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This study explores the estimation of solubility-induced elemental fractionation of noble gases in hydrocarbon-based oils through existing empirical and theoretical models, complemented by a novel molecular simulation-based approach. Quantifying such fractionation is essential for a deeper understanding of fluid processes and migration in subsurface geological resources, an area currently lacking in experimental data. To address this, the research introduces a predictive model that employs the Peng-Robinson equation of state and a fugacity-coefficient-based method to assess noble gas elemental fractionation in hydrocarbons, including normal alkanes, cycloalkanes, and aromatics. However, this model struggles with precise quantitative predictions, prompting the introduction of adjusted cross-interaction parameters to enhance its performance. Furthermore, molecular simulations, in conjunction with the refined equation of state, are shown to offer a novel method for calculating noble gas fractionation coefficients across different hydrocarbon solvents. A key finding is the identification of a universal master curve, demonstrating that noble gas solubility fractionation at low pressure in simple hydrocarbon solvents can be quantitatively determined by temperature and density alone, without the need for detailed compositional information. Consequently, a new correlation is proposed for deriving elemental fractionation coefficients based solely on oil temperature and density, offering significant improvements over existing empirical methods for a wide range of temperatures. Although limitations are noted when applying this approach to oils rich in complex heavy components like resins and asphaltenes, it allows to address inconsistencies observed in traditionally used experimental correlations at high temperatures. [ABSTRACT FROM AUTHOR]

Abstract We present MoCHI, a tool to fit interpretable models using deep mutational scanning data. MoCHI infers free energy changes, as well as interaction terms (energetic couplings) for specified biophysical models, including from multimodal phenotypic data. When a user-specified model is unavailable, global nonlinearities (epistasis) can be estimated from the data. MoCHI also leverages ensemble, background-averaged epistasis to learn sparse models that can incorporate higher-order epistatic terms. MoCHI is freely available as a Python package ( https://github.com/lehner-lab/MoCHI ) relying on the PyTorch machine learning framework and allows biophysical measurements at scale, including the construction of allosteric maps of proteins.

Thermophysical properties of industrially complex fluids whose composition is always ill-defined are in practice predicted by using thermodynamic models. To ensure the prediction accurately and reliably, a three-step procedure to obtain the properties of these fluids must be validated. The focus of this study is laid on a short review of tools which can be served for each of the three steps. It should be noted that the tools presented in this work are centered on the ones applicable for highly associating and/or polar fluids. It is also recommended in this work an approach for characterizing a pseudocomponent representative of a complex mixture, e.g. petroleum fluids, biomass fluids, considering the available analytical data. This fully described pseudocomponent can be easily used within any thermodynamic models. [ABSTRACT FROM AUTHOR]

This article explores technical challenges and potential methodologies for understanding electrochemical Reactive CO 2 Capture (RCC) mechanisms. RCC offers potential energy cost advantages by directly converting captured CO 2 into fuels and chemicals, unlike traditional carbon capture and utilization (CCU) processes that require sequential capture, concentration, and compression. However, direct conversion of captured CO 2 introduces complexity due to additional equilibrium buffer reactions, making it challenging to identify active species for reduction in electrochemical studies. This article discusses methods to integrate transport, thermodynamics, and kinetics concepts to identify active carbon sources in RCC. Vapor‐Liquid Equilibrium (VLE) and transport models are validated against experimental results obtained in a gastight rotating cylinder electrode reactor and are shown as useful tools for studying RCC in heterogeneous electrocatalysts across different capture agents, solvents, and temperatures. This article establishes an experimental framework for advancing research in electrochemical RCC. [ABSTRACT FROM AUTHOR]

