Thermodynamic Approach Research Articles

A thermodynamic approach to evaluating the ecological health and sustainability of integrated production systems in Goharkuh Taftan agro-industrial complex and sensitivity analysis of the results

In recent times, the increasing influx of energy inputs into farming systems has led to a significant enhancement in their overall efficiency. However, this has happened at the expense of endangering the sustainability of these systems and degrading the environment. Therefore, it is crucial to develop a methodology to evaluate the resilience of agricultural systems. This study utilised the Steinborn and Svirezhev methodology to assess five different production systems (wheat, barley, alfalfa, cotton, and Pistachio) within the Goharkuh Taftan agro-industrial complex. The approach measures the excessive production of entropy, which acts as an indicator of the system's departure from sustainability. The study focuses on four components: overproduction of entropy, limit energy load, maximum crop yield for sustainable agriculture, and deviation from sustainable agriculture. The results indicated that the production systems analysed in this study produce surplus entropy, thus rendering them in an unstable condition. Among all the products, alfalfa had the lowest entropy overproduction, while pistachio had the highest. The three agricultural commodities, namely wheat, barley, and cotton, are situated at a point equidistant from the two opposite ends. Alfalfa has shown greater energy use efficiency compared to pistachios. It surpasses the maximum crop yield for sustainable agriculture and has less deviation from sustainable agriculture than other integrated production systems. The differences in the intensity of energy flow and the structural characteristics of the integrated production systems were responsible for the variations in the values of the examined components. Nevertheless, none of these solutions are sustainable in the long term. An analysis of the energy inputs and components of the harvest index revealed the importance of implementing management techniques that decrease the intensity of energy flows into these systems and enhance the harvest index to attain a sustainable state. Integrating supplementary renewable energy sources will bolster the long-term sustainability of production systems.

Thermodynamic and computational approaches to the stability and structural transformation of Xe + large-molecule guest substance (LMGS) hydrates

In this study, the influence of different types of large-molecule liquid substances (LMGSs) and formation conditions on the stability and structural transformation of Xe + LMGS hydrates was investigated using phase equilibria, powder X-ray diffraction (PXRD), 129Xe NMR spectroscopy, and molecular dynamics (MD) simulations. The phase equilibria of Xe hydrates in the presence of three different LMGS types (neohexane [NH], methylcyclopentane [MCP], and methylcyclohexane [MCH]) were measured in the pressure range of 0.1–1.0 MPa. The equilibrium curves of Xe + MCH and Xe + NH hydrates shifted away from that of pure Xe hydrate under low pressure, whereas they coincided with that of pure Xe hydrate under high pressure. Interestingly, the equilibrium curve of Xe + MCP hydrate aligned with that of pure Xe hydrate throughout the pressure range. PXRD and 129Xe NMR analyses demonstrated that the equilibrium curve shift under low pressure was caused by the formation of sH (Xe + LMGS) hydrates, which was attributed to the inclusion of NH or MCH. However, MCP did not participate in sH hydrate formation with Xe. MD simulations revealed that MCP in the large cages did not contribute to the thermodynamic or dynamic stability of sH hydrates. The findings of this study provide valuable insights into the development of hydrate-based noble gas capture and storage.

Exploring antioxidative properties of xanthohumol and isoxanthohumol: An integrated experimental and computational approach with isoxanthohumol pKa determination

This study explores the antioxidative activities of xanthohumol (XN) and isoxanthohumol (IXN), prenylated flavonoids from Humulus lupulus (family Cannabaceae), utilizing the oxygen radical absorption capacity (ORAC) and ferric reducing antioxidant power (FRAP) assays along with computational Density Functional Theory methods. Experimentally, XN demonstrated significantly higher antioxidative capacities than IXN. Moreover, we determined IXN pKa values using the UV/Vis spectrophotometric method for the first time, facilitating its accurate computational modeling under physiological conditions. Through a thermodynamic approach, XN was found to efficiently scavenge HOO• and CH3O• radicals via Hydrogen Atom Transfer (HAT) and Radical Adduct Formation (RAF) mechanisms, while CH3OO• scavenging was feasible only through the HAT pathway. IXN exhibited its best antioxidative activity against CH3O• via both HAT and RAF mechanisms and could also scavenge HOO• through RAF. Both Single Electron Transfer (SET) and Sequential Proton Loss-Electron Transfer (SPLET) mechanisms were thermodynamically unfavorable for all radicals and both compounds.

