Potential Energy Research Articles

Investigation of the Gas-Phase N2+ + CH3CN Reaction at Low Temperatures.

Rate coefficients for ion-polar-molecule reactions between acetonitrile molecules (CH3CN) and nitrogen molecular ions (N2+), which are of importance to the upper atmospheric chemistry of Saturn's moon Titan, were measured for the first time at low translational temperatures. In the experiments, the reaction between sympathetically cooled N2+ ions embedded in laser-cooled Ca+ Coulomb crystals and velocity-selected acetonitrile molecules generated using a wavy Stark velocity filter was studied to determine the reaction rate coefficients. Capture rate coefficients calculated by the Su-Chesnavich approach and by the perturbed rotational state theory considering the rotational state distribution of CH3CN were compared to the experimental rate coefficients. The results indicate that the present reaction is barrierless and that the rate coefficients are consistent with the capture rate coefficients. The potential energy surface of the reaction product CH3CN+ was calculated by the CCSD(T)/aug-cc-pVQZ level theory to explore possible isomerization and dissociation pathways. Several locally stable structures leading to H2CCN+, HCCNH+, HCNCH+, and H2CNC+ were found, while no intrinsic reaction coordinate leading to the CHCN+ formation pathway accompanied by H2 abstraction has been identified. The H2CCN+ + H dissociation channel is a major pathway of the reaction product, though theoretical calculations suggest the CHCN+ + H2 dissociation channel is energetically feasible. The present experimental and theoretical studies will contribute to the accurate modeling of nitrile chemistry in interstellar matter and in the upper atmosphere of Titan.

A Cost-Effective Computational Strategy for the Electronic Layout Characterization of a Second Generation Light-Driven Molecular Rotary Motor in Solution.

Light-driven molecular rotary motors are nanometric machines able to convert light into unidirectional motions. Several types of molecular motors have been developed to better respond to light stimuli, opening new avenues for developing smart materials ranging from nanomedicine to robotics. They have great importance in the scientific research across various disciplines, but a detailed comprehension of the underlying ultrafast photophysics immediately after photo-excitation, that is, Franck-Condon region characterization, is not fully achieved yet. For this aim, it is first required to rely on an accurate description at ab initio level of the system in this potential energy region before performing any further step, that is, dynamics. Thus, we present an extensive investigation aimed at accurately describing the electronic structure of low-lying electronic states (electronic layout) of a molecular rotor in the Franck-Condon region, belonging to the class of overcrowded alkenes: 9-(2-methyl-2,3-dihydro-1H-cyclopenta[a]naphthalen-1-ylidene)-9H-fluorene. This system was chosen since its photophysics is very interesting for a more general understanding of similar compounds used as molecular rotors, where low-lying electronic states can be found (whose energetic interplay is crucial in the dynamics) and where the presence of different substituents can tune the HOMO-LUMO gap. For this scope, we employed different theory levels within the time-dependent density functional theory framework, presenting also a careful comparison adopting very accurate post Hartree-Fock methods and characterizing also the different conformations involved in the photocycle. Effects on the electronic layout of different functionals, basis sets, environment descriptions, and the role of the dispersion correction were all analyzed in detail. In particular, a careful treatment of the solvent effects was here considered in depth, showing how the implicit solvent description can be accurate for excited states in the Franck-Condon region by testing both linear-response and state-specific formalisms. As main results, we chose two cost-effective (accurate but relatively cheap) theory levels for the ground and excited state descriptions, and we also verified how choosing these different levels of theory can influence the curvature of the potential via a frequency analysis of the normal modes of vibrations active in the Raman spectrum. This theoretical survey is a crucial step towards a feasible characterization of the early stage of excited states in solution during photoisomerization processes wherein multiple electronic states might be populated upon the light radiation, leading to a future molecular-level interpretation of time-resolved spectroscopies.

Directed Electrostatics Strategy Integrated as a Graph Neural Network Approach for Accelerated Cluster Structure Prediction.