We have developed a general model to predict CO2 equilibrium solubility in aqueous tertiary amine solutions by relating the equilibrium constant (K1) to all relevant parameters in a logical function form. Testing our model, we measured CO2 equilibrium solubility data for N‐methylmorpholine (NMM) and N‐ethylmorpholine (NEM) across various conditions. Comparison with six existing models reveals our general model's superior predictive performance not only for NMM and NEM but also for an additional 10 tertiary amine solutions from literature, indicating its universality. Comprehensively considering the CO2 equilibrium solubility, amine dissociation constant (pKa) and the CO2 absorption heat, it is found that NMM and NEM may be promising desorption promoters enabling to reduce the energy cost. In short, it is expected the general model can be applied to more other tertiary amine systems. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs. A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep subsurface to shallow aquifers. The stray gas can dissolve in groundwater leading to chemical and biological reactions, which could negatively affect groundwater quality and contribute to atmospheric emissions. The knowledge of light hydrocarbon solubility in the aqueous environment is essential for the numerical modelling of flow and transport in the subsurface. Herein, we compiled a database containing 2129 experimental data of methane, ethane, and propane solubility in pure water and various electrolyte solutions over wide ranges of operating temperature and pressure. Two machine learning algorithms, namely regression tree (RT) and boosted regression tree (BRT) tuned with a Bayesian optimization algorithm (BO) were employed to determine the solubility of gases. The predictions were compared with the experimental data as well as four well-established thermodynamic models. Our analysis shows that the BRT-BO is sufficiently accurate, and the predicted values agree well with those obtained from the thermodynamic models. The coefficient of determination (R2) between experimental and predicted values is 0.99 and the mean squared error (MSE) is 9.97 × 10−8. The leverage statistical approach further confirmed the validity of the model developed. [ABSTRACT FROM AUTHOR]

A new thermodynamic model for silicate melt in the Na2O–CaO–K2O–FeO–MgO–Al2O3–SiO2–TiO2–Fe2O3–Cr2O3 model system is presented, building on the tholeiitic through to granitic melt model of Holland et al. (2018) [Journal of Petrology, 59, 881–900] but extending for the first time into anhydrous alkaline systems. The new melt model is accompanied by new thermodynamic models for nepheline, kalsilite, leucite, melilite and ilmenite. Collectively these models enable pseudosection modelling of alkaline-silicate magmatic systems, providing a new tool for investigating this geologically- and economically-important compositional space. The models are calibrated with respect to experimental data on phase relations among minerals and melt, and the fit is benchmarked here via detailed comparison with seven experimental datasets, which encompass a range of pressure (0–22 kbar), temperature (680–1350°C), oxygen fugacity (log f O2 ΔFMQ-3 to +1), total alkali (3–16 wt %) and silica (37–70 wt %) conditions. The calculated pseudosections successfully reproduce experimental crystallisation sequences and phase compositions, indicating that the thermodynamic models are well calibrated across this spectrum of conditions. Redox buffered experimental conditions are simulated using oxygen buffered pseudosections. Contouring of oxygen buffered pseudosections with X Fe3+ (mol. Fe3+/Fetotal), or pseudosections of varying X Fe3+ with ΔFMQ, reveals (i) often complex and non-intuitive relationships between these two representations of oxidation state, and (ii) substantial variation in ferric iron over narrow temperature intervals in some oxygen buffered sets of experiments. An implication is that simulating oxygen buffering is vital when benchmarking thermodynamic models using experimental results. Furthermore, because natural igneous systems likely feature a near-constant X Fe3+, it is important to assess experimental results in this framework when making inferences about natural systems, recognising that oxygen fugacity is a consequence not a control of phase equilibria in nature. Overall, our new models provide a novel tool to explore the role of variables, such as pressure, fractional crystallisation and crustal assimilation in the petrogenesis of alkaline-silicate magmatic systems and their associated mineralisation. [ABSTRACT FROM AUTHOR]

In the next 10–20 years, several observatories will aim to detect the signatures of oxygenic photosynthesis on exoplanets, though targets must be carefully selected. Most known potentially habitable exo-planets orbit cool M-dwarf stars, which have limited emission in the photosynthetically active region of the spectrum (PAR, 400 < λ < 700 nm) used by Earth's oxygenic photoautotrophs. Still, recent experiments have shown that model cyanobacteria, algae, and non-vascular plants grow comfortably under simulated M-dwarf light, though vascular plants struggle. Here, we hypothesize that this is partly due to the different ways they harvest light, reflecting some general rule that determines how photosynthetic antenna structures may evolve under different stars. We construct a simple thermodynamic model of an oxygenic antenna-reaction centre supercomplex and determine the optimum structure, size and absorption spectrum under light from several star types. For the hotter G (e.g. the Sun) and K-stars, a small modular antenna is optimal and qualitatively resembles the PSII-LHCII supercomplex of higher plants. For the cooler M-dwarfs, a very large antenna with a steep 'energy funnel' is required, resembling the cyanobacterial phycobilisome. For the coolest M-dwarfs an upper limit is reached, where increasing antenna size further is subject to steep diminishing returns in photosynthetic output. We conclude that G- and K-stars could support a range of niches for oxygenic photo-autotrophs, including high-light adapted canopy vegetation that may generate detectable bio-signatures. M-dwarfs may only be able to support low light-adapted organisms that have to invest considerable resources in maintaining a large antenna. This may negatively impact global coverage and therefore detectability. [ABSTRACT FROM AUTHOR]

