Thermodynamics-based Model Research Articles

A thermodynamic based constitutive model considering the mutual influence of multiple physical fields

In multiple physical fields, the mutual influence among these fields can significantly impact material elastoplasticity. This paper proposes a thermodynamic-based constitutive model that incorporates the mutual influence of multiple physical fields. Rather than treating physical field characteristics as adjustable “parameters” affecting material coefficients, the proposed model employs a thermodynamic dissipation potential derived from the Onsager reciprocity relations, accounting for thermodynamic forces coupling. This dissipation potential ensures that the thermodynamic flow in the stress field is influenced by both stress field and other physical fields thermodynamic forces, which describes the plastic flow under multiple physical fields, while preserving thermodynamic duality. The paper begins with the formulation of a generalized thermodynamic model applicable to diverse materials and types of coupled fields, which is then degraded to a specific model for AA5182-O AlMg alloy under the influence of temperature and strain rate fields coupling. Given the universal applicability of the generalized model, such degradation provides a structured approach framework for developing thermodynamics-based constitutive models. For different materials encountered in practical engineering, new thermodynamic forces can be introduced to describe their unique mechanical properties while preserving the overarching thermodynamics-based model framework, thereby facilitating model scalability. The paper concludes with a validation example, showing that within the Portevin-Le Chatelie (PLC) regime, the plastic flow stress of AA5182-O AlMg alloy decreases with increasing strain rate at low temperatures but increases at high temperatures. The accurate simulation of these distinct strain rate effects crucially relies on integrating the mutual influence of temperature field and strain rate field.

Mechanistic analysis of enhancer sequences in the estrogen receptor transcriptional program

Estrogen Receptor α (ERα) is a major lineage determining transcription factor (TF) in mammary gland development. Dysregulation of ERα-mediated transcriptional program results in cancer. Transcriptomic and epigenomic profiling of breast cancer cell lines has revealed large numbers of enhancers involved in this regulatory program, but how these enhancers encode function in their sequence remains poorly understood. A subset of ERα-bound enhancers are transcribed into short bidirectional RNA (enhancer RNA or eRNA), and this property is believed to be a reliable marker of active enhancers. We therefore analyze thousands of ERα-bound enhancers and build quantitative, mechanism-aware models to discriminate eRNAs from non-transcribing enhancers based on their sequence. Our thermodynamics-based models provide insights into the roles of specific TFs in ERα-mediated transcriptional program, many of which are supported by the literature. We use in silico perturbations to predict TF-enhancer regulatory relationships and integrate these findings with experimentally determined enhancer-promoter interactions to construct a gene regulatory network. We also demonstrate that the model can prioritize breast cancer-related sequence variants while providing mechanistic explanations for their function. Finally, we experimentally validate the model-proposed mechanisms underlying three such variants.

Titanium and iron isotopic records of granitoid crust production in diverse Archean cratons

Archean granitoid provides critical clues on how Earth's felsic crust was established and its geodynamics evolved. In this study, we present Fe-Ti isotope and trace-element data for granitoids (mostly TTGs) from the ∼3.8-3.6 Ga Itsaq Gneiss Complex and ∼3.3 Ga East Pilbara Terrane, Pilbara Craton. TTGs from those localities and several other cratons follow the same Ti isotopic fractionation trend as modern calc-alkaline rocks. This similarity hides important petrogenetic differences as partial melting could have played a much more important role in establishing the felsic character of TTGs compared to modern granites of calc-alkaline affinity. Our thermodynamics-based modeling of isotopic fractionation shows that partial melting of hydrated metabasite can explain the Fe and Ti isotopic compositions of many TTGs but reworking of tonalite crust is needed to explain the most extreme compositions. The same Ti isotopic fractionation trends have been found now in several cratons (West Greenland, Slave, Pilbara, and Kaapvaal cratons) in granitoids formed in different geothermal gradients, meaning that it was likely a global signature of the Archean crust. Sediment provenance studies that use those TTG compositions and point to a primarily felsic crust in the Archean are therefore valid.

