and dynamic surface tension measurements. Each system formed a saturated adsorption layer in a water solution. The critical micelle concentration decreased dramatically after the introduction of BO groups, and the diffusion-adsorption process was consistent with the kinetic mechanism of hybrid diffusion. The microscopic self-assembled aggregate micellar behavior of all the systems was investigated using DLS, TEM, and SEM. The micellization process in all systems was spontaneous and enthalpy-driven, forming spherical aggregates, with the BO block reducing the aggregate diameter of the feedstock from 220.06 nm to about one-third of 80.02 nm. In addition, the dynamic contact angle, application, and physicochemical properties such as foaming and foam stabilization of each system were investigated. The contact angle was reduced from 70 to 50° at 120 s of stabilization, with a foam volume of 80 mL in all systems at 200 s. However, the AEOnBO2 showed accelerated foam decay at 500 s, with an increase in the contact angle from 70 to 50° at 200 s, but the AEOnBO2 showed accelerated foam decay at 500 s, with a decrease in the contact angle from 70 to 50° at 120 s stabilization. At 200 s, the foam volume of all systems was 80 mL, but AEOnBO2 showed an accelerated foam decay process, which shows that the BO group can accelerate the foam decay, and the comparative results show that the BO group can also optimize other application properties and physicochemical properties.

Effects of DM and KSEA interactions on entanglement, Fisher and Wigner-Yanase information correlations of two XYZ-Heisenberg-qubit states under a magnetic field

We employ entanglement negativity, local quantum uncertainty (LQU), and local quantum Fisher information (LQFI) to characterize thermal entanglement between two XYZ-Heisenberg-qubit states under the influence of Dzyaloshinsky-Moriya(DM) and Kaplan-Shekhtman-Entin-Wohlman-Aharony (KSEA) interactions, as well as a magnetic field and thermal equilibrium temperature. A comparative examination reveals similar behaviors among these correlation measures. For the antiferromagnetic scenario, we observe that increasing the DM interaction parameter D z enhances thermal entanglement. Conversely, in the ferromagnetic case, the behavior of thermal entanglement differs with varying D z . Additionally, employing Kraus operators, we explore the performance of these quantifiers under decoherence. Notably, LQFI exhibits greater robustness than negativity and LQU, even displaying a frozen phenomenon at some time under dephasing effects.

Charge Scaling in Classical Force Fields for Lithium Ions in Polymers.

Polymer electrolytes are of interest for applications in energy storage. Molecular simulations of ion transport in polymer electrolytes have been widely used to study the conductivity in these materials. Such simulations have generally relied on classical force fields. A peculiar feature of such force fields has been that in the particular case of lithium ions (Li+), their charge must be scaled down by approximately 20% to achieve agreement with experimental measurements of ion diffusivity. In this work, we present first-principles calculations that serve to justify the charge-scaling factor and van der Waals interaction parameters for Li+ diffusion in poly(ethylene glycol) (PEO) with bistriflimide (TFSI-) counterions. Our results indicate that a scaling factor of 0.79 provides good agreement with DFT calculations over a relatively wide range of Li+ concentrations and temperatures, consistent with past reports where that factor was adjusted by trial and error. We also show that such a scaling factor leads to diffusivities that are in quantitative agreement with experimental measurements.

Gamma attenuation and radiation shielding performance of CaCu3B2Re2O12 (B[dbnd]Mn, Fe, Co, and Ni) perovskites