The solubility of 1,3,5-Tribromobenzene (m-TBB) in five kinds of binary solvent mixtures (i.e., N,N-dimethylformamide (DMF) + water, N,N-dimethylacetamide (DMA) + water, 1,4-dioxane + water, DMF + ethanol, and DMA + ethanol) was measured by a gravimetric method. The determination was carried out at temperatures ranging from 288.15 K to 323.15 K under ambient pressure. The solubility data were positively correlated with the molar fraction of good solvent and temperature. The order of solubility is 1,4-dioxane + water > DMA + ethanol > DMF + ethanol > DMA + water > DMF + water. The solubility of m-TBB was negatively correlated with solvent polarity. Four thermodynamic models (including the Jouyban–Acree–Apelblat, the Sun model, the NRTL model, and the Wilson model) were selected to correlate the solubility data of m-TBB. The solubility data are of great significance for solvent selection and yield judgment. [ABSTRACT FROM AUTHOR]

The industrial production of polypropylene–polyethylene composites (C-PP-PE) involves the generation of waste that is not usable, resulting in a significant environmental impact globally. In this research, we identified different concentrations of aluminum (8–410 ppm), chlorine (13–205 ppm), and iron (4–100 ppm) residues originating from traces of the Ziegler–Natta catalyst and the triethylaluminum (TEAL) co-catalyst. These residues accelerate the generation of plastic waste and affect the thermo-kinetic performance of C-PP-PE, as well as the formation of volatile organic compounds that reduce the commercial viability of C-PP-PE. Several families of organic compounds were quantified by gas chromatography with mass spectrometry, and it is evident that these concentrations varied directly with the ppm of Al, Cl, and Fe present in C-PP-PE. This research used kinetic models of Coats–Redfern, Horowitz–Metzger, Flynn–Wall–Ozawa, and Kissinger–Akahira–Sunose. The activation energy values (Ea) were inversely correlated with Al, Cl, and Fe concentrations. In samples PP0 and W3, with low Al, Cl, and Fe concentrations, the values (Ea) were 286 and 224 kJ mol−1, respectively, using the Horowitz method. Samples W1 and W5, with a high ppm of these elements, showed Ea values of 80.83 and 102.99 kJ mol−1, respectively. This knowledge of the thermodynamic behavior and the elucidation of possible chemical reactions in the industrial production of C-PP-PE allowed us to search for a suitable remediation technique to give a new commercial life to C-PP-PE waste, thus supporting the management of plastic waste and improving the process—recycling to promote sustainability and industrial efficiency. One option was using the antioxidant additive Irgafos P-168 (IG-P168), which stabilized some of these C-PP-PE residues very well until thermal properties similar to those of pure C-PP-PE were obtained. [ABSTRACT FROM AUTHOR]

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This study explores the efficient removal of the synthetic anionic dye-reactive red Me4BL (RRMe4BL) from an aqueous medium which is a significant contributor to environmental pollution. The present study investigates the synthesis of zinc oxide, nickel oxide, cobalt oxide and copper oxide nano adsorbents (ZnO (II), NiO (II), CoO (II), CuO (II)) through the co-precipitation method and their effectiveness in eliminating the reactive red dye Me4BL(RRMe4BL). Maximum adsorption capacities were achieved at pH 2 for ZnO (96.1 mg/g), NiO (86.9 mg/g), CoO (93.4 mg/g) and at pH 6 for CuO (76.3 mg/g) under a 0.05 g/50 mL nano-adsorbent dose, 50 mg/L dye initial concentration and 25°C T and 90 min of contact time. The fitness of the pseudo-2nd-order model explained the kinetics, while Langmuir and Temkin adsorption isotherm highlighted the efficiency of the dye adsorption. Thermodynamic studies revealed the spontaneous and exothermic nature of adsorption. The influence of electrolytes, surfactants and desorption was also analysed. Characterisation of the nanoparticles was done through SEM, XRD and FTIR which revealed the morphology and functional groups of nano-adsorbents. The adsorption method used for eliminating this anionic red dye shows several benefits, including affordability, simplicity of use and the presence of intelligent adsorbents for environment-friendly removal of industrial dyes from wastewater. [ABSTRACT FROM AUTHOR]