Surface thermomigration of 2D voids

In a thermal gradient, surface nanostructures have been experimentally observed to move due to thermomigration. However, analytical models that describe the thermomigration force acting on surfaces are still controversial. In this work, we start from a thermodynamic approach based on the Massieu function, which is used to describe thermomigration of single adatoms, to develop an expression for the velocity of thermomigrating 2D holes. The model can be simplified in two limiting cases: (i) When the hole motion is limited by adspecies diffusion, the velocity is independent from the hole size (as in our experiments). (ii) If the hole motion is limited by the attachment or detachment of species to or from steps, then the velocity is proportional to the hole width. We have studied the thermomigration of 2D monatomic deep holes on Si(100) using low energy electron microscopy. From the velocity measurements taken at different temperatures, we find, using our model, that the sum of the migration energy and the adatom creation energy is 1.95 ± 0.16 eV. This value is consistent with those found by other authors, reinforcing the validity of our thermomigration model.

Predicting Reactivity and Passivation of Solid-State Battery Interfaces.

In this work, we build a computationally inexpensive, data-driven model that utilizes atomistic structure information to predict the reactivity of interfaces between any candidate solid-state electrolyte material and a Li metal anode. This model is trained on data from ab initio molecular dynamics (AIMD) simulations of the time evolution of the solid electrolyte-Li metal interfaces for 67 different materials. Predicting the reactivity of solid-state interfaces with ab initio techniques remains an elusive challenge in materials discovery and informatics, and previous work on predicting interfacial compatibility of solid-state Li-ion electrolytes and Li metal anodes has focused mainly on thermodynamic convex hull calculations. Our framework involves training machine learning models on AIMD data, thereby capturing information on both kinetics and thermodynamics, and then leveraging these models to predict the reactivity of thousands of new candidates in the span of seconds, avoiding the need for additional weeks-long AIMD simulations. We identify over 300 new chemically stable and over 780 passivating solid electrolytes that are predicted to be thermodynamically unfavored. Our results indicate many potential solid-state electrolyte candidates have been incorrectly labeled unstable via purely thermodynamic approaches using density functional theory (DFT) energetics, and that the pool of promising, Li-stable solid-state electrolyte materials may be much larger than previously thought from screening efforts. To showcase the value of our approach, we highlight two borate materials that were identified by our model and confirmed by further AIMD calculations to likely be highly conductive and chemically stable with Li: LiB13C2 and LiB12PC.

Engineering ratchet-based particle separation via extended shortcuts to isothermality.

Microscopic particle separation plays a vital role in various scientific and industrial domains. Conventional separation methods relying on external forces or physical barriers inherently exhibit limitations in terms of efficiency, selectivity, and adaptability across diverse particle types. To overcome these limitations, researchers are constantly exploring new separation approaches, among which ratchet-based separation is a noteworthy method. However, in contrast to the extensive numerical studies and experimental investigations on ratchet separation, its theoretical exploration appears weak, particularly lacking in the analysis of energy consumption involved in the separation processes. The latter is of significant importance for achieving energetically efficient separation. In this paper, we propose a nonequilibrium thermodynamic approach, extending the concept of shortcuts to isothermality, to realize controllable separation of overdamped Brownian particles with low energy cost. By utilizing a designed ratchet potential with temporal period τ, we find in the slow-driving regime that the average particle velocity v[over ¯]_{s}∝(1-D/D^{*})τ^{-1}, indicating that particles with different diffusion coefficients D can be guided to move in distinct directions with a preset D^{*}. It is revealed that an inevitable portion of the energy cost in separation depends on the driving dynamics of the ratchet, with an achievable lower bound W_{ex}^{(min)}∝L^{2}|v[over ¯]_{s}|. Here, L is the thermodynamic length of the driving loop in the parametric space. With a sawtooth potential, we numerically test the theoretical findings and illustrate the optimal separation protocol associated with W_{ex}^{(min)}. Finally, for practical considerations, we compare our approach with the conventional ratchets in terms of separation velocity and energy consumption. The scalability of the current framework for separating various particles in two-dimensional space is also demonstrated. This paper bridges the gap between thermodynamic process control and particle separation, paving the way for further thermodynamic optimization in ratchet-based particle separation.

