Energy Minimization Research Articles

Effect of TX-100 on solubilizing power of CTAB and CPC for H Acid: An experimental and computational analysis

The present research work investigates the solubility of an anionic dye 8-amino-1-naphthol-3,6-disulfonic acid (H Acid) within the micellar mediaof two cationic surfactants cetylpyridinium chloride (CPC) and cetyltrimethylammonium bromide (CTAB) as well as in the mixed micellar mediaof each cationic surfactant with Triton X-100 (TX-100). The data from differential absorption spectroscopy across a concentration range spanning from pre-micellar to post-micellar regions was used to determine the degree of solubilization by calculating the partition coefficient (Kx), binding constant (Kb) and Gibbs free energy associated with the relevant processes. Electrical conductivity of each cationic surfactant in the presence of H Acid was recorded in aqueous media and used to determine the CMC and subsequent thermodynamic parameters including entropy (ΔSm), enthalpy (ΔHm) and Gibbs free energy change (ΔGm) associated with the process of micellization. The computational analysis was carried out with GAUSSIAN 09 using a 6-311G + basis set with a DFT/ B3LYP hybrid approach and each set of energy minimization was executed to perform frequency calculations for Frontier molecular orbital analysis and to evaluate absorption spectra. Moreover, the molecular electrostatic potential surfaces (MESP) were also computed to find their suitable hydrophobic and hydrophilic interactions.

Friston, Free Energy, and Psychoanalytic Psychotherapy.

This paper outlines the ways in which Karl Friston's work illuminates the everyday practice of psychotherapists. These include (a) how the strategic ambiguity of the therapist's stance brings, via 'transference', clients' priors to light; (b) how the unstructured and negative capability of the therapy session reduces the salience of priors, enabling new top-down models to be forged; (c) how fostering self-reflection provides an additional step in the free energy minimization hierarchy; and (d) how Friston and Frith's 'duets for one' can be conceptualized as a relational zone in which collaborative free energy minimization takes place without sacrificing complexity.

A Weierstrass Representation Formula for Discrete Harmonic Surfaces

A discrete harmonic surface is a trivalent graph which satisfies the balancing condition in the 3-dimensional Euclidean space and achieves energy minimizing under local deformations. Given a topological trivalent graph, a holomorphic function, and an associated discrete holomorphic quadratic form, a version of the Weierstrass representation formula for discrete harmonic surfaces in the 3-dimensional Euclidean space is proposed. By using the formula, a smooth converging sequence of discrete harmonic surfaces is constructed, and its limit is a classical minimal surface defined with the same holomorphic data. As an application, we have a discrete approximation of the Enneper surface.

Discrete Laplacian on Graphs, Dirichlet Problem, and Minimization of Energy


 
 
 This report is primarily interested in discrete Laplacian on graphs and Dirichlet prob- lem. We investigate two cases of graphs, their Dirichlet problems, and the method of finding solutions to such problems by minimization of their corresponding energy functionals. In the case of an infinite, locally-finite, undirected, simple graph, we find that the minimiza- tion of its energy functional yields a solution to its Dirichlet or boundary-value problem. In the case of finite, directed, locally-finite decision tree, we propose a type of such tree specified by a chosen vertex with no predecessors and by a chosen boundary set of vertices that have no successors. We then further consider a special case of such construction where all the paths of the tree terminate at the same level. We find that the minimization of such special case’s energy functional yields a solution to its Dirichlet problem only when some additional conditions on and close to the boundary (level of termination) are met.
 
 

Optimally localized single-band Wannier functions for two-dimensional Chern insulators

The construction of optimally localized Wannier functions (and Wannier functions in general) for a Chern insulator has been considered to be impossible owing to the fact that the second moment of such functions is generally infinite. In this article, we propose a solution to this problem in the case of a single band isolated from the rest of the band structure. We accomplish this by drawing an analogy between the minimization of the variance and the minimization of the electrostatic energy of a periodic array of point charges in a smooth neutralizing background. In doing so, we obtain a natural regularization of the diverging variance and this leads to an analytical solution to the minimization problem. We demonstrate our results numerically for a particular model system. Furthermore, we show how the optimally localized Wannier functions provide a natural way of evaluating the electric polarization for a Chern insulator. Published by the American Physical Society 2024

Origin of the Disparity between the Stability of Transmutated Mix-Cation and Mix-Anion Compounds