Absorption heat pumps have emerged as a potential tool to address the energy crisis because of their ability to utilize low-grade heat. The performance of an absorption heat pump largely depends on the efficiency of the working pair to operate at the source temperature. The commercialized working pairs H2O/LiBr and NH3/H2O linger with operational and economic issues. Several binary/ternary combinations were tested among water, ammonia, salt, alcohols, hydrocarbons, and ionic liquids (ILs) in quest of the potential working pairs. The last decade has witnessed a stupendous surge in IL-based working pairs because of their several advantageous properties over the traditional solvents. The present review encompasses the research progress on various working pairs, in particular, their properties, modeling and correlation results, and coefficient of performance (COP) values.

To develop effective pharmaceutical formulations using supercritical carbon dioxide (scCO2) techniques, it is necessary to obtain the solubility of the medicinal ingredients in scCO2. In the current study, the solubility of Amantadine in scCO2 was evaluated under 28 different operating conditions involving seven pressures and four temperatures. To theoretically study this process, some popular empirical models and two well‐known thermodynamic models (PR‐WS and PC‐SAFT) were examined. The results suggest that the PR‐WS and PC‐SAFT models are the most accurate in establishing a correlation of the solubility of Amantadine in scCO2. [ABSTRACT FROM AUTHOR]

Rate‐temperature scaling relationships have fascinated biologists for nearly two centuries and are increasingly important in our era of global climate change. These relationships are hypothesized to originate from the temperature‐dependent kinetics of rate‐limiting biochemical reactions of metabolism. Several prominent theories have formalized this hypothesis using the Arrhenius model, which characterizes a monotonic temperature dependence using an activation energy E. However, the ubiquitous unimodal nature of biological temperature responses presents important theoretical, methodological, and conceptual challenges that restrict the promise for insight, prediction, and progress. Here we review the development of key hypotheses and methods for the temperature‐scaling of biological rates. Using simulations, we examine the constraints of monotonic models, illustrating their sensitivity to data nuances such as temperature range and noise, and their tendency to yield variable and underestimated E, with critical consequences for climate change predictions. We also evaluate the behaviour of two prominent unimodal models when applied to incomplete and noisy datasets. We conclude with recommendations for resolving these challenges in future research, and advocate for a shift to unimodal models that better characterize the full range of biological temperature responses. [ABSTRACT FROM AUTHOR]

Simple Summary: The physical properties (hair diameter, hair length, haircoat depth, and haircoat density) and spectral properties (solar absorptivity, solar reflectivity, and solar transmissivity) of hair and haircoats play critical roles in heat and moisture exchange between an animal and its surrounding environment. These properties also play an important role in protecting the skin against penetration of ultraviolet radiation. Black haircoats absorb solar radiation, but the absorption occurs at the haircoat–air interface (away from the skin surface) where convective heat loss is high. Holstein cows with dominant black color haircoats are more suitable in latitudes with high solar input than those with a white color haircoat. A white haircoat is more transparent and allows solar energy to penetrate deeply into the haircoat, and thus, heat flows toward the skin surface (heat gain). The physical properties of hair and haircoats are not numerically the same at different locations (dorsal, ventral, lateral, neck, head, etc.) of the body of a cow. The density (no. of hairs/cm2) of a haircoat is constant to a certain depth from the skin surface, and then decreases exponentially toward the haircoat–air interface. Cattle with a dominant black haircoat spend more time using shade than those with a white or red haircoat. The physical properties (hair diameter, hair length, haircoat depth and haircoat density) and spectral properties (absorptivity, reflectivity, transmissivity) of the hair and haircoat of cattle are inputs to heat and moisture exchange between the skin surface and the surrounding environment, and thus play a critical role in body temperature regulation. Physical and spectral properties of haircoats also play an important role in protecting the skin against penetration of ultraviolet radiation. The focus of this review is to identify accurate and consistent measurement procedures of these properties. Additionally, the paper shows the utilization of the properties on heat exchange models and their implications on voluntary thermoregulation of cattle. To highlight the effects and benefits of haircoat color vis-à-vis solar radiation and its implication on ecological habitation, a brief explanation is provided using polar bears (white haircoat in a cold environment) and black goats in a hot desert environment. [ABSTRACT FROM AUTHOR]