New BDNF and NT-3 Cyclic Mimetics Concur with Copper to Activate Trophic Signaling Pathways as Potential Molecular Entities to Protect Old Brains from Neurodegeneration.

A low level of Neurotrophins (NTs), their Tyrosine Kinase Receptors (Trks), Vascular Endothelial Growth Factors (VEGFs) and their receptors, mainly VEGFR1 and VEGFR2, characterizes AD brains. The use of NTs and VEGFs as drugs presents different issues due to their low permeability of the blood-brain barrier, the poor pharmacokinetic profile, and the relevant side effects. To overcome these issues, different functional and structural NT mimics have been employed. Being aware that the N-terminus domain as the key domain of NTs for the binding selectivity and activation of Trks and the need to avoid or delay proteolysis, we herein report on the mimicking ability of two cyclic peptide encompassing the N-terminus of Brain Derived Growth Factor (BDNF), (c-[HSDPARRGELSV-]), cBDNF(1-12) and of Neurotrophin3 (NT3), (c-[YAEHKSHRGEYSV-]), cNT3(1-13). The two cyclic peptide features were characterized by a combined thermodynamic and spectroscopic approach (potentiometry, NMR, UV-vis and CD) that was extended to their copper(II) ion complexes. SH-SY5Y cell assays show that the Cu2+ present at the sub-micromolar level in the complete culture media affects the treatments with the two peptides. cBDNF(1-12) and cNT3(1-13) act as ionophores, induce neuronal differentiation and promote Trks and CREB phosphorylation in a copper dependent manner. Consistently, both peptide and Cu2+ stimulate BDNF and VEGF expression as well as VEGF release; cBDNF(1-12) and cNT3(1-13) induce the expression of Trks and VEGFRs.

Thermodynamic approach for designing processing routes of 4Mn quenching and partitioning steel

AbstractThe study addresses the design and optimization of chemical composition and processing routes of new quenching and partitioning medium-Mn alloy using theoretical and experimental approaches. The thermodynamic calculations using Thermo-Calc and JMatPro software were carried out to characterize the influence of Mn, Si and Al contents on cementite formation and precipitation processes. The evolution of individual phases as a function of temperature under thermodynamic equilibrium conditions was estimated. The investigations included the determination of continuous cooling transformation (CCT) and the time–temperature transformation (TTT) diagrams of a model 4Mn alloy. The calculated equilibrium diagrams were compared with the experimental diagrams determined using dilatometric tests. Microstructural observations were carried out to verify the results of dilatometric measurements. The results of thermodynamic calculations and experimental tests showed the moderate agreement. It is related to the inaccuracy of currently available models in the used software and/or non-equilibrium conditions of experimental tests.

Electromagnetic forces and their finite element computation

AbstractThis paper introduces the concepts of differential geometry that are necessary to establish a systematic definition for electromagnetic forces by means of a natural thermodynamic approach. It is shown that standard electromagnetic force formulae used in finite element computational electromagnetism are particular instances of that general approach. Finally, the paper offers a complete conceptual framework, as well as a mathematical toolbox, to derive electromagnetic force formulae for multi‐physics finite element models with complex materials.

Biophysical Approach to Understand Life and Cancer

ABSTRACTBackgroundFrom the perspective of biology, the characteristics of life can be categorized as cellular organizations, homeostasis, metabolism, growth, reproduction and heredity, response to stimuli and adaptation to the environment. From the perspective of physics, living organisms are highly ordered, complex, thermodynamically open systems; they are in non‐equilibrium phase. According to the second law of thermodynamics, every system in the universe is going to the disorder spontaneously. Maximum entropy signifies a thermodynamic equilibrium which means the death. Today, cancer is a major global health problem and despite the explosive development of our knowledge about the carcinogenesis the “war on cancer” has not yet been won.AimsTo examine life and cancer together based on current biophysical approach and to shed light on new paradigms.Materials & MethodsA systematic literature search for publications on a thermodynamic approach to understand life and cancer was conducted in PubMed without language restrictions. The reference lists of identified studies were also used as additional knowledge.ResultsLiving organisms exchange entropy and they gain information from the external environment. Information can be stored as memory. Life is a category of emergence like art composed from correct modules. On the contrary, cancer is the emergence of a disease formed by incorrect modules. Cancer is a chaotic disease at least for a limited period and cannot arise from healthy functional tissue units. Chaos of the lower level may be associated with the entropy increase of upper level.ConclusionsBiologic chaos control is possible.