In order to identify the importance of perovskites in nuclear science, studies aimed at obtaining the radiation interaction quantities of perovskites are essential. This study computed and analyzed the gamma photon interaction parameters of CaCu3B2Re2O12 (BMn, Fe, Co, and Ni) perovskites to reveal their shielding potentials and comparative advantages against traditional shielding materials. Four samples of ferrimagnetic quaternary perovskites whose chemical structures are summarized as CaCu3B2Re2O12 (BMn (CCMRO1), Fe (CCMRO2), Co (CCMRO3), and Ni (CCMRO4)) were considered for their gamma interaction quantities. The values of mass attenuation coefficient (μρ) was calculated with XCOM and they were in the range of 0.0552 cm2/g–0.4162 cm2/g for CCMRO1, 0.0553 cm2/g–0.4165 cm2/g CCMRO2, 0.0552 cm2/g–0.4148 cm2/g for CCMRO3, and 0.0555 cm2/g–0.4163 cm2/g for CCMRO4. The values of effective atomic number and electron density was within the range 21.38–43.38 and 2.84 x 1023 electrons/g −5.62 x1023 electrons/g, respectively. The trend of the mass energy absorption coefficients of the perovskites was also found to be in the same order as the mass attenuation coefficient. CCMRO3 has the highest photon energy absorptive ability among the perovskites while CCMRO2 has the least capacity. Also, the gamma dose rates in15 mm thick of CCMRO1, CCMRO2, CCMRO3, and CCMRO4 for 1.25 MeV are about 1446 kR/h, 1449 kR/h, 1453 kR/h, and 1446 kR/h, respectively. Comparatively, the values of the exposure and energy absorption buildup factors were almost the same for the perovskites at the same energy and optical depth. The investigated perovskites had higher mass attenuation coefficients that standard shielding glasses. The perovskites can be used for shielding or any other radiation absorption roles in radiation science and technology, especially for photons at low energies.

Prediction of electron-solid interaction parameters using machine learning.

Electron backscattering coefficient and electron-stopping power are essential concepts in many disciplines, from radiation to materials science, semiconductor manufacturing, and space exploration. They enable precise calculations, measurements, and simulations of electron interactions with matter, which contribute to advancing science, technology, and safety in a variety of applications. The availability of these data is fundamental to scientific research to validate hypotheses, conduct experiments, and explore new theories. A relatively novel machine learning approach has demonstrated notable success in enhancing data quality and completeness, significantly contributing to the facilitation of data discovery. Using fundamental material property data, the stacking ensemble machine learning (EML) technique was established in this study to generate electron-solid interaction parameters for any target material over a wide range of energies. The final stacking EML was built using the base and meta learners bagging regressor (BR), K-nearest neighbors (k-NN), random forest (RF), support vector regression (SVR), and eXtreme Gradient Boosting (XGB). In this study, two publicly available databases with a total of 4030 data points were used. Training datasets have 785 and 525 data points for electron backscattering coefficient and stopping power, respectively, whereas testing datasets contain 262 and 175 data points. Fivefeatures were used as input variables to train different individual algorithms and their combinations. On both the training and test datasets, the model was evaluated using different error metrics, including R-squared (R2), mean-absolute-error (MAE), root-mean-squared-error (RMSE), and mean-absolute-percentage-error (MAPE). Our model evaluation tests revealed that combining RF and XGB with a k-NN meta-learner outperformed other algorithms. The analysis of error metrics demonstrated a very close fit to all samples in each training dataset. Furthermore, predictions made by the model on unseen test data indicated accurate estimations of new backscattering and stopping power data. The developed model achieved high prediction accuracy for various target materials across the broad electron energy spectrum. The outcomes demonstrate the effectiveness of machine learning methodology and the chosen models' suitability for addressing substantial physics challenges.

Role of biquadratic exchange on thermodynamic quantities in anisotropic Heisenberg model

The magnetic and thermodynamic properties of the spin-1 anisotropic Heisenberg system are studied within Oguchi approximation. The system contains both the bilinear and biquadratic exchange interactions between the nearest neighboring spins located on a centered honeycomb lattice. For the positive biquadratic exchange interaction parameters, the phase transition in the Heisenberg case is of both second and first order where there is a discontinuity in the thermodynamic properties at this transition temperature. For some negative biquadratic exchange interaction parameters, in both the Heisenberg and Ising cases, the ferromagnetic state changes in favor of the antiferromagnetic state. The frustrated antiferromagnetic structure created by the biquadratic exchange parameter with negative sign was shown significantly influence the magnetization, quadrupolar moment, internal energy, heat capacity, entropy and free energy of the system, where the system has an oscillating chaotic phase regime. A double peak behavior was observed in the specific heat, with one at the critical temperature and another at a low temperature.

