Chemically Research Articles

A New Approach to Magnesium Removal in Cobalt Precipitation

ABSTRACT Sodium dodecyl sulfate (SDS) was introduced to reduce the magnesium content in cobalt hydroxide precipitates (MHPs) derived from copper-cobalt ore leaching solutions. The impact of the key parameters – SDS dosage, MgO/Co mass ratio, reaction time, temperature, stirring speed, and MgO concentration – was systematically evaluated to identify the optimal conditions for producing MHP with minimal magnesium impurity. The effect of SDS on MHP crystal morphology, surface area, pore size, reaction kinetics, and electrostatic potential was also assessed. Under optimal conditions, with SDS, a magnesium grade of 0.96% and a cobalt grade of 53.69% were achieved, alongside a cobalt recovery of 98.69%. Moreover, SDS was found to enhance the chemical control reaction, reducing the activation energy from 74.96 kJ/mol to 67.86 kJ/mol. This study offers valuable insights into the magnesium removal mechanism facilitated by SDS, addressing the challenge of high magnesium impurities in MHP products and providing guidance for impurity control in other precipitation processes.

Capturing Ring Opening in Photoexcited Enolic Acetylacetone upon Hydrogen Bond Dissociation by Ultrafast Electron Diffraction.

Photoinduced biological and chemical reactions are often based on key structural transformations of a molecule driven across multiple electronic states. Acetylacetone (AcAc) is a prototypical system for complex chemical pathways involving several conical intersections (CI) and singlet-triplet intersystem crossings (ISC) characterized by distinct geometries. In the gas phase, AcAc is predominantly in a planar ring-like enolic form stabilized by a strong intramolecular O-H···O hydrogen bond. Following excitation into the S2 (ππ*) state at 266 nm, acetylacetone undergoes rapid internal conversion followed by intersystem crossing. Such relaxation pathways are associated with structural changes including ring opening, deplanarization, and bond elongation. In this work, ultrafast electron diffraction (UED) at the SLAC MeV-UED setup is employed as a direct structural probe with a time resolution of 160 fs. Together with trajectory surface hopping simulations, analysis of the UED data provides a new perspective on the early time nuclear dynamics in acetylacetone. Specifically, AcAc is observed to undergo ring opening, deplanarization, and bond elongation all within the first 700 fs after photoexcitation. The monitored dynamics is associated mainly with the nuclear motion on the S1 potential energy surface, formed after very rapid transfer from S2 to S1, allowing AcAc to reach the conical intersection to intersystem crossing. Such time scales of nuclear motion are contrasted with the time scales of electronic transitions in AcAc that were previously characterized with spectroscopic methods, specifically internal conversion (<100 fs) and intersystem crossing (∼1.5 ps).

A perspective marking 20 years of using permutationally invariant polynomials for molecular potentials.

This Perspective is focused on permutationally invariant polynomials (PIPs). Since their introduction in 2004 and first use in developing a fully permutationally invariant potential for the highly fluxional cation CH5+, PIPs have found widespread use in developing machine learned potentials (MLPs) for isolated molecules, chemical reactions, clusters, condensed phase, and materials. More than 100 potentials have been reported using PIPs. The popularity of PIPs for MLPs stems from their fundamental property of being invariant with respect to permutations of like atoms; this is a fundamental property of potential energy surfaces. This is achieved using global descriptors and, thus, without using an atom-centered approach (which is manifestly fully permutationally invariant). PIPs have been used directly for linear regression fitting of electronic energies and gradients for complex energy landscapes to chemical reactions with numerous product channels. PIPs have also been used as inputs to neural network and Gaussian process regression methods and in many-body (atom-centered, water monomer, etc.) applications, notably for gold standard potentials for water. Here, we focus on the progress and usage of PIPs since 2018, when the last review of PIPs was done by our group.

Atmospheric Switching between Etching and High-Quality Fluorination of Graphene by XeF2.