Principles of Molecular Evolution: Concepts from Non-equilibrium Thermodynamics for the Multilevel Theory of Learning.

We present a non-equilibrium thermodynamics approach to the multilevel theory of learning for the study of molecular evolution. This approach allows us to study the explicit time dependence of molecular evolutionary processes and their impact on entropy production. Interpreting the mathematical expressions, we can show that two main contributions affect entropy production of molecular evolution processes which can be identified as mutation and gene transfer effects. Accordingly, our results show that the optimal adaptation of organisms to external conditions in the context of evolutionary processes is driven by principles of minimum entropy production. Such results can also be interpreted as the basis of some previous postulates of the theory of learning. Although our macroscopic approach requires certain simplifications, it allows us to interpret molecular evolutionary processes using thermodynamic descriptions with reference to well-known biological processes.

Structural Particularities, Prediction, and Synthesis Methods in High-Entropy Alloys

High-Entropy Alloys (HEAs) represent a transformative class of materials characterized by multiple principal elements and high configurational entropy. This review article provides an in-depth examination of their structural particularities, prediction methodologies, and synthesis techniques. HEAs exhibit unique structural stability due to high-entropy effects, severe lattice distortions, and slow diffusion processes. Predictive models, including thermodynamic and kinetic approaches, are essential for understanding phase stability. Various synthesis methods impact HEA properties, and advanced characterization techniques are crucial for their study. The article highlights current applications and future research directions, emphasizing the potential of HEAs in diverse technological fields.

IBFFM Low-Lying States and Their Spin- Dependent Level Densities For Even-A Nuclei Associated with SU(6) Approximation and It’s O(6) Dynamical Symmetry of IBM

Objective: in this paper spin dependent level density dependence from dynamical, exchange particle-quasiparticle interactions and residual proton-neutron interactions are investigated. Theoretical framework: in the interacting boson-fermion-fermion model(IBFFM) for odd-odd nuclei 196Au the low-lying states and their densities are calculated for π d 3/2 , π d 5/2 , π s ½ , π h11/2 proton quasiparticles and ν p1/2, ν f5/2, ν p3/2, ν f7/2, ν i13/2 neutron quasiparticles and ν p1/2, ν f5/2, ν p3/2, ν f7/2, ν i13/2 neutron quasiparticles states, coupled to the IBM core in Su(6) approximation and it's O(6) dynamical symetry of interacting boson model (IBM). Method: we also applied cutting bosons and fermions space and investigated their impacts on spin dependent level density. The results are shown graphically and compared to the previous combinatorial, thermodynamic and spectral distribution approaches for 132Pr, 244 am and 114 Cd. Results and discussion: the IBFFM low-lying states up to 2 MeV are exactely in acordance with experimentala data. The IBFFM spin–dependent level densities can be well accounted by bethe and modified spin distribution formula. For small changes of dynamical, exchange and residual interactions we have a small changes in the spin-dependent level density of states. Research implications: the complex collective features and interplay between collective and quasiparticle degrees of freedom do not influence sizeable the IBFFM spin-dependent level density distribution. Originality/value: this study contributes to the literature of IBFFM low-lying states and their spin- dependent level densities for even-A nuclei.

A thermodynamic approach to energy requirements for CO2 capture and a comparison between the minimum energy for liquid and solid sorbent processes

There has been an increased interest in the use of solid sorbents for CO2 capture from flue gases to reduce emissions from fossil energy. This work uses a simple Carnot engine-like model to compare the energy requirements for a CO2 capture process using a solid adsorbent in a circulating fluidized bed with its minimal thermodynamic needs and with the performance of a conventional liquid solvent process. The energy requirements for CO2 capture using thermal swing separation sorption are dominated by the standard Gibbs free energy of separation from the sorbent (Δg0,sep), the sensible heat needed to reach the desorption temperature, and loading optimization to avoid thermodynamic pinching effects. The Δg0,sep is an invariant of the system, so only its value at reference conditions is required and it is independent of the desorption temperature or the heat of evaporation of a liquid solvent. A baseline is established using the Δg0,sep as well as the equivalent work for a well-established amine process. In all cases the energy requirements are found to be well above the minimum thermodynamic values and those of conventional liquid absorption. Higher-capacity solid sorbents and challenging improvements on heat recovery will be needed to close the gap.