Thermo-Hydro-Chemo-Mechanical (THCM) Continuum Modeling of Subsurface Rocks: A Focus on Thermodynamics-Based Constitutive Models

Abstract Accurate multiphysics modeling is necessary to simulate and predict the long-term behavior of subsurface porous rocks. Despite decades of modeling subsurface multiphysics processes in porous rocks, there are still considerable uncertainties and challenges remaining partly because of the way the constitutive equations describing such processes are derived (thermodynamically or phenomenologically) and treated (continuum or discrete) regardless of the way they are solved (e.g., finite element or finite volume methods). We review here continuum multiphysics models covering aspects of poromechanics, chemo-poromechanics, thermo-poromechanics, and thermo-chemo-poromechanics. We focus on models that are derived based on thermodynamics to signify the importance of such a basis and discuss the limitations of the phenomenological models and how thermodynamics-based modeling can overcome such limitations. The review highlights that the experimental determination of thermodynamics response coefficients (coupling or constitutive coefficients) and field applicability of the developed thermodynamics models are significant research gaps to be addressed. Verification and validation of the constitutive models, preferably through physical experiments, is yet to be comprehensively realized which is further discussed in this review. The review also shows the versatility of the multiphysics models to address issues from shale gas production to CO2 sequestration and energy storage and highlights the need for inclusion of thermodynamically consistent damage mechanics, coupling of chemical and mechanical damage, and two-phase fluid flow in multiphysics models.

Design Optimization of a Gas Turbine Engine for Marine Applications: Off-Design Performance and Control System Considerations.

This paper addresses a design optimization of a gas turbine (GT) for marine applications. A gain-scheduling method incorporating a meta-heuristic optimization is proposed to optimize a thermodynamics-based model of a small GT engine. A comprehensive control system consisting of a proportional integral (PI) controller with additional proportional gains, gain scheduling, and a min-max controller is developed. The modeling of gains as a function of plant variables is presented. Meta-heuristic optimizations, namely a genetic algorithm (GA) and a whale optimization algorithm (WOA), are applied to optimize the designed control system. The results show that the WOA has better performance than that of the GA, where the WOA exhibits the minimum fitness value. Compared to the unoptimized gain, the time to reach the target of the power lever angle is significantly reduced. Optimal gain scheduling shows a stable response compared with a fixed gain, which can have oscillation effects as a controller responds. An effect of using bioethanol as a fuel has been observed. It shows that for the same input parameters of the GT dynamics model, the fuel flow increases significantly, as compared with diesel fuel, because of its low bioethanol heating value. Thus, a significant increase occurs only at the gain that depends on the fuel flow.

Cerium anomaly as a tracer for paleo-oceanic redox conditions: A thermodynamics-based Ce oxidation modeling approach

Reconstructing redox conditions in the paleo-ocean is essential to understand the Earth’s biogeochemical evolution. Cerium (Ce) anomaly in marine sediments has been used to distinguish oxic versus anoxic depositional environments in the Paleo-ocean. Previous studies suggested that dissolved oxygen is indispensable to cerium oxidation. Therefore, this reaction can be thermodynamically modeled to quantify oxygen contents in the ocean. This study presents a series of thermodynamics-based models to relate Ce anomaly to dissolved oxygen level. We then evaluated these models in two representatively settings, including an oxic ocean and anoxic basin. Finally, we examined the modeled relationship on a compiled dataset of cerium anomaly and dissolved oceanic oxygen content. These models suggest that the cerium anomaly is quantitatively related to oceanic oxygen, pH, and phosphate concentration. Notably, the results suggest that cerium anomaly is not sensitive to changes in dissolved oxygen in oxic environments. By contrast, Ce anomaly is well correlated with dissolved oxygen in anoxic environments, and it was less affected by pH and phosphate concentration. This research has significant implications for using lanthanide patterns in ancient marine carbonates to quantify dissolved oxygen level, especially during anoxic events in the Paleo-ocean.

A semantics, energy-based approach to automate biomodel composition.

Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.

Unified mechanics theory based flow stress model for the rate-dependent behavior of bcc metals

A unified mechanics theory-based micromechanical model is developed to investigate the rate-dependent post-yield behavior of body-centered cubic(bcc) metals. The entropy generation mechanisms in bcc metals at a high strain rate are investigated. Thermodynamic State Index(TSI) in the unified mechanics theory is used to model the state of material as a function of entropy generation rate and then a dynamic yield stress function is derived. This work introduces a novel approach to modeling the internal heat generation and vacancy concentration change, at high strain rates. The derived rate-dependent model is validated for a wide range of strain rates, using the test data [1] for mild steel and compared with an irreversible thermodynamics-based model, available in the literature.