Fluorinated graphene (FG), a two-dimensional graphene derivative, has attracted wide attention due to its extraordinary physical and chemical properties, as well as its underlying applications. The treatment of xenon difluoride (XeF2) has proved to be an effective way to achieve FG with different stoichiometric F/C ratios without graphene being etched. Here we compare the fluorination of mechanically exfoliated graphene by a home-built XeF2 fluorination system and a commercial Orbis XeF2 etching system. During fluorination in the Orbis etching system, graphene behaves as a protective mask for the silicon substrate, as expected from reported studies (Robinson, J. T. Nano Lett. 2010, 10, 3001-3005, 10.1021/nl101437p; Rangarajan, A. Graphene as an etch mask for silicon. University of Illinois at Urbana-Champaign, 2014). However, in the home-built system, the results surprisingly demonstrate that graphene starts to be etched from the interface of graphene edges and the substrate, which we attribute to the introduction of water molecules during fluorination. We also find that quenching of graphene Raman signatures does not necessarily mean that all carbon atoms are covalently bound to a fluorine atom but that it probably arises from the etching away of graphene. These results reveal the importance of atmospheric water in the synthesis chemistry and derivative reactions of FG, and they provide guidance for its structure engineering to achieve high-quality FG formation.

Challenges and Opportunities in Using High Percentage Waste Glass Powder as Cement Replacement in Concrete

This paper investigates the feasibility of using waste glass powder as a partial replacement for cement in concrete, exceeding the current observed limit of ~ 20%. The study examines the chemical reactions between glass powder and cement to explore the likely factors that may restrict the replacement percentage to this threshold. Using mole-concept theory-based analysis, the findings suggest that additional calcium-silicate-hydrate (C-S–H) may be formed from the reactions between glass powder and Portlandite. This indicates the potential for cement replacement percentages greater than 20% without compromising the strength of the concrete, contrasting with the current experimentally observed limit. The paper identifies four potential key factors that may be responsible for the limited cement replacement: (1) at higher cement replacement percentage, there is unreacted glass powder in the mix; (2) the contribution to the strength of the C-S–H formed from the chemical reactions involving the glass powder is inferior to that from cement hydration; (3) size of the glass particles that hamper full expected chemical reactions; and (4) the slow rate of the chemical reactions, and hence the strength gain may not happen within 28 days. Finally, the paper discusses possible means of overcoming the above limitations towards achieving high glass powder percentages as cement replacement in concrete. The effect of high glass powder content on the fresh, mechanical and durability properties of concrete is beyond the scope of this study. Instead, the focus is on exploring potential methods to overcome the challenges associated with its use, aiming to reduce the carbon footprint.

Isothermal Heating of Blood Flow in Inclined Vessels: A Study of Variable Temperature and Concentration

ABSTRACTThis study investigates the isothermal heating effects on blood flow through inclined vessels, incorporating variable temperature and concentration under the influence of magnetic fields, chemical reactions, and porous media. Blood is modeled as a non‐Newtonian Casson fluid containing suspended dust particles and trihybrid nanoparticles, forming a two‐phase flow system. The governing equations, including separate momentum and energy equations for fluid and dust phases, are formulated using Rosseland and Boussinesq approximations and transformed into dimensionless form through similarity transformations. The Poincaré–Lighthill Perturbation Technique is applied to obtain analytical solutions. The results highlight the significant influence of parameters, such as Casson fluid behavior, thermal and mass Grashof numbers, volume fraction, and magnetic field strength on velocity, temperature, and concentration profiles. Findings suggest that higher dust volume fractions and magnetic field intensities reduce flow velocity, while temperature and concentration gradients enhance heat and mass transfer. These insights are vital for optimizing biomedical applications, including drug delivery systems and thermal therapies.

A Broad-Spectrum Catalyst for Aliphatic Polymer Breakdown.

