Potential Energy Research Articles

Nuclear quantum effects in gas-phase ethylene glycol.

Path integral molecular simulations are used to explore the nuclear quantum effects (NQEs) on the structure, dihedral landscape and infrared spectrum of ethylene glycol. The simulations are carried out on a new reaction surface Hamiltonian-based model potential energy surface, with special focus on the role of the OCCO and HOCC dihedrals. In contrast with classical simulations, we analyse how the intramolecular interactions between the OH groups change due to zero-point effects as well as temperature. These are found to be weak. The NQEs on the free energy profile along the OCCO dihedral are analysed, where notable effects are seen at low temperatures and found to be correlated with the radii of gyration of the atoms. Finally, the power spectrum of the molecule from path integral simulations is compared with the experimental infrared spectrum, yielding a good agreement of band positions.

Computer-Based Experiment for the Motion of Spring Oscillator on a Linear Air Track Using Ultrasonic Sensor

In the present paper, an affordable innovative physical experimental equipment consisting of an upper computer, an ultrasonic sensor module, and an Arduino microcontroller has been designed. The relationship between the position of the slider fixed on two springs and time is measured by using the ultrasonic sensor module. A system for slider motion data and image acquisition is constructed by using the LabVIEW interface of Arduino UNO R3. The purpose of this experiment is to demonstrate and interpret the propagation of waves represented by harmonic motion. The spring oscillator system including a slider and two springs is measured and recorded, and the motion can be realized using curve fitting to the wave equation in Sigmaplot. The vibration periods obtained from experimental measurements and curve fitting of the wave equation are 1.130 s and 1.165 s, respectively. The experimental data are in good agreement with the theoretical model. The experimental measurement results show that the maximum kinetic energy is 0.0792 J, the maximum potential energy is 0.0795 J, and the total energy at the position of half the amplitude is 0.0791 J. The results verify the mechanical energy conservation of spring oscillator system in a short time. This self-made instrument has improved the visualization and the automation level of the corresponding experiments.

Quantum Extreme Learning of molecular potential energy surfaces and force fields

Abstract Quantum machine learning algorithms are expected to play a pivotal role in quantum chemistry simulations in the immediate future. One of such key applications is the training of a quantum neural network to learn the potential energy surface and force field of molecular systems. We address this task by using the quantum extreme learning machine paradigm. This particular supervised learning routine allows for a resource efficient training, consisting of a simple linear regression performed on a classical computer. We have tested a setup that can be used to study molecules of any dimension and optimized for immediate use on NISQ devices with a limited number of native gates. We have applied this setup to three case studies: lithium hydride, water, and formamide, carrying out both noiseless simulations and actual implementation on IBM quantum hardware. Compared to other supervised learning routines, the proposed setup requires minimal quantum resources, making it feasible for direct implementation on quantum platforms, while still achieving a high level of predictive accuracy compared to simulations. Our encouraging results pave the way towards the future application to more complex molecules, being the proposed setup scalable.

DFT/MM Simulations for Cycloreversion Reaction of Cyclobutane Pyrimidine Dimer with Deprotonated and Protonated E283.

DNA photolyase targets the primary ultraviolet (UV)-induced DNA lesion─cyclobutane pyrimidine dimer (CPD), attaches to it, and catalyzes its dissociation. The catalytic mechanism of DNA photolyase and the role of the conserved residue E283 remain subjects of debate. This study employs two-dimensional potential energy surface maps and minimum free energy paths calculated at the ωB97XD/6-31G/MM level to elucidate these mechanisms. Results suggest that the catalytic process follows a sequential, stepwise reaction in which the C5-C5 and C6-C6 bonds are cleaved in order, facilitated by a protonated E283. Activation free energies for these cleavages are calculated at 4.4 and 4.2 kcal·mol-1, respectively. Protonation of E283 reduces electrostatic repulsion with CPD and forms dual hydrogen bonds with it and provides better solvation, stabilizing the CPD radical anion, particularly during intermediate state. This stabilization renders the initial splitting step exergonic, slows reverse reactions of the C5-C5 bond cleavage and electron transfer, and ensures a high quantum yield. Furthermore, the protonation state of E283 significantly affects the type of bond cleavage. Other residues in the active site were also investigated for their roles in the mechanism.