Co‐Pyrolysis and Pyrolysis of Corn‐Cob Biomass and Waste Plastic: Comprehensive Study Based on Kinetic and Thermodynamic Approach

AbstractThis study focuses on the utilization of agro‐residual corn‐cob biomass, waste plastic and the combination of both for pyrolysis reaction using thermal analysis. Circular bioeconomy is assured by closing all the resource materials loops through co‐pyrolysis process. The conversion profiles of corn cob pyrolysis at various heating rates reveal a three‐stage decomposition process, and plastic waste exhibits single stage degradation. Due to the interaction between the blended materials, additional degradation peaks arise during the co‐pyrolysis of waste plastic (PET bottles) and biomass (corn cobs). The apparent activation energy fluctuates in the range of 120–260 kJ/mol with the conversion, according to Flynn‐Wall‐Ozawa (FWO) and Kissinger‐Akahira‐Sunose (KAS) kinetic methods. Notably, for co‐pyrolysis the apparent activation energy is lower (168 kJ/mol using FWO) than the individual biomass (179 kJ/mol using FWO) and plastic (175 kJ/mol using FWO), suggesting a positive synergistic effect during charring. The liquid crude and char product analysis from corn cob pyorlysis through FTIR and XRD confirms the application of the products in energy and chemical processes. The results obtained in this study can be utilized for co‐pyrolysis reactor analysis specifically using waste plastic bottles that are accumulating in the environment.

Fast and efficient chromium(VI) extraction by colloidal Mg/Al layered double hydroxide nanoparticles

Due to the constraints associated with diffusion and mixing time, traditional kinetic and thermodynamic approaches were inadequate for probing the true mechanism of interaction between chromate and Layered Double Hydroxide (LDH). To circumvent these limitations, colloidal suspensions of Mg/Al-NO3 LDH, characterized by a positively charged surface (approximately +50 mV) in ultrapure water and a mean average diameter of 140 nm, allowing the formation of stable suspensions for days, were swiftly mixed with Cr(VI) suspensions at both pH = 4 and 9 using a stopped flow technique. This rapid mixing, accomplished in <5 milliseconds, enabled the examination of the initial stages of interaction between the toxic anion and the host compound. Two distinct steps in the adsorption process were identified: a very fast step (completed in <5 ms), representing up to 80% of the measured variation, and a slower step lasting up to 100 s. The fast step assumed to be driven by electrostatic interaction (ζ ∼ +50 mV) with the surface, and sites close to the surface are easily accessible to the chromate anions. The slower step corresponded to a diffusion process close or inside the particles. Chromate extraction efficiency was investigated through ultrafiltration tests, varying the LDH and chromate amounts, indicating that 2 nitrate ions are exchanged for 1 chromate, regardless of the pH considered, and a total exchange can be fulfilled with 0.1 g L−1 of LDH within the explored concentration range.

Experimental and thermodynamic modelling of hydrate dissociation conditions for CO[formula omitted] + propane mixtures

The possibility of hydrate formation poses a central issue for Carbon Capture and Storage (CCS) and Enhanced Oil Recovery with Water-Alternating-Gas (EOR/WAG) injection projects. In most of the cases, however, the available fluid for this purpose consists of a CO2-rich stream containing contaminants such as hydrocarbons and permanent gases. As a result, there is a growing interest in evaluating the effect of small impurities concentrations on the phase behaviour of such streams. This work investigates the impact of propane as a promoter in carbon dioxide hydrate formation, covering a concentration range in the feed gas phase between 10 and 69% on mole basis. The study also considers the Lw-LCO2-H region, taking into account liquid and supercritical transportation commonly encountered in CCS projects. Additionally, a procedure to estimate uncertainties in the graphical determination of the dissociation temperature and pressure is discussed. The thermodynamic modelling approach includes three different modifications of cubic equations of state (CEoS): asymmetric mixing rule, advanced Huron-Vidal mixing rule, and cubic-plus-association approach. An alternative procedure based on setting different sets of CO2 Kihara’s parameters when shifting between structures was also used. While satisfactory average temperature deviations were obtained for those equations of state, maximum deviation between calculated and experimental temperatures spanned from 0.5 to 2.5 K, depending on the thermodynamic model.