We present a directed electrostatics strategy integrated as a graph neural network (DESIGNN) approach for predicting stable nanocluster structures on their potential energy surfaces (PESs). The DESIGNN approach is a graph neural network (GNN)-based model for building structures of large atomic clusters with specific sizes and point-group symmetry. This model assists in the structure building of atomic metal clusters by predicting molecular electrostatic potential (MESP) topography minima on their structural evolution paths. The DESIGNN approach is benchmarked on the prototype Mgn clusters with n < 150. The predicted MESP topography minima of Mgn clusters, n < 70, fairly agrees with the whole-molecule MESP topography calculations. Moreover, the ground-state structures of Mgn (n = 4-32) clusters generated through the DESIGNN approach corroborate well with the global minimum structures reported in the literature. Furthermore, this approach could generate novel symmetric isomers of medium to large Mgn clusters in the size regime, n < 150, by constraining the point-group symmetry of the parent clusters. The parent growth potential (GP) of a cluster gives a measure of its parent cluster to accommodate more atoms and characterize the structures on the DESIGNN-guided path. The GP of a cluster can also be interpreted as a measure of the cooperative interaction relative to its parent cluster. Along the highest GP paths, the DESIGNN approach is further employed to generate stable Mgn nanoclusters with n = 228, 236, 257, 260. Therefore, the DESIGNN approach holds great promise in accelerating the structure search and prediction of large metal clusters guided through MESP topography.

Energy Landscapes in Chemical Reactions and Transport.

Both, molecular chemical reactions and transport of atoms in solid media are determined by the energy landscape in which the seemingly different processes take place. Chemical reactions can be described as cooperative translocation of two chemical entities on a common potential energy surface. Transport of atoms in a solid can be envisaged as the translocation of a single particle in the potential energy landscape of all other particles constituting the solid. The goal of this manuscript is to demonstrate common grounds but also distinct differences in the physico-chemical processes, their experimental quantification and their theoretical modelling. This work will span the range from the historical foundations all the way to the current challenges. While scientists at the beginning of the 20th century where commonly active in both fields, e. g., Wilhelm Jost has pioneered and shaped the field of transport in solids and reaction kinetics in Germany, the fields have drifted apart for the last 50 decades. It is now time to bring the fields together again. Ultimately, it is suggested that knowledge gained in the field of transport may in fact stimulate advancement in the field of molecular reactivity and vice versa. Here, the energy landscapes are pivotal for knowledge-based advancement.

Dual-Mode Textile Sensor Based on PEDOT:PSS/SWCNTs Composites for Pressure–Temperature Detection

As an innovative branch of electronics, intelligent electronic textiles (e-textiles) have broad prospects in applications such as e-skin, human–computer interaction, and smart homes. However, it is still a challenge to distinguish multiple stimuli in the same e-textile. Herein, we propose a dual-parameter smart e-textile that can detect human pulse and body temperature in real time, with high performance and no signal interference. The doping of SWCNTs in PEDOT:PSS improves the electrical conductivity and Seebeck coefficient of the prepared composites, which results in excellent pressure and temperature-sensing properties of the PEDOT:PSS/SWCNTs/CS@PET-textile (PSCP) sensor. The dual-mode sensor has high sensitivity (32.4 kPa−1), fast response time (~21 ms), and excellent durability (&gt;2000 times) in pressure detection. Concurrently, this sensor maintains a high Seebeck coefficient of 25 μV/K in the 0–120 K temperature range with a tremendous linear relationship. Based on impressive dual-mode sensing characteristics and independent temperature-difference- and pressure-sensing mechanisms, smart e-textile sensors realize the real-time simultaneous monitoring of weak pulse signals and human body temperature, showing great potential in medical healthcare. In addition, the potential energy is excited by the temperature gradient between the human skin and the environment, which provides a novel idea for wearable self-powered devices.

Green Ferrites: Eco‐Friendly Synthesis to Applications in Environmental Remediation, Antimicrobial Activity, and Catalysis—A Comprehensive Review

ABSTRACTFerrite magnetic materials have emerged as capable materials in engineering, research, and medicine because of their exclusive and fascinating properties obtained from a variety of synthesis techniques. These ferrites are significant in commercial products, research, and biomedical applications. Green synthesis methods for ferrite nanocomposites and nanoparticles are becoming increasingly popular due to their usefulness in a range of industries, engineering, environmental, and medicinal remediation. Ferrite nanoparticles and nanocomposites (MFe2O4, where M = Ni, Cu, Mg, Co, Zn, and Mn) have recently gained popularity due to their many uses in biological, environmental, and chemical interactions. This review covers the most recent investigations over the last few years on green‐synthesized ferrite nanoparticles, ferrites containing nanocomposites, and more elements, with a focus on microorganism‐mediated and plant‐based synthesis processes. The surface features of ferrite nanoparticles synthesized from green materials are discussed, as is their potential for sensors, energy, water treatment, antibacterial activity, biological, and heavy metal removal applications. This article presents an inclusive overview of green‐synthesized ferrites, including the most recent research advances and findings. To fully realize the promise of nanoferrites in several fields, a thorough understanding of green manufacturing, properties, and applications is essential. Green‐synthesized ferrites are chosen due to their potential for improved control over particle size and shape, lower cost, decreased toxicity, and environmental friendliness, all of which preserve magnetic properties that are better than those of conventionally synthesized ferrites, making them a more sustainable choice for a range of applications.