Effect of ceria morphology on hydrogen production via methane steam reforming for membrane reformer

AbstractHydrogen is a potential energy carrier in comparison to conventional fuels due to its high energy content. Methane is an attractive source for ‘on‐site’ production of hydrogen by using membrane reformer due to its low cost. However, such reformers are not well studied and high temperature operation of steam methane reforming (SMR) makes the integration with membrane separation difficult. Further, the main product of SMR is CO and H2 in which CO has an inhibition effect on the membrane separation process. Therefore, it is vital to synthesize a low temperature and low CO selective catalyst for a suitable integration with membrane reformer. Nickel‐based catalyst is widely used for SMR due to its low cost and high catalytic activity. CeO2 is a favoured support as it mobilizes the lattice oxygen and reduces the coke formation and CO selectivity. Though several studies are reported on CeO2 based support, the effect of CeO2 surface morphology is not studied for SMR. In the current work, Ni/CeO2 of different shapes (nanocube and nanorod) are synthesized. The complete characterization of the support was performed. The effect of support shape, calcination temperature, and reduction temperature on SMR activity is found at different operating temperatures. For each condition conversion, CO, CO2 selectivity, and hydrogen yield are calculated. The results show the CeO2 morphology has a considerable effect on conversion, CO selectivity, and hydrogen yield. It is found that ceria nanocube calcined at 550°C provides better performance at high temperature.

DFT/MM Simulations for Cycloreversion Reaction of Cyclobutane Pyrimidine Dimer with Deprotonated and Protonated E283.

DNA photolyase targets the primary ultraviolet (UV)-induced DNA lesion─cyclobutane pyrimidine dimer (CPD), attaches to it, and catalyzes its dissociation. The catalytic mechanism of DNA photolyase and the role of the conserved residue E283 remain subjects of debate. This study employs two-dimensional potential energy surface maps and minimum free energy paths calculated at the ωB97XD/6-31G/MM level to elucidate these mechanisms. Results suggest that the catalytic process follows a sequential, stepwise reaction in which the C5-C5 and C6-C6 bonds are cleaved in order, facilitated by a protonated E283. Activation free energies for these cleavages are calculated at 4.4 and 4.2 kcal·mol-1, respectively. Protonation of E283 reduces electrostatic repulsion with CPD and forms dual hydrogen bonds with it and provides better solvation, stabilizing the CPD radical anion, particularly during intermediate state. This stabilization renders the initial splitting step exergonic, slows reverse reactions of the C5-C5 bond cleavage and electron transfer, and ensures a high quantum yield. Furthermore, the protonation state of E283 significantly affects the type of bond cleavage. Other residues in the active site were also investigated for their roles in the mechanism.

Theoretical Study of Infrared and Ultraviolet Spectroscopy in SiP Interstellar Molecules

Abstract Insufficient theoretical investigation is being conducted on the spectroscopic characteristics within the infrared wavelength range of SiP, an identified interstellar molecule. Using the ic-MRCI method, potential energy functions and dipole moment functions for the ground state (${X}^2\Pi $) and low excited states (${{\rm{A}}}^2{\Sigma }^ + $) of the SiP molecule were calculated. Based on experimental spectroscopy data, least squares fitting was used for the potential energy functions of the ${X}^2\Pi $ and ${{\rm{A}}}^2{\Sigma }^ + $ states. By combining these potential energy and dipole moment functions, the one-dimensional Schrödinger equation was solved to obtain the vibronic energy levels and Einstein A coefficients for the electronic states. Partition functions of the SiP molecule from 0.1 K to 3000 K and the radiative properties of ${X}^2\Pi \leftrightarrow {X}^2\Pi $ and ${X}^{\rm{2}}\Pi \leftrightarrow {{\rm{A}}}^2{\Sigma }^ + $ were derived. Infrared spectroscopy of the ${X}^2\Pi $ state and ultraviolet spectroscopy of the ${X}^{\rm{2}}\Pi \leftrightarrow {{\rm{A}}}^2{\Sigma }^ + $ transition at 100 K, a temperature crucial for astronomical research, were calculated. Results indicate that the spectral line intensity of the ${X}^{\rm{2}}\Pi \leftrightarrow {{\rm{A}}}^2{\Sigma }^ + $ transition is greater, making it more suitable for astronomical observation. The obtained computational results in this paper yield spectroscopic parameters for the characterization of the interstellar molecule SiP, furnishing theoretical underpinnings for subsequent experimental observations.