Thermolysis of the well-defined aluminum fluoroalkoxide supported on silica (≡SiOAl(OC(CF3)3)2(O(Si≡)2), 1, 0.20 mmolAl g-1) at 200 °C forms a fluorinated amorphous silica-alumina (F-ASA) containing a distribution of Al(IV), Al(V), and Al(VI) sites that maintain relatively strong Lewis acidity. Small amounts of Brønsted sites are also present in F-ASA. Solid-state NMR studies show that a majority of the aluminum centers in F-ASA are not close to the Si-F groups that form during thermolysis. F-ASA is exceptionally reactive in cracking (or pyrolysis) reactions of neat polymer melts. Catalyst loadings as low as 2 wt % (0.017 mol % aluminum) efficiently break down isotactic polypropylene, high-density polyethylene, ethylene/1-octene copolymer, and postconsumer wastes. The major products of this reaction are hyperbranched liquid paraffins containing internal olefins and very small amounts of aromatics. Under continuous distillation of oils from the reaction mixtures, pyrolysis on 50 g reaction scales is feasible. F-ASA cokes and deactivates during this reaction but can be reactivated by calcination in air. These properties are complementary to other state-of-the-art catalysts for polymer breakdown, but unlike those catalysts F-ASA does not require an additional cofed reactant (e.g., H2, olefin, etc.) to drive the reaction.

Tuning the Reaction Chemistry for the Sulfo-Bromination of Bismuth, Leading to Dual-Tapered Bi-Sulfobromide Platelet Nanocrystals and Their Heterostructures.

The chemistry of sulfo-bromination of metals leading to dual-tapered 2D-shaped nanostructures is reported. This has been confined to the metal ion Bi(III), whose reduction followed by reionization in the presence of sulfide and bromide precursors leads to the desired bismuth sulfobromide nanocrystals. Initially Bi19S27Br3 seed rods are taken, where Bi(0) nanocrystals are connected via a redox chemistry, conjugating with secondary metal ions. Then these 1D-shaped Bi19S27Br3-Bi(0) heterostructures are transformed to dual-tapered 2D-shaped Bi19S27Br3-Bi(0) nanostructures following a solution-liquid-solid (SLS) growth mechanism. The sulfo-bromination process is initially nucleated on the metal(0) sites but grown on the surface of the substrate seed rods. The size of Bi(0) equilibrates the tapering, whereby the length of the rods is gradually reduced and the width of the rods is slowly widened, leading to the dual-tapered 1D to 2D shape-transferred Bi-chalcohalide nanostructures. Extensive electron microscopic analysis and stepwise synthesis have been carried out to investigate the growth mechanism and to understand the tapering during the shape evolution processes. In addition, these materials of seed rods, intermediate and final nanostructures obtained are further explored as photocatalysts for HER and their activities are compared. The reaction chemistry discussed here enables the controlled incorporation of two anions with Bi(0) ionization, where one end of the nanostructure initiates nucleation, while the other end promotes growth. Overall, the reaction chemistry here provides a pathway for the solution-processed 2D SLS growth process, leading to shape-controlled metal chalcohalide nanostructures.

Selective Excitation of IR-Inactive Modes via Vibrational Polaritons: Insights from Atomistic Simulations.

Vibrational polaritons, hybrid light-matter states formed between molecular vibrations and infrared (IR) cavity modes, provide a novel approach for modifying chemical reaction pathways and energy transfer processes. For vibrational polaritons involving condensed-phase molecules, the short polariton lifetime raises a debate over whether pumping polaritons may produce different effects on molecules compared to directly exciting the molecules in free space or under weak coupling. Here, for liquid methane under vibrational strong coupling, classical cavity molecular dynamics simulations show that pumping the upper polariton (UP) formed by the asymmetric bending mode of methane can sometimes selectively excite the IR-inactive symmetric bending mode. This finding is validated when the molecular system is described using both empirical force fields and machine-learning potentials, also in qualitative agreement with analytical theory of polariton energy transfer rates based on Fermi's golden rule calculations. Additionally, our study suggests that polariton-induced energy transfer to IR-inactive modes reaches maximal efficiency when the UP has significant contributions from both photons and molecules, underscoring the importance of light-matter hybridization. As IR-inactive vibrational modes are generally inaccessible to direct IR excitation, our study highlights the unique role of polariton formation in selectively controlling IR-inactive vibrations. Since this polariton-induced process occurs after the polariton decays, it may impact IR photochemistry on a time scale longer than the polariton lifetime, as observed in experiments.