A Method for the Precise Determination of the Intramolecular Potential Energy Surface on the Basis of Microwave and Submillimeter-Wave Spectra: Diatomic Molecules as a Relevant Illustration

A new method for the precise semiempirical determination of the basic parameters (structural parameters and parameters of the intramolecular potential energy surface, PES) of a molecule on the basis of highly accurate experimental data from the microwave and submillimeter-wave regions is suggested. The options and advantages of this method in comparison with the other methods of molecular PES determination are discussed using a diatomic molecule as an appropriate illustration. The HCl molecule is exploited as a suitable example. It is shown with this example that the use of a very limited number (ten for H35Cl and five for D35Cl) of submillimeter-wave line positions allows one to determine the values of the equilibrium rotational parameter, harmonic frequency, and anharmonic coefficients of the third, fourth, and fifth order with accuracy of 0.01%, 0.01%, 0.01%, 2.1%, and 10.1%, respectively, in comparison with the analogous results obtained from extensive infrared studies.

The Properties of the Low-Lying Electronic States and Avoided Crossings of the SbP Molecule: A Theoretical Investigation Includes Spin-Orbit Coupling.

High-level multireference configuration interaction plus Davidson correction (MRCI + Q) calculation method was employed to determine the potential energy curves (PECs) of 10 Λ-S states, which come from the first and second dissociation channels of the SbP molecule, as well as 34 Ω states considering the spin-orbit coupling (SOC) effect. By solving the Schrödinger equation for nuclear motion, spectroscopic constants for the ground state X1Σ+ and low-lying excited states were obtained and compared with experimental data. The excellent agreement indicates the reliability of our calculations. Additionally, the calculated spin-orbit (SO) matrix elements of the 13Π and 15Π states with other Λ-S states were analyzed, and the majority of the values in the Franck-Condon region exceed 200 cm-1, indicating strong interactions between these states. What's more, the joint effects of spin-orbit coupling and avoided crossing were discussed in detail, leading to the complex potential energy curves and double-well phenomena observed in the Ω states. Taking forbidden transitions into account, transition dipole moments with the SOC effect are considered. The Franck-Condon factors, Einstein coefficients, and radiative lifetimes for the 13Σ+1 ↔ X1Σ+0+ transition were obtained. Analysis indicates that direct laser cooling of SbP is inappropriate.

Depolarization and polarization transfer rates for the C_2 (X ^1Σ^+_g, a ^3Π_u) + H(^2S_ ) collisions in the solar photosphere

This paper is a continuation of a series of studies that investigated the collisional depolarization of solar molecular lines such as those of MgH, CN and C_2. It is focused on the solar molecule C_2, which exhibits striking scattering polarization profiles, although its intensity profiles are inconspicuous and barely visible. The current interpretation of the C_2 polarization in terms of magnetic fields is incomplete because collisional data are almost completely lacking. We accurately compute the collisional depolarization and polarization transfer rates for the C_2 $(X ^1Σ^+_g, a ^3Π_u)$ by isotropic collisions with hydrogen atoms H $(^2S_ )$. We also investigate the solar implications of our findings. We used the package MOLPRO to obtain potential energy surfaces for the electronic states X ^1Σ^+_g and a ^3Π_u of C_2, and the code MOLSCAT to study the quantum dynamics of the C_2 $(X ^1Σ^+_g, a ^3Π_u)$ + H$(^2S_ )$ systems. We used the tensorial irreducible basis to express the resulting collisional cross sections and rates. Furthermore, sophisticated genetic programming techniques were employed to determine analytical expressions for the temperature and total molecular angular momentum dependence of these collisional rates. We obtained quantum depolarization and polarization transfer rates for the C_2 $(X ^1Σ^+_g, a ^3Π_u)$ + H$(^2S_ )$ collisions in the temperature range T !=! 2,000 -- 15,000 K. We also determined analytical expressions that write these rates as functions of the temperature and total molecular angular momentum. In addition, we show that isotropic collisions with neutral hydrogen can only partially depolarize the lower state of the C_2 lines. This highlights that the approximation of neglecting lower-level polarization is limited in modeling the polarization of C_2 lines. Isotropic collisions with neutral hydrogen atoms are a fundamental ingredient for understanding C_2 polarization.