Transmutation is an efficient approach for material design. For example, ternary compound CuGaSe2 in chalcopyrite structure is a promising material for novel optoelectronic and thermoelectric device applications. It can be considered as formed from the binary host compound ZnSe in zinc-blende structure by cation transmutation (i.e., replacing two Zn atoms by one Cu and one Ga). While cation-transmutated materials are common, anion-transmutated ternary materials are rare, for example, Zn2AsBr (i.e., replacing two Se atoms by one As and one Br) is not reported. The physical origin for this puzzling disparity is unclear. In this work, we employ first-principles calculations to address this issue, and find that the distinct differences in stability between cation-transmutated (mix-cation) and anion-transmutated (mix-anion) compounds originate from their different trends of ionic radii as functions of their ionic state, i.e., for cations, the radius decreases with the increasing ionic state, whereas for anions, the radius increases with the increasing absolute ionic state. Therefore, for mix-cation compounds, the strain energy and Coulomb energy can be simultaneously optimized to make these materials stable. In contrast, for mix-anion systems, minimization of Coulomb energy will increase the strain energy, thus the system becomes unstable or less stable. Thus, the trend of decreasing strain energy and Coulomb energy is consistent in mix-cation compounds, while it is opposite in mix-anion compounds. Furthermore, the study suggests that the stability strategy for mix-anion compounds can be controlled by the ratio of ionic radii r 3/r 1, with a smaller ratio indicating greater stability. Our work, thus, elucidates the intrinsic stability trend of transmutated materials and provides guidelines for the design of novel ternary materials for various device applications.

Constraint free physics-informed machine learning for micromagnetic energy minimization

We introduce a novel method for micromagnetic energy minimization which uses physics-informed neural networks to find a magnetic configuration which minimizes the Gibbs Free energy functional without the need of any constraint optimization framework. The Cayley transform is applied to a neural network to assure that the model output lives on the Lie group of rotation matrices SO(3). For the stray field computation we use the splitting ansatz of Garcia-Cervera and Roma together with a hard constraint extreme learning machine in combination with a Taylor series approximation for very accurate evaluation of the single layer potential which only requires a very coarse discretization of the surface. Further, we present a modeling framework for constructive solid geometry which uses R-functions to exactly satisfy essential boundary conditions arising in the course of stray field computation. This framework can be applied to many other areas of interest. Our method shows promising results on the NIST μMAG Standard Problem #3, and is also applied to compute the demagnetization process of a hard magnetic Nd2Fe14B cube.

Development and performance assessment of a novel multigeneration clean energy system based on biomass-LNG using a dynamic model and supervised learning algorithms

Combining process integration mechanisms with artificial intelligence (AI) can be used as a tool for maximum use of biomass capacity and energy production. This study proposes a continuous multi-generation hybrid energy production system based on biomass-LNG using the carbon capture, utilization, and storage (CCUS) method. In this system, using the Gibbs free energy minimization approach, a process based on the fluidized bed gasifier was designed, which in addition to producing hydrogen and electricity from biomass, also produces liquid CO2 and precipitated calcium carbonate (PCC) from liquid natural gas and limestone for the first time. This process was also examined from thermal (HHV) and thermodynamic (Exergy) standpoints. The simulation of the gasification unit was able to predict the percentage of exhaust gases from the gasifier with errors of RMSE = 3.8 and RMSE = 3.2 for almond shell and rice shell biomass, respectively. Following that, a dataset with more than 14 million records was generated. Then, machine learning methods were employed to investigate and improve the process's simulation characteristics. The evaluation of 15 machine learning algorithms in the construction of the predictive model showed that ANN, Extra Tree Regressor, and Random Forest are the most accurate algorithms in predicting the desired values (such as hydrogen, work, PCC, liquid CO2, exergy, and HHV) with R2 > 0.99. The dataset analysis showed that the current process could produce 130 kg/h of hydrogen, 375 kWh of work, 2600 kg/h of PCC, and 531 kg/h of liquid carbon dioxide on average. As a final step, a WPF desktop application was developed that simplifies the use of ML models so that the impact of changing the variables can easily be calculated.