Thermodynamics-based modeling reveals regulatory effects of indirect transcription factor-DNA binding

SummaryTranscription factors (TFs) influence gene expression by binding to DNA, yet experimental data suggests that they also frequently bind regulatory DNA indirectly by interacting with other DNA-bound proteins. Here, we used a data modeling approach to test if such indirect binding by TFs plays a significant role in gene regulation. We first incorporated regulatory function of indirectly bound TFs into a thermodynamics-based model for predicting enhancer-driven expression from its sequence. We then fit the new model to a rich data set comprising hundreds of enhancers and their regulatory activities during mesoderm specification in Drosophila embryogenesis and showed that the newly incorporated mechanism results in significantly better agreement with data. In the process, we derived the first sequence-level model of this extensively characterized regulatory program. We further showed that allowing indirect binding of a TF explains its localization at enhancers more accurately than with direct binding only. Our model also provided a simple explanation of how a TF may switch between activating and repressive roles depending on context.

Thermodynamics-based modeling reveals regulatory effects of indirect transcription factor-DNA binding in Drosophila

Sequence-to-expression relationship is one of the major research topics in the field of regulatory genomics. Prediction of epigenomic states such as DNA accessibility or transcription factor(TF)-DNA binding has been studied extensively, but predicting a gene's expression in different cell types based on its regulatory enhancer sequences remains largely unsolved. Here, we present a thermodynamics-based sequence-to-expression model that combines DNA accessibility, TF concentrations and enhancer sequence information to classify enhancers into their spatio-temporal activity classes in Drosophila mesoderm.

The Fundaments of Structural Integrity of Large-Scale Pressure Systems

At Centre for Energy Research in Budapest, Hungary, research is underway to develop sound fundaments for future Structural Integrity Calculations of Large-Scale Pressure Systems. Many existing Structural Integrity Calculation methodologies have been revised. Despite the fact that many complex Large-Scale Pressure Systems have been built and operated over the decades based on the tried, standard-based engineering approaches, it has emerged that there are inherent problems even at the core of these methodologies. Generalised concept to Structural Integrity seems to be a promising approach to lay solid fundaments for future Structural Integrity Calculations methodologies for Large-Scale Pressure Systems. The paper outlines the structure of the framework, shows how philosophical considerations can be used to pave the way for a sounder scientific approach to Structural Integrity of Large-Scale Pressure Systems, and finally presents the base of an enhanced, modern thermodynamics-based model.

On swelling stress–strain of coal and their interaction with external stress

Gas sorption and its induced volumetric strain can significantly influence gas flow in coal by controlling the change in the conductivity of coal cleats. A significant number of studies have been conducted to date to describe the coal swelling stress with sorbing gases and several theoretical models have been proposed to estimate swelling stresses. Despite these efforts, the accurate prediction of coal swelling stress remains a challenge hence a comprehensive theoretical and experimental investigation of swelling stress is required. This is particularly important when swelling stress of fractured coals develops under external loading. We, therefore, perform two sets of time-dependent diffusion and volumetric strain experiments under various stress conditions and gas pressures on coal specimens (a highly cleated and a dense sample) exposed to helium and carbon dioxide. These experiments are conducted to investigate i) the performance of commonly used theoretical models for swelling stress estimation, ii) the validity of thermodynamics swelling coupling coefficient defining the swelling stress and iii) the effect of external stress on coal volumetric strain response (hydromechanical versus swelling/shrinkage). Our analysis shows that the developed models based on non-equilibrium thermodynamics can predict both the evolution and the final swelling stress closely. We further show that the new definition of swelling coupling coefficient leads to greater performance of non-equilibrium thermodynamics-based models and further suggest a new experimental technique for characterizing this coupling coefficient. Finally, the results reveal that the effect of external stress on the hydromechanical volumetric strain of coal (during gas adsorption by unloading and desorption by loading) has a considerable hysteresis, especially at high pore pressures.