The chemical bonding and adsorption properties of the umbelliform B6Fe cluster

The interesting report [J. Am. Chem. Soc. 2016, 138, 5644−5651] is that the FeB6 monolayers have pronounced stabilities, in which planar hypercoordinate Fe atoms are located at the centre of six-membered boron rings. Here, we find that the potential energy surface of the FeB6 cluster has a single deep funnel that leads down to an umbelliform structure of the global minimum with the triplet state, which is 0.17 eV lower than that of the reported C2v plane. The chemical bonding analysis by the AdNDP reveals that the FeB6 has six localised two-centre two-electron (2c–2e) B–B bonds and six localised 2c–2e B–Fe bonds|, and the remaining two 7c–1e σ bonds are delocalised over the umbelliform structure, which is further confirmed by the ELF, LOL and bond order analyses. After the CO molecule is adsorbed on the FeB6, it prefers to be located at the top site of Fe atom. The adsorption energy is 1.34 eV that is due to the σ-donation from the CO 5σ orbital to the Fe. The charge transfer makes the C–O stretching frequency and bond length have a red-shift.

Analytical derivative approaches for vibro-polaritonic structures and properties. I. Formalism and implementation.

Vibro-polaritons are hybrid light-matter states that arise from the strong coupling between the molecular vibrational transitions and the photons in an optical cavity. Developing theoretical and computational methods to describe and predict the unique properties of vibro-polaritons is of great significance for guiding the design of new materials and experiments. Here, we present the abinitio cavity Born-Oppenheimer density functional theory (CBO-DFT) and formulate the analytic energy gradient and Hessian as well as the nuclear and photonic derivatives of dipole and polarizability within the framework of CBO-DFT to efficiently calculate the harmonic vibrational frequencies, infrared absorption, and Raman scattering spectra of vibro-polaritons as well as to explore the critical points on the cavity potential energy surface. The implementation of analytic derivatives into the electronic structure package is validated by a comparison with the finite-difference method and with other reported computational results. By adopting appropriate exchange-correlation functionals, CBO-DFT can better describe the structure and properties of molecules in the cavity than CBO-Hartree-Fock method. It is expected that CBO-DFT is a useful tool for studying the polaritonic structures and properties.

Full Quantum Dynamics Study for H Atom Scattering from Graphene.

This study deals with the understanding of hydrogen atom scattering from graphene, a process critical for exploring C-H bond formation and energy transfer during atom surface collision. In our previous work [Shi, L.; J. Chem. Phys. 2023, 159, 194102], starting from a cell with 24 carbon atoms treated periodically, we have achieved quantum dynamics (QD) simulations with a reduced-dimensional model (15D) and a simulation in full dimensionality (75D). In the former work, the H atom attacked the top of a single C atom, enabling a comparison of QD simulation results to classical molecular dynamics (cMD). Our approach required the use of sophisticated techniques such as Monte Carlo canonical polyadic decomposition (MCCPD) and multilayer multiconfiguration time-dependent Hartree (ML-MCTDH), as well as further development of quantum flux calculations. We could benchmark our calculations by comparison to cMD calculations. We now refined our method to better mimic experimental conditions. Specifically, rather than sending the H atom to a specific position on the surface, we employed a plane wave for the H atom in directions parallel to the surface. Key findings for these new simulations include the identification of discrepancies between classical molecular dynamics (cMD) simulations and experiments, which are attributed to both the potential energy surface (PES) and quantum effects. Additionally, this study sheds light on the role of classical collective normal modes during collisions, providing insights into energy transfer processes. The results validate the robustness of our simulation methodologies and highlight the importance of considering quantum mechanical effects in the study of hydrogen-graphene interactions.

Electronic spectroscopy and excited state mixing of OThF.