In this work, CO2 equilibrium solubility of 1M N,N‐diethylethanolamine (DEEA):2M 1,6‐hexamethyl diamine (HMDA), 1.5M DEEA:1.5M HMDA and 2M DEEA:1M HMDA was studied with a temperature range of 298–333 K and CO2 partial pressure range of 8–100 kPa. Seven thermodynamic models including Empirical model, Kent and Eisenberg (KE) model, Hu–Chakma model, Austgen model, Helei Liu model, Liu et al. model, and Li–Shen model were developed by correlating reaction equilibrium constants with observed equilibrium solubility of CO2 in mixed amine solvents. The evaluation of those models was conducted in terms of the average absolute relative deviation (AARD). The results indicated that Liu et al. model considering T, [Amine], Ptotal and [CO2(aq)] can better represent this complex system with an AARD of 8.06%. Meanwhile, comprehensive comparison and analysis were also performed to identify the contribution of parameters to develop models, which could provide a guideline for the development of accurate thermodynamic models for representation of thermodynamic behaviors. [ABSTRACT FROM AUTHOR]

Binding constants (K) are foundational to supramolecular chemistry and quantified by modelling spectroscopic (NMR, UV-vis) titration data according to chemical equilibria. Spurred by growth in data science, the tools and methods for determining K values have accelerated in recent years. To share these advances, we provided a Workshop on Quantifying Binding Constants at ISMSC 2023 in Iceland and herein share the objectives, processes, and recommendations. We framed this short course in terms of learning to drive, from the basics 'under the hood', to 'behind the wheel', and navigating 'the open road'. These steps are crucial in the 'drive to K-town', where participants appreciate the importance of building, analysing, and comparing models. K-town is where they assess the hazards of incomplete models, inaccurate K values, and incorrect uncertainty assessment. We conclude with the Supramolecular Chemist's Pledge as a starting point for considering quality control in determining K values. [ABSTRACT FROM AUTHOR]

[Display omitted] • Thermodynamic simulations were used to predict the presence of bismuth and lead in a more precise form. • Pure water as an stripping extractant is not only efficient, but also cleaner and renewable. • Deep separation of bismuth and lead (β Bi/Pb = 3.84 × 106) was achieved by stripping with water. • Fe and Pb (<2 mg/L) in the organic phase can be reduced to the requirements of high purity bismuth-based materials. A novel lead and bismuth deep-separation extraction-stripping system is proposed for the leaching solution of molybdenite-bismuthinite mixed ore, which creates perfect conditions for the preparation of high-purity bismuth-based materials. Based on the activity and ionic strength theories, the forms of bismuth and lead present in the solution were predicted according to the thermodynamic models of different systems. The results showed that N235 + 2-octyl alcohol + kerosene formed a synergistic extraction system, which realized the synergistic extraction of bismuth, iron and lead with solvent extraction ratios of 98.74 %, 9.34 % and 46.24 %, respectively. In addition, the FTIR spectra of bismuth and lead before and after extraction were recorded to better understand the extraction and vaporization mechanisms. When stripping with water, the stripping ratios of iron and lead were 99.87 % and 99.74 %, respectively, while the loss ratio of bismuth was only 0.01 %. In conclusion, this study will be a key link in the comprehensive recycling process of bismuth resources. [ABSTRACT FROM AUTHOR]

Recovery of propionic acid from aqueous solution is economically and environmentally important. In this study, the liquid-liquid equilibrium data of water + propionic acid + cyclic alcohols (cyclopentanol and cyclohexanol) ternary system was obtained at 303.2, 313.2, and 323.2 K temperatures. These ternary systems exhibit type-1 behavior of liquid-liquid equilibrium (LLE). The Hand and Bachman equations confirm the validity of the measured data. For correlation of liquid-liquid equilibrium data, the NRTL and UNIQUAC thermodynamic models have been used and the inter-molecular interactions coefficients have been determined. RMSD values for NRTL and UNIQUAC models in cyclopentanol containing systems were 0.0107 and 0.0057, respectively, for cyclohexanol 0.0108 and 0.0076 respectively, which showed the accuracy of these models in correlation liquid-liquid equilibrium data. The values of the selectivity factor for both solvents larger than the unit are obtained, which shows that these solvents can be used to extract propionic acid from aqueous solution.