Modelling beaches morphodynamic by Hadamard sensitivity analysis

The paper presents a morphodynamic model which can be coupled with any wave model capable of producing time/spectral averaged wave quantities. This model based on a wave energy minimization principle highlights the morphodynamic phenomenology, such as the sandbar creation. Such a model can be used in solving engineering optimization problems. It is also developed to illustrate the idea that beach sand transport can be thought as a non-local phenomenon. We used wave calculations from SWAN and XBeach in our model, and we compared the morphodynamic results to LIP and SANDS hydro-morphodynamic benchmark as well as open-sea simulations. Using supplementary mathematical development, we improved the minimization method using the Hadamard derivative.

Chemical profiling and in-silico prediction of bioactive compounds from Wrightia tinctoria R.Br to treat psoriatic arthritis

Psoriatic arthritis (PsA) is an autoimmune-mediated inflammatory skin condition with limited remedies. This study mainly focuses on exploring the therapeutic efficiencies of Wrightia tinctoria R.Br (WT) for the treatment of PsA. Quantification and chemical profiling for the WT leaves were tested using standard in vitro biochemical assays. The ethanol extract of WT has been found to have high amounts of phenolic (24.48±0.03 mg/mL) and flavonoid (29.2±0.16 mg/mL) contents when compared to other solvent fractions. We also conducted a series of in vitro assays, including DPPH, nitric oxide radical scavenging, and protein denaturation inhibition assays, to assess the overall antioxidant and anti-inflammatory capabilities of WT extracts. The GC-MS analysis of WT leaf extract displayed Lup-20(29)-en-3-yl acetate, 24-Norursa-3,12-diene, and 3-O-Methyl-D-fructose as major bioactive compounds. The screened bioactive compounds, via pharmacokinetic and pharmacodynamic analysis, were subjected to density functional theory for energy minimization. Further, the hub targets of PsA were filtered from the Open Target online database to study the drug-target interaction. CD4, CXCL12, KLRD1, MMP9, and SERPINA1 were found to be the primary targets, which have a central role in the disease pathway. Selected disease targets were then docked with the energy-minimized bioactive compounds from WT leaves using PyRx. The results suggest that the ethanolic leaf extract from WT leaves could alter the progression of pathway mediators and effectively manage the PsA.

Crack propagation in anisotropic brittle materials: From a phase-field model to a shape optimization approach

The phase-field method is based on the energy minimization principle which is a geometric method for modeling diffusive cracks that are popularly implemented with irreversibility based on Griffith’s criterion. This method requires a length-scale parameter that smooths the sharp discontinuity, which influences the diffuse band and results in mesh-dependent fracture propagation results. Recently, a novel approach based on the optimization on Riemannian shape spaces has been proposed, where the crack path is realized by techniques from shape optimization. This approach requires the shape derivative, which is derived in a continuous sense and used for a gradient-based algorithm to minimize the energy of the system. In this paper, the novel approach based on shape optimization is presented, followed by an assessment of the predicted crack path in both isotropic and anisotropic brittle material using numerical calculations from a phase-field model.

Effects of residual stress and microstructure on extremely anisotropic grain growth in nanotwinned Cu films

In this study, the thermal stability and microstructural evolutions of nanotwinned copper (NT-Cu) films under thermal cycling are investigated. The microstructures and residual stresses were tuned by the electroplating current density. It was found that the thermal stability of the NT-Cu films decreased with an increase in current density. The texture transition from (111) to (100) suggests that the extremely anisotropic grain growth (EAGG) was driven by the minimization of strain energy. Bending beam technic was employed to measure the residual stress in the NT-Cu films. Large residual stress in the NT-Cu films is also considered a main driving force for the transition to the (100)-oriented texture. Additionally, strain energy, surface/interface energy, grain boundary energy, and twin boundary energy were calculated, and the results supported the experimental results.

Equilibrium Study of Carbon Dioxide Reforming of Methane to Syngas

Fugacity coefficients for the components in the gas mixture are determined using the Soave–Redlich–Kwong (SRK) equation of state. The Gibbs free energy minimization method is employed to determine the equilibrium composition of the components for CO2 reforming of CH4 to syngas. To utilize CO2 efficiently and avoid carbon deposition, CO2 composition in the initial feed should not be greater than 1 (nCH4,0 = 1), and the reaction is preferably operated at atmospheric pressure. Setting nCH4,0:nCO2,0 to 1:1, and increasing nO2,0 in the feed from 0 to 1.0 to adjust the initial composition, results in a decrease in the syngas equilibrium yield, and a increase in both nCO2,e and nH2O,e. The temperature required for complete carbon deposition removal decreased. Considering the effective utilization of CO2 at nCH4,0:nCO2,0 1:1, it is recommended to set nO2,0 in the feed to less than 0.5.