Electronic spectra for OThF have been recorded using fluorescence excitation and two-photon resonantly enhanced ionization techniques. Multiple vibronic bands were observed in the 340-460nm range. Dispersed fluorescence spectra provided ground state vibrational constants and evidence of extensive vibronic state mixing at higher excitation energies. Two-photon ionization measurements established the ionization energy for OThF of 6.283(5) eV. To guide the assignment of the OThF spectra, electronic structure calculations were carried out using relativistic equation-of-motion coupled-cluster singles and doubles methods. These calculations indicated that spin-orbit induced mixing of the 32A″ and 42A' states was mediated by a seam of potential energy surface intersections.

Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method

Abstract Back-illuminated spot mapping is essential for observations with modern spectroscopic survey telescopes. In the fiber position detection system, after the fiber view camera (FVC) detects the positions of the light spots from the robotic fiber positioners (RFPs), these positions must be mapped to the RFPs individually to complete subsequent calculations of their operational data. The back-illuminated images captured by the FVC show thousands of small light spots, each only hundreds of microns in size, randomly distributed on a completely black background, making accurate one-to-one mapping to the actual RFP positions highly challenging due to the lack of additional RFP features. This study constructs an artificial probability potential field to calculate the likelihood of each light spot appearing in the patrol area of an RFP, employing a global probability potential energy optimization method to establish the optimal mapping relationship. The proposed method successfully maps all light spots in the closed-loop fiber positioning task and is ultimately applied to the fiber positioning system of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, achieving accurate mapping of 4000 RFPs on the focal plane. This algorithm effectively addresses challenges such as multitarget interference, uniform background, and RFP failures, providing a reliable approach for mapping the back-illuminated points of tens of thousands of dual-rotation RFPs without requiring special backlight designs in future spectral survey telescopes.

Balconies can guide wind turbine placement in cities

The presence and geometry of balconies influences wind patterns and wind energy potential.

Evaluation of Energy Potential in a Landfill Through the Integration of a Biogas–Solar Photovoltaic System

The integration of biogas and photovoltaic solar energy systems in sanitary landfills represents a promising strategy for sustainable energy generation and efficient urban waste management. This study evaluates the potential for biogas and photovoltaic energy production in two cells of the Municipal Landfill of Chihuahua, Mexico. Using the LandGEM and MMB models (Landfill Gas Emission Model and the Mexican Biogas Model), biogas generation was estimated by considering the composition of the landfill gas and the characteristics of the cover in each cell, revealing notable differences due to their operational periods and waste deposition. Photovoltaic simulations, conducted with the HelioScope software 2020, evaluated spatial configurations and solar radiation data. The generation potential for 2025 was simulated using predictive models, yielding results between 25.48 and 26.08 MW for the biogas–photovoltaic system, depending on the orientation of the panels and the optimization of the coverage. The novelty of this work lies in the combined evaluation of biogas and photovoltaic potential within a single landfill site, integrating advanced modeling tools to optimize system design. By demonstrating the feasibility and benefits of this hybrid system, the study contributes to clean energy solutions, environmental mitigation, and improved waste management strategies. Our findings emphasize the importance of site-specific management practices and predictive modeling to enhance renewable energy production and reduce greenhouse gas emissions, supporting sustainable urban development initiatives.

Robotic Microcapsule Assemblies with Adaptive Mobility for Targeted Treatment of Rugged Biological Microenvironments.

Microrobots are poised to transform biomedicine by enabling precise, noninvasive procedures. However, current magnetic microrobots, composed of solid monolithic particles, present fundamental challenges in engineering intersubunit interactions, limiting their collective effectiveness in navigating irregular biological terrains and confined spaces. To address this, we design hierarchically assembled microrobots with multiaxis mobility and collective adaptability by engineering the potential magnetic interaction energy between subunits to create stable, self-reconfigurable structures capable of carrying and protecting cargo internally. Using double emulsion templates and magnetic control techniques, we confine 10 nm iron oxide and 15 nm silica nanoparticles within the shell of 100 μm microcapsules that form multiunit robotic collectives. Unexpectedly, we find that asymmetric localization of iron oxide nanoparticles in the microcapsules enhances the intercapsule potential energy, creating stable connections under rotating magnetic fields without altering the magnetic susceptibility. These robotic microcapsule collectives exhibit emergent behaviors, self-reconfiguring into kinematic chain-like structures to traverse complex obstacles, arched confinements, and adhesive, rugged biological tissues that typically impede microscale systems. By harnessing these functions, we demonstrate targeted antifungal delivery using a localized biofilm model on mucosal tissues, showing effective killing ofCandida without binding or causing physical damage to host cells. Our findings show how hierarchical assembly can produce cargo-carrying microrobots with collective, self-adaptive mobility for traversing complex biological environments, advancing targeted delivery for biomedical applications.