Influence of excipients on solubility of oxcarbazepine: Modeling and prediction based on thermodynamic models

In this work, the solubility of oxcarbazepine in polymers (PEG 6000, PEG 20,000, PVP K25, and PVP K30) and their aqueous solutions was investigated by experimental measurement and thermodynamic modeling. Firstly, the solubility of oxcarbazepine in water and polymers was modeled and the corresponding binary interaction parameters (oxcarbazepine + water and oxcarbazepine + polymer) were determined based on the experimental phase equilibrium data. Furthermore, the solubility of oxcarbazepine in the polymer aqueous solution (the mass ratios of polymers in water were 2 %, 4 %, and 6 %) was predicted by the solid-liquid equilibrium (SLE) coupled with the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT). It was observed that the predicted results agreed well with the experimental data, and the average relative deviation (ARD) was <7 %. In this study, the solubility of oxcarbazepine in polymer aqueous solution was successfully predicted through the SLE coupled with the PC-SAFT, which was expected to provide theoretical guidance for the selection of pharmaceutical excipients and the rational design of preparations.

Temperature Dependence of Magnetization and Exchange Interaction in Amorphous Fe–Ni–Si–B Alloys

The temperature dependence of the magnetization of rapidly quenched amorphous Fe–Ni–Si–B alloys was studied by the magnetometry method. The Curie temperatures were determined, and the exchange interaction parameters was calculated: the constants of spin-wave stiffness and exchange stiffness, the root mean-square range of the exchange interaction. The nearest neighboring distance between transition metal atoms was estimated based on the magnetic characteristics.

Assessment stability and G x E interactions of baby corn hybrids for yield and yield contributing traits

The present study consisted of total 45 hybrids along with 18 parents and 2 checks. These entries were evaluated in randomized block design with three replications over three locations. Observations were recorded on ten characters to study per se performance, estimates genotype × environment interaction and stability parameters. The crosses × environment interactions were significant for all the characters indicating existence of non-linear response of crosses to the changing environments. The analysis of variance for individual environment indicated significant differences among genotypes for all the traits indicating the heritable nature of inheritance of these traits. The crosses EIQ-103 × EI-2156, EIQ-180 × EI-2518-4, and EIQ-103 × EI-670-2 were found to perform well across different environmental conditions for yield and yield-contributing traits. Specifically, the crosses EIQ-103 × EI-2156 and EI-1104-1 × EI-2156 demonstrated stability across various environments, while the crosses EI-2173 × EI-2156 and EIQ-235 × EI-2518-4 were particularly suitable for unfavourable conditions. Keywords: Baby Corn, Stability Analysis, Eberhart &amp; Russell, G x E Interactions

Prediction Model for Coformer Screening of Energetic Eutectics Based on Flory‐Huggins Interaction Parameter

AbstractBased on intermolecular interactions, Flory‐Huggins interaction parameter χAB&gt;0 was presented as a prediction model to screen the coformer of energetic eutectics. To evaluate the predictive accuracy of this model, 80 energetic eutectics were collected from literatures. The molecular structures were optimized by computationally cheap molecular mechanics and high precision dispersion‐corrected density functional, respectively. Then the weighted Monte Carlo method was used to calculate the mixing energy ΔEmix of the binary system and thus derive the dimensionless χAB. The results show that the prediction accuracy is up to 85% based on M06‐2X‐D3/6‐311+G (d, p) optimization geometry and RESP charge, much greater than 45% of molecular mechanics method. Furthermore, size/shape mismatch between eutectic molecules was considered by shape index and molecular volume to enrich the prediction model. Based on this prediction model, a new energetic eutectic MTNP‐TNT was discovered, whose χAB value is 3.376 obtained by M06‐2X‐D3/6‐311+G (d, p) method. Experimentally, the classical “V” phase diagram drawn from the differential scanning calorimetry (DSC) data also suggests the MTNP‐TNT eutectic with eutectic temperature of 54.41°C at the molar ratio of 51.50: 48.50. Theoretical and experimental results successfully validate the χAB&gt;0 prediction model for screening the coformers of energetic eutectics. This work opens a way for the crystal engineering of energetic eutectic solid forms with attractive physicochemical properties using a computational approach.