Optimal time-invariant distributed formation tracking for second-order multi-agent systems

This paper addresses the optimal time-invariant formation tracking problem with the aim of providing a distributed solution for multi-agent systems with second-order integrator dynamics. In the literature, most of the results related to multi-agent formation tracking do not consider energy issues while investigating distributed feedback control laws. In order to account for this crucial design aspect, we contribute by formalizing and proposing a solution to an optimization problem that encapsulates trajectory tracking, distance-based formation control and input energy minimization, through a specific and key choice of potential functions in the optimization cost. To this end, we show how to compute the inverse dynamics in a centralized fashion by means of the Projector-Operator-based Newton’s method for Trajectory Optimization (PRONTO) and, more importantly, we exploit such an offline solution as a general reference to devise a stabilizing online distributed control law. Finally, numerical examples involving a cubic formation following a chicane-like path in the 3D space are provided to validate the proposed control strategies.

Folding of the cerebellar cortex is clade-specific in form but universal in degree.

Like the cerebralcortex, the surface of the cerebellum is repeatedly folded. Unlike the cerebralcortex, however, cerebellar folds are much thinner and more numerous; repeatthemselves largely along a single direction, forming accordion-like folds transverseto the mid-sagittal plane; and occur in all but the smallest cerebella. We haveshown previously that while the location of folds in mammalian cerebral cortex isclade-specific, the overall degree of folding strictly follows a universalpower law relating cortical thickness and the exposed and total surface areas predictedfrom the minimization of the effective free energy of an expanding, self-avoidingsurface of a certain thickness. Here we show that this scaling law extends tothe folding of the mid-sagittal sections of the cerebellum of 53 speciesbelonging to six mammalian clades. Simultaneously, we show that each clade hasa previously unsuspected distinctive spatial pattern of folding evident at themid-sagittal surface of the cerebellum. We note, however, that the mammaliancerebellum folds as a multi-fractal object, because of the difference betweenthe outside-in development of the cerebellar cortex around a preexisting coreof already connected white matter, compared to the inside-out development ofthe cerebral cortex with a white matter volume that develops as the cerebralcortex itself gains neurons. We conclude that repeated folding, one of the mostrecognizable features of biology, can arise simply from the interplay betweenthe universal applicability of the physics of self-organization and biological,phylogenetical clade-specific contingency, without the need for invokingselective pressures in evolution.

Delay and Energy Minimization for Cooperative NOMA-MEC Networks With SWIPT Aided by RIS

Delay and Energy Minimization for Cooperative NOMA-MEC Networks With SWIPT Aided by RIS

Revisiting the Young’s model for ferrofluid droplets: Magnetowetting or magneto-dewetting?

Magnetic field-mediated wetting of ferrofluid droplets has emerged to be of fundamental importance because of its plethora of applications ranging from chemical and biomolecular analysis to soft robotics and medical imaging. However, while extensive studies continue to be reported on the underlying experimental facets, a fundamental theoretical depiction of the observed contact angle variation with the applied magnetic field remains grossly elusive, as attributable to a complex dependence of the induced magnetization on the droplet’s intrinsic magnetic properties. Circumventing these constraints, here we put forward a first-principle analytical model that delineates the variation in the contact angle as a function of an applied magnetic field on a sessile ferrofluid droplet, by appealing to energy minimization principles. One key feature of our analysis is the consideration of the local magnetization as a function of the magnetic field itself, resulting in a new contribution to the interfacial energy by virtue of normal traction at the droplet's contact with its non-magnetic surroundings. This theory is supported by experiments identified in prior research to elucidate the fundamental physics of relevance. Our results highlight the substantial influence of the saturation magnetization and the initial susceptibility of the ferrofluid on the resulting contact angle alterations, as well as possible non-trivial routes of highly selective and precise enhancement or attenuation in the extent of wetting. These findings are likely to be of fundamental importance towards establishing the design foundations of portable magnetic resonance imaging devices, micromixers, and microreactors, magnetically-manipulated automatic control of soft fluidic matters, among others.