Factors for Manipulating the Tolerance of the Search Method Used in Genetic Algorithms to Determine Nanoclusters

Objective: The objective is to present a new method to explore BFGS where a new decision-making flow was added in order to optimize and computationally improve the performance of the Genetic Algorithm, controlling the value of the gradient as it evolves. Theoretical Framework: In the literature, the work presented by [Chen, 2014] stands out, who proposed that there must be a repulsive contribution to ensure the stability of the structure, which is introduced as the interaction between atomic pairs that makes up the second term of the cohesion energy. [Goldberg,1989] proposed the use of a genetic algorithm to search for available minima in the potential energy function associated with clusters. Method: The methodology adopted in this research was the use of Evolutionary Algorithms (EAs) are inspired by the principle of natural selection and survival of the fittest individuals, discovered by physiologist Charles Darwin and described in his book "The Origin of Species", from 1859. Among various selection methods, the roulette wheel method was used, as it is useful in problems where diversity needs to be maintained to avoid premature convergence. The crossover used by Deaven and Ho, which is a technique known as the cut-and-splice method, applied in the context of optimizing molecular structures or atomic clusters and the aluminum and magnesium clusters that were explored using a Genetic algorithm applied to Gupta potential function and tuned to look for the lowest energy minima for each cluster size. Results and Discussion: The results obtained revealed [synthesize the main results of the research]. In the discussion section, these results are contextualized in light of the theoretical framework, highlighting the implications and relationships identified. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: The objective of this article was to present a new method to explore BFGS where a new decision-making flow was added in order to optimize and computationally improve the performance of the Genetic Algorithm, controlling the value of the gradient as it evolves. This new method proved to be very promising according to the results presented in the previous section, since the Sequential Genetic Algorithm, which becomes quite costly as it invokes the BFGS optimization method, always has a very small Gradient vector error, unlike the Genetic Algorithm which It starts with a very low value and is gradually increased according to established criteria. In experiments carried out with both 10 seeds and 30 seeds, the Genetic Algorithm obtained better energies in the general average and the standard deviation was also much better, reaching better global minimums. Originality/Value: This study contributes to the literature by creating new flows in the Genetic Algorithm, enabling computational gains in the processing of experiments, which was proven in the results obtained.

Automated and Efficient Sampling of Chemical Reaction Space.

Machine learning interatomic potentials (MLIPs) promise quantum-level accuracy at classical force field speeds, but their performance hinges on the quality and diversity of training data. An efficient and fully automated approach to sample chemical reaction space without relying on human intuition, addressing a critical gap in MLIP development is presented. The method combines the speed of tight-binding calculations with selective high-level refinement, generating diverse datasets that capture both equilibrium and reactive regions of potential energy surfaces. By employing single-ended growing string and nudged elastic band methods, reaction pathways previously underrepresented in MLIP training sets, particularly near transition states are systematically explored. This approach yields datasets with rich structural and chemical diversity, essential for robust MLIP development. Open-source code is provided for the entire workflow, facilitating the integration of the approach into existing MLIP development pipelines.

Comparative Techno-Economic Analysis of Gray Hydrogen Production Costs: A Case Study

Despite Iran’s considerable renewable energy (RE) potential and excellent wind capacity and high solar radiation levels, these sources contribute only a small fraction of the country’s total energy production. This paper addresses the techno-economic viability of gray hydrogen production by these renewables, with a particular focus on solar energy. Given the considerable potential of solar energy and the strategic location of Shahrekord, it would be an optimal site for a hydrogen generation plant integrated with a solar field. HOMER Pro 3.18.3 software was utilized to model and optimize the levelized cost of hydrogen (LCOH) of steam reforming using different hydrocarbons in various scenarios. The results of this study indicate that natural gas (NG) reforming represents the most cost-effective method of gray hydrogen production in this city, with an LCOH of −0.423 USD/kg. Other hydrocarbons such as diesel, gasoline, propane, methanol, and ethanol have a price per kilogram of produced hydrogen as follows: USD −0.4, USD −0.293, USD 1.17, USD 1.48, and USD 2.15. In addition, integrating RE sources into hydrogen production was found to be viable. Moreover, by implementing RE technologies, CO2 emissions can be significantly reduced, and energy security can be achieved.