Data-Driven Kinetic Reaction Networks for Separation Chemistry.

Understanding complex, multistep chemical reactions at the molecular level is a major challenge whose solution would greatly benefit the design and optimization of numerous chemical processes. The separation of rare-earth (4f) and actinide (5f) elements is an example where improving our chemical understanding is important for designing and optimizing new chemistries, even with a limited number of observations. In this work, we leverage data-driven artificial intelligence and machine-learning approaches to develop kinetic reaction networks that describe the liquid-liquid extraction mechanism of uranium using N,N-di-2-ethylhexyl-isobutyramide (DEHiBA). Specifically, we compare and contrast the properties of two classes of models: (1) purely data-driven models that are regularized using chemistry-agnostic, L1 regression and (2) chemistry-informed models that are regularized using relative reaction energies provided by quantum mechanical calculations. We observe that purely data-driven models are unbiased, simple, and accurate in their predictions of experimental measurements when provided with sufficient data but are difficult to fully constrain and interpret. In contrast, chemistry-informed models exhibit significantly improved chemical interpretability and consistency, providing a detailed description of the separation process while achieving high accuracy through ensemble averaging. Overall, the dominant species predicted to be extracted into the organic phase is UO2(NO3)2(DEHiBA)2, agreeing with experimental slope analysis, thermodynamic modeling, EXAFS, and crystal structures. This work demonstrates that leveraging the fundamental structure of the problem can lead to efficient learning schemes that provide both accurate predictions and chemical insights at a low computational cost.

Direct capture of a low-energy free-electron into delocalized σ* orbitals for enabling state- and bond-selective reactions

Chemically activating a bond by capturing a low-energy free-electron directly and resonantly into its σ* orbital is conceptually simple and yet the most fascinating possibility for achieving state-specific and bond-specific chemical control. But this direct approach has not been explored experimentally due to the very low resonant electron capture cross-section of electrons into the σ* orbital. Here we report defunctionalization and dehydrogenation reactions that are bond-selectively enabled by the direct capture of a low-energy electron into the σ* orbital. The remarkable efficiency of these reactions can be attributed to superpositions of the σ* orbital with its vicinal or conjugated σCH* orbitals. The ubiquity of such quantum superpositions in molecules opens unprecedented experimental possibilities in the aspiration to control chemical reactions using low-energy free-electrons.

Recent updates of the MPEXS2.1-DNA Monte Carlo code for simulations of water radiolysis under ion irradiation

To improve radiotherapy, especially that with ion beams such as proton and carbon ion beams, the mechanisms of interactions induced by ionizing radiation must be understood. MPEXS2.1-DNA is a Monte Carlo simulation code developed for water radiolysis studies and DNA damage simulations that uses GPU devices for fast computation. However, the original chemistry model in MPEXS2.1-DNA did not include detailed chemical reactions for reactive oxygen species (ROS), e.g., O•-, O2, O2•-, HO2•, HO2-. In the present study, drawing the former work on the step-by-step (SBS) model for the RITRACKS code, we implemented an alternative SBS model into MPEXS2.1-DNA to increase the capabilities and computational speed of water radiolysis simulations under ion irradiation. This model is based on the theory of Green’s function of the diffusion equation (GFDE-SBS). Also, we implemented multiple ionization processes which enhance ROS generation under high-LET irradiation. We compared the simulation results obtained by GFDE-SBS with experimental data from previous studies. The validation results demonstrated that the GFDE-SBS model accurately reproduced the measured radiation chemical yields of major species, such as hydroxyl radicals and hydrogen peroxide. Furthermore, the computational speed of GFDE-SBS was increased approximately ten times faster than the original model due to the changes in time stepping. Additionally, simulations using a Fricke dosimeter confirmed that this model is reliable for long-term simulations over seconds. These improvements enable simulations of radiation interactions and can help in the study of DNA damage mechanisms.