Optimal Design of LCC Resonant Converter With Phase Shift Control for Wide Input/Output Voltage Ranges in Fuel Cell System

This paper proposes an optimal design of an LCC resonant converter with a phase shift control for a fuel cell system which has wide input and output voltage ranges. The proposed optimal design focuses on the circulating energy minimization by adjusting the transformer turns ratio according to the maximum gain of resonant tank. This makes the root mean square (RMS) value of resonant current and turn-off current stationary even though the resonant tank change. Thus, designers can select resonant tank optimized for the converter specifications without considering the conduction and switching losses. By the proposed optimal design, the efficiency degradation at worst case, which is a significant issue of the fuel cell system with wide output voltage range, can be minimized. In addition, for the fuel cell converter with wide input voltage range, a phase shift control which operates the full-bridge inverter with a constant effective duty cycle according to the fuel cell voltage is proposed. This control scheme improves the light-load efficiency without deteriorating the rated-load efficiency by reducing the circulating current and switching frequency. The validity of the proposed works is confirmed by experimental results of the 30kW LCC resonant converter.

A MOLECULAR MODELLING APPROACH FOR STRUCTURE-BASED VIRTUAL SCREENING AND IDENTIFICATION OF NOVEL ISOXAZOLES AS POTENTIAL ANTIMICROBIAL AGENTS AGAINST S. AUREUS

Objective: Universal use of antibacterial agents and swift development of resistance by the microorganisms pose a major threat to public health. Hence, there is a pressing need to develop novel antimicrobials. Isoxazole derivatives exhibiting versatile biological activities have been widely used as important scaffolds in the field of drug designing. Methods: Twenty isoxazole derivatives were virtually screened by means of the molecular docking approach in order to identify potential antimicrobials against the most common disease-causing bacteria, S. aureus. In silico studies were done to detect the selectivity of the novel isoxazole derivatives for the selected bacterial protein targets using ‘Glide’. In silico docking was carried out on few essential enzymes of S. aureus; Dihydrofolate reductase (DHFR), DNA gyrase, Dihydropteroate Synthetase (DHPS), Pyuvate kinase (PK). The compounds were subjected to energy minimization, followed by optimization and minimization of protein and generation of 3D grid at its active site. The ligands were subjected to molecular docking the Standard Precision and Extra Precision modes. Results: Docking of the compounds with Pyruvate Kinase and dihydrofolate reductase are quite encouraging.2C (4-hydroxy) and 2D (4-hydroxy) analogues gavea G Score of-8.33 and-8.64 with DHFR and Pyruvate Kinase respectively. However, the dock scores for the other target proteins indicate that the scaffolds have not bound with those bacterial targets. Moreover, ADME studies indicate that the derivatives do not show any violations in the rules for the requirements of orally active drugs. Conclusion: Study suggests that the derivatives 2C (4-hydroxy) and 2D(2-hydroxy) specifically bind to the active site of PK and DHFR. In silico ADME studies predicted the compounds to be “drug-like.” Hence the hydroxy derivatives may be considered as leads for further structural modifications to arrive at potential anti-bacterial agents.

Creation of Multi-Principal Element Alloy NiCoCr Nanostructures via Nanosecond Laser-Induced Dewetting.

The multi-principal element alloynanoparticles (MPEA NPs), a new class of nanomaterials, present a highly rewarding opportunity to explore new or vastly different functional properties than the traditional mono/bi/multimetallic nanostructures due to their unique characteristics of atomic-level homogeneous mixing of constituent elements in the nanoconfinements. Here, the successful creation of NiCoCr nanoparticles, a well-known MPEA system is reported, using ultrafast nanosecond laser-induced dewetting of alloy thin films. Nanoparticle formation occurs by spontaneously breaking the energetically unstable thin films in a melt state under laser-induced hydrodynamic instability and subsequently accumulating in a droplet shape via surface energy minimization. While NiCoCr alloy shows a stark contrast in physical properties compared to individual metallic constituents, i.e., Ni, Co, and Cr, yet the transient nature of the laser-driven process facilitates a homogeneous distribution of the constituents (Ni, Co, and Cr) in the nanoparticles. Using high-resolution chemical analysis and scanning nanodiffraction, the environmental stability and grain arrangement in the nanoparticles are further investigated. Thermal transport simulations reveal that the ultrashort (≈100ns) melt-state lifetime of NiCoCr during the dewetting event helps retain the constituent elements in a single-phase solid solution with homogenous distribution and opens the pathway to create the unique MPEA nanoparticles with laser-induced dewetting process.