Thermodynamic modelling of systems involved in natural gas dehydration with triethylene glycol using a group contribution association model

Natural gas (NG) dehydration through absorption into Triethylene Glycol (TEG) is one of the most important applications in the NG industry. The optimal design of the TEG dehydration process requires a deep understanding of the thermodynamic behavior of mixtures containing TEG, water, hydrocarbons, and other compounds present in natural gas. In this work, the recently developed Universal Mixing Rule – Cubic Plus Association (UMR-CPA) group contribution equation of state (EoS) is extended to these systems. UMR-CPA combines the PR-CPA EoS with the UNIFAC group contribution activity coefficient model through the Universal Mixing Rules. Parameters for pure water, TEG and NG components were determined by accurately fitting vapor pressure, density and heat capacity data. For non-associating compounds, the model leads to overall deviations of 1.2 % in vapor pressures and 6.1 % in isobaric heat capacities. Water properties are also quite accurately described, with overall deviations of approximately 0.4 %, 1.2 % and 5.7 % in vapor pressures, liquid densities and isobaric heat capacities, respectively. The model was then applied to mixtures of water and TEG with gases and hydrocarbons by correlating the proper group interaction parameters. Very satisfactory results were obtained for both vapor-liquid and liquid-liquid phase equilibria in these systems, where also an adequate reproduction of the minimum of hydrocarbon solubility in water was noted. Finally, the UMR-CPA EoS was further validated through the prediction of the phase behavior of ternary systems including TEG and/or water and NG compounds. Very good predictions were achieved for the low TEG and water content in the vapor phase of the TEG-H2O-CH4 ternary system, with absolute deviations of around 0.05 and 23.26 ppm, respectively. Overall, the model yields accurate predictions, suggesting its suitability for designing the TEG dehydration process.

Calculations of mean ionic activity coefficients of copper and manganese salts in aqueous solutions

Accurately predicting the activity coefficients of copper and manganese salts in aqueous solutions is crucial for treating industrial wastewater, and it is of practical interest to calculate the activity coefficients of heavy metals in aqueous solutions using the Equation of State because of its high flexibility and wide range of applicability. This work conducts a modeling study on the mean ionic activity coefficients of copper and manganese salts in aqueous solutions. The thermodynamic framework used in this work is an electrolyte version of the Cubic Plus Association Equation of State (e-CPA). The model's ion-water binary interaction parameters are obtained by regressing the osmotic coefficients and mean ionic activity coefficients in aqueous solutions. The modeling results indicate that the electrolyte Equation of State can satisfactorily correlate the water activity, osmotic coefficients, and mean ionic activity coefficients of copper and manganese salts in aqueous solutions over a wide range of salt concentrations. Among all the systems at 298.15 K, the biggest average relative deviation between calculated and experimental values is within 6.7 % and 2.3 % for the mean ionic activity coefficients and water activity, respectively. Furthermore, this work discusses the impact of ion pairs on the phase equilibrium of aqueous systems from a microscopic mechanism perspective and analyzes and discusses the model's adaptability. The model used in this work can accurately predict the activity coefficients of a variety of copper and manganese salts in aqueous solutions over wide concentration ranges and provides an improved interface for improving the calculation accuracy of the model under high concentration or other complex conditions.

Integrating thermodynamic and kinetic approaches for the design of effective and sustainable PET chemical upcycling systems

Understanding and optimizing the individual contributions of recycling process components are critical in the development of effective and sustainable upcycling systems. Herein, each process component, i.e., alcohol, co-solvent, Lewis acid, and reaction conditions, is newly and holistically assessed for the alcohol-based conversion of postconsumer polyethylene terephthalate (PET) to terephthalic acid (TPA) and its precursors by integrating thermodynamic and kinetic considerations. First, an analysis based on the Flory-Huggins interaction parameter (χ1,2) establishes the importance of co-solvents in the depolymerization process due to reduction of thermodynamic potential. Second, a kinetic analysis of the catalyst component proves the vitality of the solubility of the Lewis acid source for efficient PET deconstruction. In addition, further validation experiments determine methanol as the most effective option in tandem alcoholysis given its reduced steric hindrance and relatively higher nucleophilicity, whereas process optimization tests suggest the existence of an optimum methanol molar ratio (XMetOH) of 0.16 and operation at 50 °C to realize TPA yields that exceed 90 % within 15 min across various pure and mixed PET feedstocks. Selection and implementation of greener solvents in the process is also found to reduce co-solvent based emissions by 96.3 % whilst retaining comparable monomer production efficiency. Overall, the implementation of thermodynamic considerations and kinetics-based understanding of roles played by each component is found to boost the overall depolymerization process, and the integration of these thermodynamic and kinetic approaches provides a unified avenue for optimizing and developing sustainable recycling processes for post-consumer plastic waste.