Theoretical and Experimental Investigation of Bifunctional Oxygen Electrocatalysts from Carbonized MOFs

Multifunctional electrocatalysts are the key to sustainable energetics. An efficient bifunctional catalyst material that can catalyze both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is required for rechargeable metal-air batteries. Although recent research has shown materials that can compete with the standard expensive noble metal catalysts (Pt and RuO2), further advances are needed. Most notable class of new catalysts includes carbonized metal-organic frameworks (MOFs), which leads to active single site catalysts. Furthermore, computational chemistry-based methods are essential to explain the observed activity and provide further guidelines to the synthesis of better performing materials. Here we give an overview of recent advances in computationally guided electrocatalyst evaluation. We highlight the limitations observed by thermodynamics-based modelling and discuss proposed solutions for improved catalytic materials.

Thermodynamics-Based Model Construction for the Accurate Prediction of Molecular Properties From Partition Coefficients.

Developing models for predicting molecular properties of organic compounds is imperative for drug development and environmental safety; however, development of such models that have high predictive power and are independent of the compounds used is challenging. To overcome the challenges, we used a thermodynamics-based theoretical derivation to construct models for accurately predicting molecular properties. The free energy change that determines a property equals the sum of the free energy changes (ΔGFs) caused by the factors affecting the property. By developing or selecting molecular descriptors that are directly proportional to ΔGFs, we built a general linear free energy relationship (LFER) for predicting the property with the molecular descriptors as predictive variables. The LFER can be used to construct models for predicting various specific properties from partition coefficients. Validations show that the models constructed according to the LFER have high predictive power and their performance is independent of the compounds used, including the models for the properties having little correlation with partition coefficients. The findings in this study are highly useful for applications in drug development and environmental safety.

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks.

Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.

Solubility determination, model evaluation and solution thermodynamics of isovanillin in 15 pure solvents and 4 binary solvents

Researches on the basic solubility data and the physicochemical parameters of isovanillin are scarce in literature. In this paper, the solubility data, dissolution thermodynamic properties of isovanillin in 15 organic pure solvents (methanol, ethanol, n-propanol, iso-propanol, n-butanol, iso-butanol, methyl acetate, ethyl acetate, isobutyl acetate, formic acid, acetic acid, propionic acid, acetone, xylene and diethyl ether) and 4 binary solvents (ethanol + water, iso-propanol + water acetic acid + water, propionic acid + water) were determined at T = 278.15 to 318.15 K and T = 283.15 to 315.15 K, respectively, and reported for the first time. Three classic models were employed to correlate the experimental solubility, including an empirical equation and two thermodynamics-based models of Apelblat model and λh model. The models used were further evaluated by root mean square deviation (RMSD). Results show that the solubility of isovanillin presents a strong dependency on solution temperature and the polarity of solvents used. It shows high solubility in strong polar solvents such as formic acid, methanol and acetone, while low in less polar solvents such as xylene, diethyl ether. In the investigated binary solvents, a significant co-solvency phenomenon is observed, and the increase in solubility is found to do with the polarity of good solvent used in this study. RMSD value suggests that all the models used perform good correlation. Furthermore, the single crystal structure of isovanillin was solved and reported for the first time. Besides, the melting point and the fusion entropy of isovanillin were determined by DSC, and the thermodynamic properties of isovanillin dissolution process including ΔsolG, ΔsolH and ΔsolS were calculated by Van’t Hoff equation. Results indicate that the dissolution process of isovanillin is an endothermic, nonspontaneous entropy-driven process.

Non-Equilibrium Thermodynamics-Based Convective Drying Model Applied to Oblate Spheroidal Porous Bodies: A Finite-Volume Analysis

Commonly based on the liquid diffusion theory, drying theoretical studies in porous materials has been directed to plate, cylinder, and sphere, and few works are applied to non-conventional geometries. In this sense, this work aims to study, theoretically, the drying of solids with oblate spheroidal geometry based on the thermodynamics of irreversible processes. Mathematical modeling is proposed to describe, simultaneously, the heat and mass transfer (liquid and vapor) during the drying process, considering the variability of the transport coefficients and the convective boundary conditions on the solid surface, with particular reference to convective drying of lentil grains at low temperature and moderate air relative humidity. All the governing equations were written in the oblate spheroidal coordinates system and solved numerically using the finite-volume technique and the iterative Gauss–Seidel method. Numerical results of moisture content, temperature, liquid, vapor, and heat fluxes during the drying process were obtained, analyzed, and compared with experimental data, with a suitable agreement. It was observed that the areas near the focal point of the lentil grain dry and heat up faster; consequently, these areas are more susceptible to the appearance of cracks that can compromise the quality of the product. In addition, it was found that the vapor flux was predominant during the drying process when compared to the liquid flux.