A comprehensive study of pharmaceutics solubility in supercritical solvent through diverse thermodynamic and hybrid Machine learning approaches

The pharmaceutical industry is increasingly drawn to the research of innovative drug delivery systems through the use of supercritical CO2 (scCO2)-based techniques. Measuring the solubility of drugs in scCO2 at varying conditions is a crucial parameter in this context. In this research, the supercritical solubility of two pharmaceutical ingredients, namely Febuxostat and Chlorpromazine, has been assessed theoretically using various thermodynamic approaches, including PR, SRK, UNIQUAC, and Wilson models. Additionally, hybrid machine learning models of PO-GPR, and PO-KNN were applied to anticipate the supercritical solubility of these medicines. Verification of the accuracy of each model for each pharmaceutical substance is conducted against previously reported experimental solubility data. In the comparison between the SRK and PR models, it is observed that the SRK model displays greater precision in correlating the solubility of both drugs. It consistently achieves a mean Radj value of 0.995 across all cases and mean AARD% values of 14.47 and 9.30 for Febuxostat and Chlorpromazine, respectively. Furthermore, the findings indicate that the UNIQUAC model surpasses the Wilson model in precisely representing the solubility of both medicines. It consistently achieves a mean Radj value higher than 0.985 across both cases and mean AARD% values of 11.39 and 7.08 for Febuxostat and Chlorpromazine, respectively. Additionally, the performance of both hybrid machine learning models proved to be excellent in anticipating the supercritical solubility of both compounds.

Anhysteretic strains in ferroelectric ceramics under electromechanical loading

This study investigates anhysteretic strains in PZT ceramics. The anhysteretic curves are associated with a stable balanced state of polarization in the domain structure, excluding dissipative effects related to mechanisms such as domain wall pinning. Anhysteretic measurements are representative of an -ideal- scenario in which the material would undergo no energy loss due to dissipative processes, focusing on the stable and reversible aspects of the domain configuration. The different methodologies employed to measure deformations under electromechanical loading are presented, leading to the introduction of digital image correlation (DIC) as the chosen technique, recognized for its ability to capture detailed information on transverse and longitudinal strain. The article then describes a procedure developed to obtain anhysteretic strain and anhysteretic polarisation for different levels of compressive loadings. The subsequent presentation of the results of the transverse and longitudinal strain analyses provides valuable insights into the reversible and irreversible behavior of the material. They can be used as a basis for the thermodynamical modelling approaches grounded on separating reversible and irreversible contributions or as a validation of existing models describing anhysteretic behavior. The compressive stress affects both the shape of hysteretic and anhysteretic curves. The anhysteretic curve represents a stable equilibrium in the domain structure. Compressive stress reduces strain by affecting the pinning of domain walls. These points justify the interest in studying the effect of compressive stress on the anhysteretic behavior of ferroelectrics.

A Systems Biology Analysis of Chronic Lymphocytic Leukemia

Whole-genome sequencing has revealed that TP53, NOTCH1, ATM, SF3B1, BIRC3, ABL, NXF1, BCR, and ZAP70 are often mutated in CLL, but not consistently across all CLL patients. This paper employs a statistical thermodynamics approach in combination with the systems biology of the CLL protein–protein interaction networks to identify the most significant participant proteins in the cancerous transformation. Betti number (a topology of complexity) estimates highlight a protein hierarchy, primarily in the Wnt pathway known for aberrant CLL activation. These individually identified proteins suggest a network-targeted strategy over single-target drug development. The findings advocate for a multi-target inhibition approach, limited to several key proteins to minimize side effects, thereby providing a foundation for designing therapies. This study emphasizes a shift towards a comprehensive, multi-scale analysis to enhance personalized treatment strategies for CLL, which could be experimentally validated using siRNA or small-molecule inhibitors. The result is not just the identification of these proteins but their rank-order, offering a potent signal amplification in the context of the 20,000 proteins produced by the human body, thus providing a strategic basis for therapeutic intervention in CLL, underscoring the necessity for a more holistic, cellular, chromosomal, and genome-wide study to develop tailored treatments for CLL patients.