The aim of this paper is to simulate a modular bio-refinery, which utilizes the thermochemical conversion process, to transform the Nigerian sawdust wood (Nesogordonia papaverifera) as feedstock to produce bio-oil, syngas, and bio-char. In this work, the thermochemical conversion process used is fast pyrolysis. For this work, the focus is on achieving an improved bio-oil, in both quality and quantity. The simulation software used is ASPEN Plus V11, using the fluid package Peng-Robinson with Boston-Mathias (PR-BM). The conventional components (N2, O2, H2O, H2, S, CO, CO2, and solid carbon) and non-conventional components (sawdust wood and ash) were adequately specified, and the reaction feeds were pyrolyzed at 300 °C at 5 bar, which generates the highest pyrolysis oil yield in comparison with other varied temperatures from 300 to 500 °C. In the process, the drying and decomposition were carried out using FORTRAN statements through calculator blocks. The result shows that the bulk of the bio-product is the bio-oil, with its component mixture being methanol, glyoxal, and glycol-01 taking up to about 70% yield. Sensitivity analysis shows that the yield of the bio-oil greatly reduces with a significant increase in temperature. Therefore, to ensure the optimal yield of the bio-oil for the Nigerian sawdust (Nesogordonia papaverifera) model used, the operating condition of the feed should be below 400 °C. [ABSTRACT FROM AUTHOR]

Aerosol acidity, defined as pH, is a critical property that influences the formation, evolution, and health and climate effects of atmospheric aerosol particles. Direct measurement of ambient aerosol pH, however, remains challenging for atmospheric scientists. Here, based on the method of colorimetric analysis on aerosol-loaded pH-indicator papers, we develop a new device that can achieve in situ and real-time measurement of the pH of ambient aerosol droplets at a fixed relative humidity of 90%. The design of this device provides a more convenient and efficient method than the pH paper methods used in previous studies by allowing automated sample switching and data recording. The size range of ambient aerosols that are collected on pH papers is determined to be ∼0.4-2.5 μm. In addition, a standardized calibration procedure is established using pH buffer standards. An intensive ambient measurement was performed with the device to examine its operational stability as well as the reliability of the measured results. The measured aerosol pH reveals good agreement with those calculated by two commonly used thermodynamic models, i.e., ISORROPIA and E-AIM. These comparisons further demonstrate that the thermodynamic models are capable of predicting aerosol pH with a reasonable range of uncertainty.

Strategic blending of supplementary cementitious materials (SCMs) into ordinary portland cement (OPC) helps reduce energy use and greenhouse gas emissions from concrete production. Expanding thermodynamic databases to include new reaction products from blended cements improves computational approaches used to understand the impact of blending SCMs with cement. Determination of thermodynamic parameters of cement reaction products based on temperature-dependent solubility is widely used in cement research; however, assumptions, limitations, and potential errors due to intercorrelation of the thermodynamic parameters in these calculation methods are rarely discussed. Here, methods for obtaining thermodynamic parameters are critically reviewed, including discussion of experimental validation. The discussion herein provides useful guidance to improve and validate the process of determining thermodynamic parameters of new reaction products from SCM-OPC reactions.

In this paper, the effects of the initial filling rate and heat flux density on the natural convection inside the liquid hydrogen storage tank and the variation laws of temperature and pressure are studied. The study found that the optimal initial filling rate of the 250 m³ liquid hydrogen storage tank was 86%. When the initial filling rate is in the range of 35% to 95%, the change of the heat flux density has a greater impact on the self-pressurization phenomenon than the change of the filling rate. When the initial filling rate is lower than 35%, the pressure in the tank rises sharply, and the change of the initial filling rate has a great influence on the self-pressurization phenomenon. The high initial filling rate and high heat flux density make the pressure rise of the liquid hydrogen storage tank faster during the pressure recovery period. When the liquid hydrogen begins to evaporate in large quantities, the low filling rate and high heat flux make the tank pressure increase faster. By comparing the three thermodynamic models with the simulation results, it is found that the pressure deviation of the 250 m³ liquid hydrogen storage tank with a filling rate of 86% is within 20% calculated by the three-zone model, which is the closest to the simulation results. The deviation of the surface evaporation model at high heat flux density and high filling rate reached 76% and 88.3%, respectively, which was the most affected calculation model by the change of heat flux density and initial filling rate. [ABSTRACT FROM AUTHOR]