OBIWAN: An Element-Wise Scalable Feed-Forward Neural Network Potential.

Estimating the potential energy of a molecular system at a quantum level of theory is a task of paramount importance in computational chemistry. The often employed density functional theory approach allows one to accomplish this task, yet most often at significant computational costs. This prompted the community to develop so-called machine learning potentials to achieve near-quantum accuracy at molecular mechanics computational cost. In this paper, we introduce OBIWAN, a feed-forward neural network that bears some relevant structural properties that also led to the definition of a new kind of general-purpose neural network layer. Its featurization process scales efficiently with newly added atomic species. This allows one to seamlessly add new atom types without requiring to change the topology of the network. Also, this allows one to train on new data sets leveraging a previously trained OBIWAN, hence converging very quickly. This avoids training from scratch and renders the approach more compliant with a green computing perspective.

Construction of macromolecular structure model of Luling coal and study on the dynamic mechanism of micro-wetting process

The physicochemical structure and energy composition of coal macromolecules are the major factors affecting coal wettability. This study thus employed 13C NMR, FTIR, and XPS to determine the chemical structure of coal in the No. 10 coal seam of the Luling coal mine and gain insights into the molecular mechanisms of coal wetting. The results showed that the molecular formula of the Luling 10 model was C290H223O25N5S. Through molecular dynamics simulation, upon the stable adsorption of sodium dodecyl sulfate (SDS) on the coal surface, both the mobility of water molecules and the water molecule content in the interfacial adsorption layer increased. After SDS was added, except for the hydrogen bond energy, the increase rate of each potential energy increased, and van der Waals energy and bond length energy changed the most. The reason for the decrease of hydrogen bond energy is that more atoms in coal macromolecules form hydrogen bonds with polar water molecules. The increase of SDS promoted the significant changes of bond length energy, bond angle energy and van der Waals force of coal, thus increasing the wettability of coal. Taken together, our findings provide important insights into the molecular mechanisms through which surfactants improve chemical wetting.

Tribological behavior of graphene/ h-BN vdW heterostructures: the role of defects at the BN layer.

Molecular dynamics (MD) simulations and first principles calculations were performed to study the tribological behavior of graphene/h-BN (G/h-BN) heterostructures with vacancy and (Stone-Wales) SW defect under uniform normal load, revealing the mechanism of the effect of defect types on friction, and discussing the coupling effect of temperature and interfacial defects on the tribological behavior of G/h-BN heterostructures. Under the normal force of 0.2nN/atom, the friction force of the four systems is 0.0057, 0.0096, 0.0077, and 0.26 nN, respectively. The friction force of SW defect heterostructure is 45 times that of perfect interface heterostructure. The influence of defect type on friction force is SW>SV>DV. By observing the dynamic change of the Z-direction coordinate position of the sliding layer atoms, the slip potential energy curves and the evolution law of the moiré pattern, the relationship between the structural morphology and the energy change of different defective heterostructures and the frictional behavior was investigated comprehensively and intuitively for the first time. From the perspective of atomic strain, the deformation of heterostructures at the atomic level was quantified. The results showed that at 300 K and 0 K, the maximum strain of atoms in the sliding layer was 11.25% and 9.85%, respectively. The thermal perturbation mainly occurs in the out-of-plane direction, which in turn affects the friction. Through density functional theory, it is found that under uniform load, it is difficult to form bonds between the graphene sliding layer and the substrate layer when the defects are in the h-BN substrate layer, which has less influence on the friction of the system, thus making the defective heterostructures also remain superlubricity state. These results provide a new understanding of the interfacial friction of G/h-BN defective heterostructure.