Образование лигнофенолоформальдегидных смол при среднем содержании щёлочи в реакционной смеси

In this study the composition and properties of lignin-phenol-formaldehyde resin have been studied. The lignin-phenol-formaldehyde resin was synthesized with a content of 15.9 % of technical sodium lignosulfonates relative to the resin weight by absolute dry. The aim of this research is to evaluate the composition of the reaction mixture of the synthesis of lignin-phenol-formaldehyde resin at different stages. Physico-chemical analysis was conducted to determine the compliance of the synthesized resin with the requirements of GOST 20907-2016 «Liquid phenolformaldehyde resins. Specifications». The obtained lignin-phenol-formaldehyde resin has an extremely low relative viscosity (15 c) a high concentration of free phenol (0.16 %), and free formaldehyde (0.43 %). The composition of the resin was investigated using 13C NMR spectroscopy at thre synthesis stages. At the first stage of synthesis was observed the low reactivity of the “phenol-formaldehyde” system that explained by the low concentration of an alkaline catalyst in the reaction mixture. Additionally, signals of free formaldehyde and ether fragments were detected in the reaction mixture. During the second stage of synthesis, the process of polycondensation progressed further, resulting in the formation of high molecular weight oligomers. These oligomers comprise three phenol residues connected by one methylene para-para bond and one methylene ortho-para' bridge. Following the second stage of synthesis, the number of free reactive centers in the ortho position decreases by approximately 9 times in the reaction mixture, and the proportion of methylene carbon decreases by 9 %. The spectra of the reaction mixture after the third stage of synthesis exhibit a complete absence of signals from free reaction centers, resulting in signals of free formaldehyde. The obtained results of the study enable the establishment of the interaction between lignin and phenol during the exposure of the reaction mixture at a temperature of 96-98 °C, as well as the evaluation of the effect of substituting the phenol fraction with lignin on the chemical composition of the mixture at different stages of synthesis. Particleboards manufactured using the synthesized resin demonstrate favorable properties.

Gas–liquid two-phase bubble flow spinning for hydrovoltaic flexible electronics

Hydrovoltaic technologies that generate electricity by absorbing or transferring free water without chemical reactions have been explored as potential candidates for renewable energy. Self-powered flexible sensors, including hydrovoltaic fibers, are becoming an important research direction in the field of renewable energy. However, integrating sensing and power generation in functional fibers remains challenging due to the need to regulate water movement to achieve performance differences. Here, we present a gas-liquid two-phase flow spinning method, inspired by spider multimodal spinning, that uses bubble-triggered spinning-liquid deformation to fabricate hollow, solid spindle, and ratchet tooth-shaped fibers. These structures alter water adsorption and transfer behaviors, making them suitable for targeted applications in hydrovoltaic devices for energy and sensing fields. Shaped fibers prepared from alginate-bridged MoS₂ enable a wide range of hydrovoltaic applications. The obtained fiber has a power density of 2.18 mW/cm3, stable operation at 2.1 V for 43 hours, and sensitivity of 9.36 mV/RH%/s, leading to the development of smart masks for nasal cycle monitoring, diagnosis, and therapy as potential applications. Spinning materials were extended to materials such as carboxymethyl cellulose, polyvinyl alcohol, etc., inspiring the design of structure-responsive hydroelectric materials and advancing textile electronics.