The thermodiffusion behavior of binary Lennard‐Jones mixtures in the liquid state is investigated by combining the individual strengths of non‐equilibrium molecular dynamics (NEMD) and equilibrium molecular dynamics (EMD) simulations. On the one hand, boundary‐driven NEMD simulations are useful to quickly predict Soret coefficients because they are easy to set up and straightforward to analyze. However, careful interpolation is required because the mean temperature in the measurement region does not exactly reach the target temperature. On the other hand, EMD simulations attain the target temperature precisely and yield a multitude of properties that clarify the microscopic origins of Soret coefficient trends. An analysis of the Soret coefficient suggests a straightforward dependence on the thermodynamic properties, whereas its dependence on dynamic properties is far more complex. Furthermore, a limit of applicability of a popular theoretical model, which mainly relies on thermodynamic data, was identified by virtue of an uncertainty analysis in conjunction with efficient empirical Soret coefficient predictions, which rely on model parameters instead of simulation output. Finally, the present study underscores that a combination of predictive models and EMD and NEMD simulations is a powerful approach to shed light onto the thermodiffusion behavior of liquid mixtures. [ABSTRACT FROM AUTHOR]

Modern thermodynamic models incorporate the concept of association (hydrogen bonding) and they can describe very satisfactorily many properties of water containing mixtures. They have not been successful in representing water's anomalous properties and this work provides a possible explanation. We have analyzed and interpreted recent experimental data, molecular simulation results, and two-state theory approaches and compared against the predictions from thermodynamic models. We show that the dominance of the tetrahedral structure implemented in modern thermodynamic models may be the reason for their failure for describing water systems. While this study does not prove the two-state theories for water, it indicates that a high level of tetrahedral structure of water is not in agreement with water's anomalous properties when used in thermodynamic models. [ABSTRACT FROM AUTHOR]

Eucrites exhibit a range of igneous and metamorphic textures and geochemistries that can be used to study the evolution of early planetary differentiation and crust formation in the solar system. We integrated petrologic/textural observations, in-situ geochemical analyses, and thermodynamic modeling to explore the petrogenesis of Elephant Moraine (EET) 90020, an unbrecciated meteorite. We identified microdomains that record relatively high metamorphic temperatures and concluded that diffusion processes likely modified EET 90020 during and/or after peak thermal conditions. There is little evidence that partial melting caused the distribution of minor and trace elements within or among the microdomains. Trace element linear transect measurements within the microdomains imply that phosphate minerals strongly controlled trace element distributions throughout the sample. The discrepancy between the observed metamorphic textures, major element chemistry, and the trace element distributions is a consequence of differing chemical mobility. Multiple processes are influencing geochemistry within a single sample which has implications for the development of petrogenetic models that seek to reconcile the differences observed between eucrite geochemical groups. [ABSTRACT FROM AUTHOR]

Serpentinization of olivine-rich ultramafic rocks is recognized to have been widespread across the solar system throughout its history, with substantial implications for the chemical and physical properties of planetary lithospheres, atmospheric compositions, and astrobiology. One especially significant product of serpentinization is molecular hydrogen (H 2), whose generation is closely linked to the oxidation of Fe as serpentinization proceeds. While numerous experimental simulations of serpentinization have been conducted over the years, these studies have been performed almost exclusively using reactant minerals that contain relatively high Mg and low Fe contents representative of terrestrial mantle rocks. In contrast, very few studies have been conducted with the more Fe-enriched mineral compositions that may predominate on other solar system bodies. In this study, an experiment was conducted to investigate mineral alteration and H 2 generation during serpentinization of Fe-rich olivine (hortonolite; Fo ∼62) at 230 °C and 35 MPa. After 3500 h of reaction, ∼55 % of the hortonolite reacted to secondary minerals composed of serpentine (chrysotile) and magnetite. Chrysotile contained proportionally less Fe than the original hortonolite, reflecting the partitioning of some Fe into magnetite; however, it contained substantially more Fe than serpentine precipitated from alteration of Mg-rich, Fe-poor terrestrial mantle olivine (Fo ∼90) under the same reaction conditions. Reaction of hortonolite also produced more than four times as much magnetite as Mg-rich olivine. Generation of H 2 occurred steadily throughout the experiment, with more than five times as much H 2 generated per mole of hortonolite reacted than observed for Fe-poor olivine at the same conditions. The results suggest that serpentinization of Fe-rich ultramafic rocks on Mars and other planetary bodies may have a substantially greater capacity to generate H 2 and to precipitate magnetite than their Fe-poor terrestrial counterparts, which would enhance their potential to support H 2 -based biological communities, contribute to atmospheric warming, and augment local magnetic signatures in planetary lithospheres. [ABSTRACT FROM AUTHOR]