Analysis of Energy Potential of Switchgrass Biomass

In this research, the energy potential of switchgrass (SG) was analyzed to find promising directions for producing bioenergy from this biomass. The first direction is determining the thermal energy of bioethanol extracted from SG biomass after its pretreatment, enzymatic hydrolysis (saccharification), and fermentation of the resulting glucose. It was established that after a two-stage pretreatment of 1 ton of SG with dilute solutions of nitric acid and alkali, the largest amount of bioethanol can be extracted with an energy potential of 4.9 GJ. It is also shown that by the utilization of solid and liquid waste, the production cost of bioethanol can be reduced. On the other hand, the direct combustion of 1 ton of the initial SG biomass used as a solid biofuel provides an increased amount of thermal energy of 18.3 GJ, which is 3.7 times higher than the energy potential of the resulting bioethanol extracted from 1 ton of this biomass. Thus, if the ultimate goal is to obtain the maximum energy amount, then another direction for obtaining bioenergy from biomass should be implemented, namely, direct combustion, preferably after pelletizing. Studies have shown that fuel characteristics of SG pellets such as the gross thermal energy and density of thermal energy are lower than those of wood pellets, but they can be improved if the SG biomass is densified into pellets together with binders made from polymer waste.

Analysis of Energy Potential of Switchgrass Biomass

In this research, the energy potential of switchgrass (SG) was analyzed to find promising directions for producing bioenergy from this biomass. The first direction is determining the thermal energy of bioethanol extracted from SG biomass after its pretreatment, enzymatic hydrolysis (saccharification), and fermentation of the resulting glucose. It was established that after a two-stage pretreatment of 1 ton of SG with dilute solutions of nitric acid and alkali, the largest amount of bioethanol can be extracted with an energy potential of 4.9 GJ. It is also shown that by the utilization of solid and liquid waste, the production cost of bioethanol can be reduced. On the other hand, the direct combustion of 1 ton of the initial SG biomass used as a solid biofuel provides an increased amount of thermal energy of 18.3 GJ, which is 3.7 times higher than the energy potential of the resulting bioethanol extracted from 1 ton of this biomass. Thus, if the ultimate goal is to obtain the maximum energy amount, then another direction for obtaining bioenergy from biomass should be implemented, namely, direct combustion, preferably after pelletizing. Studies have shown that fuel characteristics of SG pellets such as the gross thermal energy and density of thermal energy are lower than those of wood pellets, but they can be improved if the SG biomass is densified into pellets together with binders made from polymer waste.

Optimizing Energy Efficiency and Environmental Sustainability in Gas Distribution Station: A Comprehensive Analysis and Technological Solutions

It is important to address the world‘s energy crisis, increasing energy demand and changing climate by finding ways to recover unused energy and minimise primary and secondary energy use and emissions. The natural gas sector, which consists of the transmission network and gas distribution stations, is an important part of the global and Lithuanian energy sector. However, due to the operating principle of gas pressure regulators, the energy potential of high-pressure gas is not efficiently utilized in gas distribution stations. As a result, natural gas boilers are used for gas preheating, and gas distribution stations cause additional environmental pollution. This study aims to find ways to optimise the efficiency of gas distribution stations and reduce their negative environmental impact by identifying areas where energy is wasted and proposing alternative technological solutions: turbine expander (as an alternative for gas pressure regulator), ground heat pumps, solar collectors and photovoltaic solar cells (as gas preheating alternatives). The best alternative technological solution for the gas distribution station is evaluated based on energy efficiency, economic viability, and environmental impact (3E criteria).