New insight into the role of inclusions in hydrogen-induced degradation of fracture toughness: three-dimensional imaging and modeling

ABSTRACT An in-depth understanding of the role of non-metallic inclusions (NMIs) in the hydrogen-induced failure of structural materials is important in the manufacture and application of steels. In this paper we investigated the type, the amount and the distribution of NMIs in pipeline steels and their relation to the susceptibility to hydrogen-induced cracking (HIC). Scanning Electron Microscope (SEM) observation confirmed the interlinking of the microcracks formed at the inclusion-matrix interfaces. By combining with the nondestructive three-dimensional (3D) mapping of crack propagation paths, based on the synchrotron tomography technique, we obtained direct evidence that the cracking initiation at the NMIs and then interlinking on the (nearly) same plane are the main mechanism of HIC failure in X70 steels. We built an elastic-energy-based model, which can be applied to quantitatively predict the HIC-induced dependence of the fracture toughness on NMIs, based on statistical information of the NMIs. The theoretical results show a good agreement with the experimental observation. We proposed a criterion to determine the susceptibility to HIC by the observation of NMIs. We also developed a thermodynamics-based model to analyze the hydrogen trapping at the inclusion-matrix interface and its dependence on the strength of the steel matrix. For the first time, the direct relationship between NMIs and HIC-induced degradation of fracture toughness is obtained.

A persistently low level of atmospheric oxygen in Earth\u2019s middle age

Resolving how Earth surface redox conditions evolved through the Proterozoic Eon is fundamental to understanding how biogeochemical cycles have changed through time. The redox sensitivity of cerium relative to other rare earth elements and its uptake in carbonate minerals make the Ce anomaly (Ce/Ce*) a particularly useful proxy for capturing redox conditions in the local marine environment. Here, we report Ce/Ce* data in marine carbonate rocks through 3.5 billion years of Earth’s history, focusing in particular on the mid-Proterozoic Eon (i.e., 1.8 – 0.8 Ga). To better understand the role of atmospheric oxygenation, we use Ce/Ce* data to estimate the partial pressure of atmospheric oxygen (pO2) through this time. Our thermodynamics-based modeling supports a major rise in atmospheric oxygen level in the aftermath of the Great Oxidation Event (~ 2.4 Ga), followed by invariant pO2 of about 1% of present atmospheric level through most of the Proterozoic Eon (2.4 to 0.65 Ga).

Transport-Based Modeling of Bubble Nucleation on Gas Evolving Electrodes.

Bubble nucleation is ubiquitous in gas evolving reactions that are instrumental for a variety of electrochemical systems. Fundamental understanding of the nucleation process, which is critical to system optimization, remains limited as prior works generally focused on the thermodynamics and have not considered the coupling between surface geometries and different forms of transport in the electrolytes. Here, we establish a comprehensive transport-based model framework to identify the underlying mechanism for bubble nucleation on gas evolving electrodes. We account for the complex effects on the electrical field, ion migration, ion diffusion, and gas diffusion arising from surface heterogeneities and gas pockets initiated from surface crevices. As a result, we show that neglecting these effects leads to significant underprediction of the energy needed for nucleation. Our model provides a non-monotonic relationship between the surface cavity size and the overpotential required for nucleation, which is physically more consistent than the monotonic relationship suggested by a traditional thermodynamics-based model. We also identify the significance of the gas diffuse layer thickness, a parameter controlled by external flow fields and overall electrode geometries, which has been largely overlooked in previous models. Our model framework offers guidelines for practical electrochemical systems whereby, without changing the surface chemistry, nucleation on electrodes can be tuned by engineering the cavity size and the gas diffuse layer thickness.