A challenge in quantitative biology is to predict output patterns of gene expression from knowledge of input transcription factor patterns and from the arrangement of binding sites for these transcription factors on regulatory DNA. We tested whether widespread thermodynamic models could be used to infer parameters describing simple regulatory architectures that inform parameter-free predictions of more complex enhancers in the context of transcriptional repression by Runt in the early fruit fly embryo. By modulating the number and placement of Runt binding sites within an enhancer, and quantifying the resulting transcriptional activity using live imaging, we discovered that thermodynamic models call for higher-order cooperativity between multiple molecular players. This higher-order cooperativity captures the combinatorial complexity underlying eukaryotic transcriptional regulation and cannot be determined from simpler regulatory architectures, highlighting the challenges in reaching a predictive understanding of transcriptional regulation in eukaryotes and calling for approaches that quantitatively dissect their molecular nature.

The mobility industry has experienced a fast evolution towards electric-based transport in recent years. Recently, hybrid electric vehicles, which combine electric and conventional combustion systems, have become the most popular alternative by far. This is due to longer autonomy and more extended refueling networks in comparison with the recharging points system, which is still quite limited in some countries. This paper aims to conduct a literature review on thermodynamic models of heat engines used in hybrid electric vehicles and their respective configurations for series, parallel and mixed powertrain. It will discuss the most important models of thermal energy in combustion engines such as the Otto, Atkinson and Miller cycles which are widely used in commercial hybrid electric vehicle models. In short, this work aims at serving as an illustrative but descriptive document, which may be valuable for multiple research and academic purposes.

• Solubility of β-HMX in three binary mixed solvent systems was measured by the laser dynamic method. • Six thermodynamic models were used to correlate the solubility of β-HMX. • The thermodynamic properties' microscopic mechanisms of β-HMX were revealed by DFT calculations and MD simulations. Octogen (HMX) is the most powerful military explosive in current use. However, the unclear thermodynamic molecular mechanisms severely limit the development of its production process. In this paper, the solubility of β-HMX in three binary mixed solvent systems (acetone + ethanol, acetone + dichloromethane, acetone + toluene) was measured via a dynamic method at temperature ranging from 283.15 to 313.15 K under atmospheric pressure. The experimental results reveal that the solubility of β-HMX in these binary mixed solvent systems is positively correlated with acetone molar fraction and temperature, and the solvent composition has a greater impact on its solubility compared with the temperature. Moreover, the solubility of β-HMX is further correlated with the Van't Hoff equation, modified Apelblat equation, CNIBS/R-K model, Jouyban-Acree-Van't Hoff model, Jouyban-Acree-Apelblat model and NRTL model, and the modified Apelblat equation can give better fitting result (ARD = 8.101 × 10−3, RMSD = 1.065 × 10−5). Finally, the microscopic mechanism of the thermodynamic properties of β-HMX in binary mixed solvents is revealed by investigating the types, intensity and interaction sites of interactions based on density functional theory (DFT) and molecular dynamic (MD) simulation. The results demonstrate that both acetone molecules and ethanol molecules can form certain intermolecular interactions with β-HMX molecules, which are the main driving force of solubilization. In contrast, solvent–solvent interactions have an antagonistic effect on the solubility of β-HMX in mixed solvents. This work can further be informative for researchers in the field of energetic material for the solubility evaluations and provide a reference for the industrial production and performance enhancement of HMX in the future. [ABSTRACT FROM AUTHOR]

Propionic acid extraction is of economic and environmental importance. In the present study, the liquid-liquid equilibrium data of the ternary system of water + propionic acid + cyclic alcohols (cyclopentanol and cyclohexanol) was obtained at 303.2, 313.2, and 323.2 K temperatures. Phase behavior of type-1 has been observed for studied systems. The Hand and Bachman equations confirm the validity of the measured data. For correlation of liquid-liquid equilibrium data, the NRTL and UNIQUAC thermodynamic models have been used and the coefficients of the inter-molecular interaction have been determined. RMSD values for NRTL and UNIQUAC models in cyclopentanol-containing systems were 0.0107 and 0.0057, respectively, and for cyclohexanol 0.0108 and 0.0076 respectively, which showed the accuracy of these models in correlation liquid-liquid equilibrium data. The values of the selectivity factor for both solvents larger than the unit are obtained, which indicates the ability of the solvents to extract propionic acid. [ABSTRACT FROM AUTHOR]