Optimizing Energy Efficiency and Environmental Sustainability in Gas Distribution Station: A Comprehensive Analysis and Technological Solutions

It is important to address the world‘s energy crisis, increasing energy demand and changing climate by finding ways to recover unused energy and minimise primary and secondary energy use and emissions. The natural gas sector, which consists of the transmission network and gas distribution stations, is an important part of the global and Lithuanian energy sector. However, due to the operating principle of gas pressure regulators, the energy potential of high-pressure gas is not efficiently utilized in gas distribution stations. As a result, natural gas boilers are used for gas preheating, and gas distribution stations cause additional environmental pollution. This study aims to find ways to optimise the efficiency of gas distribution stations and reduce their negative environmental impact by identifying areas where energy is wasted and proposing alternative technological solutions: turbine expander (as an alternative for gas pressure regulator), ground heat pumps, solar collectors and photovoltaic solar cells (as gas preheating alternatives). The best alternative technological solution for the gas distribution station is evaluated based on energy efficiency, economic viability, and environmental impact (3E criteria).

Accelerating structure search using atomistic graph-based classifiers.

We introduce an atomistic classifier based on a combination of spectral graph theory and a Voronoi tessellation method. This classifier allows for the discrimination between structures from different minima of a potential energy surface, making it a useful tool for sorting through large datasets of atomic systems. We incorporate the classifier as a filtering method in the Global Optimization with First-principles Energy Expressions (GOFEE) algorithm. Here, it is used to filter out structures from exploited regions of the potential energy landscape, whereby the risk of stagnation during the searches is lowered. We demonstrate the usefulness of the classifier by solving the global optimization problem of two-dimensional pyroxene, three-dimensional olivine, Au12, and Lennard-Jones LJ55 and LJ75 nanoparticles.

A new low-carbon project scheduling problem with renewable and traditional energy: A comprehensive analysis and its solution

Employing multi-energy complementarity in project energy supply proves to be an efficient strategy for accomplishing low-carbon project scheduling. However, current project scheduling problems primarily concentrate on traditional single-energy models. They optimize schedules to reduce energy emissions but often neglect the potential of renewable energy. This paper integrates project scheduling and renewable energy as interrelated aspects. Based on a renewable energy supply model grounded in the generation characteristics of renewable energy sources, a model for MC-MRCPSPM (multi-mode resource-constrained project scheduling problem with multiple complementary energies in the manufacturing context) is constructed and a memetic algorithm is employed for its resolution. The research findings conclusively demonstrate that using renewable energy as a power source during project execution leads to an average reduction of approximately 58.8% in carbon emissions, with a justifiable 14.73% increase in energy costs. Employing a multi-energy complementarity approach in project scheduling effectively reduces carbon emissions while maintaining reasonable energy costs and offers project managers greater decision-making flexibility.

Management of sustainable investments: A comprehensive financial evaluation of wind energy facilities in Kastamonu

The rich renewable sources of nature, such as water, wind, solar, geothermal, and biomass, are converted into energy, revitalized into the economy without causing pollution, and ensure sustainability in energy management. Wind power plants have been among the most preferred renewable energy sources in recent years since they are harmless to the environment and easy to install in places with consistent and sufficient wind speed. This study focuses on conducting a feasibility analysis of a Wind Power Plant (WPP) in Kastamonu, a region known for its persistent wind patterns. The analysis aims to contribute to the existing literature by examining the potential of a WPP investment project within the region. Utilizing wind speed data collected from 23 observation stations for six years, starting from 2017 to 2022, a total of 1,200,600 h, a statistical evaluation method known as the Weibull probability density function is employed to indicate the wind energy potential. The parameters are determined by applying the maximum likelihood method. The findings indicate that it is feasible to establish Wind Energy Power Plants in specific locations, namely İnebolu, İnebolu Kar, Küre, and Tosya stations. The cost estimation for establishing a 10 MW power plant with three different turbine powers across these four locations ranges from 10 million USD to 20,8 million USD. Furthermore, the analysis indicates that the net profit for producing 1 kW of electrical energy falls from 9.39 to 50.65 USD. The projected payback period for the investment ranges from 2 to 25 years, depending on factors such as the exact site of the facility and the size of the turbines. Some investments are more feasible than others, with economic viability and potential return on investment varying significantly within the specified locations.