Photon–photon chemical thermodynamics of frequency conversion processes in highly multimode systems

Frequency generation in highly multimode nonlinear optical systems is inherently a complex process, giving rise to an exceedingly convoluted landscape of evolution dynamics. While predicting and controlling the global conversion efficiencies in such nonlinear environments has long been considered impossible, here, we formally address this challenge even in scenarios involving a very large number of spatial modes. By utilizing fundamental notions from optical statistical mechanics, we develop a universal theoretical framework that effectively treats all frequency components as chemical reactants/products, capable of undergoing optical thermodynamic reactions facilitated by a variety of multi-wave mixing effects. These photon–photon reactions are governed by conservation laws that directly determine the optical temperatures and chemical potentials of the ensued chemical equilibria for each frequency species. In this context, we develop a comprehensive stoichiometric model and formally derive an expression that relates the chemical potentials to the optical stoichiometric coefficients, in a manner akin to atomic/molecular chemical reactions. This advancement unlocks new predictive capabilities that can facilitate the optimization of frequency generation in highly multimode photonic arrangements, surpassing the limitations of conventional schemes that rely exclusively on nonlinear optical dynamics. Notably, we identify a universal regime of Rayleigh–Jeans thermalization where an optical reaction at near-zero optical temperatures can promote the complete and entropically irreversible conversion of light to the fundamental mode at a target frequency. Our theoretical results are corroborated by numerical simulations in settings where second-harmonic generation, sum-frequency generation and four-wave mixing processes can manifest.

Evaluating the Chemical Reactivity of Wildfire-Derived Dissolved Organic Molecules: Glutathione Binding through Kendrick Mass Defect Analysis.

The emerging risks to organisms of pyrogenic-derived dissolved organic matter (PyDOM) from forest fires are of concern due to its toxic and mutagenic potential (e.g., pro-oxidative responses in fauna through the depletion of glutathione, a nitrogen- and sulfur-containing tripeptide found in cells). This study simulates this phenomenon in a laboratory setting by identifying bonding between reduced l-glutathione and organic molecules in leachates from environmentally weathered biomass samples (charred and uncharred) using Kendrick Mass Defect (KMD) analysis from formula lists obtained from negative-mode electrospray ionization-Fourier transform-ion cyclotron resonance-mass spectrometry ((-)ESI-FT-ICR-MS). These formula lists reveal a 10-fold increase in nitrogen- and sulfur-containing molecular formulas in the charred biomass samples compared with the unreacted charred biomass when subjected to reaction with glutathione. KMD analysis attributed the bonding of glutathione to the biomass leachates accounting for approximately 25% of the new nitrogen- and sulfur-containing molecular formulas as either addition-type or condensation/elimination-type reactions. KMD sheds light on a different fraction of chemically reactive wildfire-produced organic compounds that may be of interest for subsequent toxicological studies.

Dynamic Combinatorial Chemistry of Ditellurides.

Dynamic combinatorial chemistry enables the exploration of reversible chemical exchange reactions. Here, we report studies on the dynamic Te-Te bond exchange of chemically and structurally diverse ditellurides using 125Te NMR spectroscopy. The results revealed rapid and unbiased equilibration, forming a consistent 1:1 distribution of reactants and products across all chemical systems. Extending to multi-component mixtures, we observed robust equilibrium formation even in complex systems involving multiple ditelluride species that can be easily distinguished by 125Te NMR spectroscopy. In line with the NMR analyses showing that the Te-Te bond exchange efficiently proceeds in various solvents, at very low temperature, in the absence of visible light and in the presence of radical scavengers, quantum chemical analyses revealed that the ditelluride-ditelluride exchange likely proceeds via a non-synchronous concerted mechanism and not via an alternative radical mechanism. Integrated NMR spectroscopic and quantum chemical analyses also showed that the efficiency of the chalcogen-chalcogen exchange involving ditellurides follows the trend Te-Te > Te-Se > Te-S. Overall, the results indicate that ditellurides are excellent dynamic systems that may find applications across molecular sciences.