Theoretical study of infrared and ultraviolet spectroscopy in SiP interstellar molecules

ABSTRACT Insufficient theoretical investigation is being conducted on the spectroscopic characteristics within the infrared wavelength range of SiP, an identified interstellar molecule. Using the ic-MRCI method, potential energy functions and dipole moment functions for the ground state (${X^2}\Pi $) and low excited states (${{\rm{A}}^2}{\Sigma ^ + }$) of the SiP molecule were calculated. Based on experimental spectroscopy data, least squares fitting was used for the potential energy functions of the ${X^2}\Pi $ and ${{\rm{A}}^2}{\Sigma ^ + }$ states. By combining these potential energy and dipole moment functions, the one-dimensional Schrödinger equation was solved to obtain the vibronic energy levels and Einstein A coefficients for the electronic states. Partition functions of the SiP molecule from 0.1 to 3000 K and the radiative properties of ${X^2}\Pi \leftrightarrow {X^2}\Pi $ and ${X^{\rm{2}}}\Pi \leftrightarrow {{\rm{A}}^2}{\Sigma ^ + }$ were derived. Infrared spectroscopy of the ${X^2}\Pi $ state and ultraviolet spectroscopy of the ${X^{\rm{2}}}\Pi \leftrightarrow {{\rm{A}}^2}{\Sigma ^ + }$ transition at 100 K, a temperature crucial for astronomical research, were calculated. Results indicate that the spectral-line intensity of the ${X^{\rm{2}}}\Pi \leftrightarrow {{\rm{A}}^2}{\Sigma ^ + }$ transition is greater, making it more suitable for astronomical observation. The obtained computational results in this paper yield spectroscopic parameters for the characterization of the interstellar molecule SiP, furnishing theoretical underpinnings for subsequent experimental observations.

Removal mechanism of double-diamond-abrasive-grinding GaN single crystals under graphene lubrication

Gallium nitride (GaN) is an advanced material used to manufacture chip wafers and high-power devices. Recently, grinding processing, has been applied in the fields of machinery manufacturing, aerospace, and medical devices as a highly efficient machining method. An in-depth understanding of the material removal mechanism produced by the double-grinding processes can provide guidance for the design of GaN-based nanodevices. Herein, molecular dynamics simulations were used to investigate the mechanism of removal of double-diamond-abrasive-grinding gallium nitride crystals under graphene lubrication, and a systematic study was performed to investigate the involved surface morphology, grinding force, stress distribution, and subsurface damage behavior. Results reveal that graphene can substantially enhance the wear resistance of GaN substrates by reducing surface wear, atomic displacement., potential energy, and subsurface damage, thereby playing a protective role toward the substrate. As the grinding depth increases, the grinding force and subsurface damage depth also increase. Furthermore, the effects of abrasive grain spacing on subsurface damage depth and phase change atoms were analyzed and found to have limited influence on material removal efficiency. These results deepen our understanding of material removal and protection mechanisms relative to substrates resulting from double-grinding processes as well as offer valuable insights for the rational design of abrasive wheels.

Experimental Characterization and Phase-Field Damage Modeling of Ductile Fracture in AISI 316L

(1) Modeling and characterization of ductile fracture in metals is still a challenging task in the field of computational mechanics. Experimental testing offers specific responses in the form of crack-mouth (CMOD) and crack-tip (CTOD) opening displacement related to applied force or crack growth. The main aim of this paper is to develop a phase-field-based Finite Element Method (FEM) implementation for modeling of ductile fracture in stainless steel. (2) A Phase-Field Damage Model (PFDM) was coupled with von Mises plasticity and a work-densities-based criterion was employed, with a threshold to propose a new relationship between critical fracture energy and critical total strain value. In addition, the threshold value of potential internal energy—which controls damage evolution—is defined from the critical fracture energy. (3) The material properties of AISI 316L steel are determined by a uniaxial tensile test and the Compact Tension (CT) specimen crack growth test. The PFDM model is validated against the experimental results obtained in the fracture toughness characterization test, with the simulation results being within 8% of the experimental measurements. (4) The novel implementation offers the possibility for better control of the ductile behavior of metallic materials and damage initiation, evolution, and propagation.