A programmable magnetic digital microfluidic platform integrated with electrochemical detection system

Digital microfluidic (DMF) technology is widely used in bioanalysis and chemical reactions due to its accuracy and flexibility in manipulating droplets. However, most DMF systems usually rely on complex electrode fabrication and high driving voltages. Sensor integration in DMF systems is also quite rare. In this study, a programmable magnetic digital microfluidic (PMDMF) platform integrated with electrochemical detection system was proposed. It enables non-contact, flexible droplet manipulation without complex processes and high voltages, meeting the requirements of automated electrochemical detection. The platform includes a magnetic control system, a microfluidic chip, and an electrochemical detection system. The magnetic control system consists of a microcoil array circuit board, a N52 permanent magnet, and an Arduino control module. N52 magnets generate localized magnetic fields to drive droplet movement, while the Arduino module enables programmable control for precise manipulation. The maximum average velocity of the droplet is about 3.9 cm/s. The microfluidic chip was fabricated using 3D printing and the superhydrophobic surface of chip was fabricated by spray coating. The electrochemical detection system consists of the MoS2@CeO2/PVA working electrode, Ag/AgCl reference electrode, and carbon counter electrode. To evaluate the practical value of the integrated platform, glucose in sweat was automatically and accurately detected. The proposed platform has a wide linear detection range (0.01–0.25 mM), a lower LOD (6.5 μM), a superior sensitivity (7833.54 μA·mM−1·cm−2), and excellent recovery rate (88.1–113.5%). It has an extensive potential for future application in the fields of medical diagnostics and point-of-care testing.

Electrical double layer induced zeta potential effect in a disk cone system with surface catalyzed reaction

The present study highlights the zeta potential effect of electrokinetic flow in a disk cone system. The study sheds light on the shape of nanoparticles on ternary nanofluid flow with surface catalyzed chemical reaction. The potential implication is optimization of microfluidic appliances and reactors. The pace of reaction on the surface is analyzed by homogeneous and heterogeneous reactions in the presence of surface catalyzed chemical reactions. The designed model is a system of coupled partial differential equations. Utilization of self-similar variables along with normalization converted the system of partial differential equations into ordinary differential equations. Fourth order collocation method by using MATLB helped to analyze the results in graphical form. It has been concluded that electric field parameter, electroosmotic parameter and zeta potential amplifies the radial velocity while disk cone system is rotating in same direction. The lamina shape of the particles is more sensitive to the temperature variation by increasing thermal radiation parameter as compared to spherical shape.

Enhancing High-Order Harmonic Generation Efficiency Through Molecular Size and Orientation Effects: A Pathway to Ultrafast Chemical Dynamics Studies

High-order harmonic generation provides a powerful tool for probing ultrafast chemical dynamics, such as electron transfer, bond breaking, and molecular structural changes, with attosecond temporal resolution. The strong laser fields used in HHG can also directly influence chemical reaction pathways and rates, enabling coherent control of reaction selectivity. However, enhancing the efficiency of harmonic emission remains a critical challenge in ultrafast science. In this study, we investigate the effects of molecular size and orientation on HHG efficiency using time-dependent density functional theory simulations. By analyzing the linear molecules C18H2, C2H2, and C10H2 under linearly polarized laser fields, we demonstrate that larger molecular sizes significantly enhance harmonic emission intensity. Our results reveal that C18H2, with its larger spatial dimensions, exhibits substantially higher harmonic intensity compared to smaller molecules like C2H2. This enhancement is further supported by examining charge redistribution and bond length changes during the HHG process. Additionally, we validate our findings with C10H2, a molecule of intermediate size, confirming the correlation between molecular size and harmonic efficiency.