Computational Dynamics Research Articles

Molecular Mechanistic Analysis of Liquid-Crystalline Polymers Composed of p-Hydroxybenzoic Acid I: Thermal Properties.

All-atom molecular dynamics (MD) calculations of the crystalline polymeric p-hydroxybenzoic acid (pHBA) were conducted at various temperatures to investigate its thermal response. The calculated structure factor equivalent to the X-ray diffraction pattern of pHBA clearly showed two phase transitions occurring at 600 and 650 K. The first transition at 600 K occurred from the orthorhombic phase to the pseudohexagonal phase, identified by the presence of the 211-peak. This peak disappeared during the second transition at 650 K, indicating that the phase at 650 K was hexagonal. The structure of the pseudohexagonal phase was anisotropic with respect to the ab plane but isotropic in the hexagonal phase. Discontinuous changes in the calculated unit cell volume and unit cell length were observed at 600 K, associated with the first phase transition. We also calculated the linear expansion coefficients in three directions. An anisotropic expansion was observed in three directions for the orthorhombic crystal. In particular, the linear expansion coefficient in the c-direction was negative. In contrast to this, an isotropic expansion was found in the a- and b-directions for the hexagonal crystal, while the expansion in the c-direction is still negative. This study provides valuable insights into the thermal behavior of polymeric pHBA, which is essential for understanding its structural transformations and designing crystalline polymers with tailored thermal properties.

Flow-Induced Stress Analysis of a Large Francis Turbine Under Different Loads in a Wide Operation Range

Francis turbines, being widely used in hydropower plants, operate under different loads which significantly affect their hydraulic characteristics and structural dynamics. It is essential to carry out the flow-induced dynamics analysis of the large prototype Francis turbines under different loads in a wide load operation range to optimize the hydraulic performance, ensure structural reliability, and prevent mechanical failure. This work analyzes the flow-induced dynamics of a large Francis turbine prototype with a rated power of 46 MW. Computer-aided design (CAD) models of the Francis turbine unit are first constructed, including the fluid and structural domains. After generating the computational meshes of the flow passages in the Francis turbine unit, Computational fluid dynamics (CFD) calculations are carried out under four typical operating conditions from 25% load to 100% load, and the pressure files obtained from CFD calculations are applied to the finite element model to analyze the flow-induced stresses of the runner. The results show that the pressure inside the Francis turbine runner decreases gradually from the spiral case to the draft tube under 25%, 50%, 75%, and 100% loads, but the local pressure distribution in the crown chamber of the Francis turbine unit varies under different loads. The locations of the maximum stress of the runner under the four different operating conditions vary with the power output. The flow-induced maximum stress of the runner at 25% load is located on the chamfer of the connection between the blade trailing edge and the crown. But from 50% load to 100% load, the maximum stress of the runner appears on the chamfer of the connection between the blade leading edge and the band. From 25% load to full load, the maximum stress of the unit is one-fifth of the yield stress of the runner material, and the runner will not be damaged during normal use. The calculation method with a fully three-dimensional fluid–structure interaction (FSI) method and the conclusions proposed in this study can provide important references for the design and evaluation of other hydraulic turbine units.

Superlattice Thermal Modulation in MoS2${\rm MoS}{_2}$ by Defect Engineering

Abstract is one of the most investigated and promising transition‐metal dichalcogenides. Its popularity stems from the interesting properties of the monolayer phase, which can serve as the fundamental block for numerous applications. In this paper, an atomistic perspective on the modulation of thermal transport properties in monolayer through strategic defect engineering, specifically the introduction of sulfur vacancies is proposed. Using a combination of molecular dynamics simulations and lattice dynamics calculations, how various distributions of sulfur vacancies (ranging from random to periodically arranged configurations) affect its thermal conductivity is shown. Notably, it is observed that certain periodic arrangements restore the thermal conductivity of the pristine system, due to a minimized interaction between acoustic and optical phonons facilitated by the imposed superperiodicity. This research deepens the understanding of phononic heat transport in two‐dimensional (2D) materials and introduces a different point‐of‐view for phonon engineering in nanoscale devices, offering a pathway to enhance device performance and longevity through tailored thermal management strategies.

SF6 Dynamic Capacitance Measurement Methods for Breaks in the Breaking Process of Circuit Breakers

In order to effectively obtain the contact state without disassembling the interrupter chamber of the SF6 circuit breaker, a dynamic capacitance measurement method for the breakout process of the circuit breaker is proposed. The dynamic capacitance measurement is carried out by applying high-frequency excitation at both ends of the interrupter chamber, the dynamic capacitance measurement system that can meet the pF-level variation is designed, and the measurement method for correcting the stray capacitance of the wire is proposed. Based on the fundamental wave component method, a dynamic capacitance calculation method is proposed for the circuit breaker tripping process, and the optimal parameter combination for the dynamic capacitance calculation is determined through simulation analysis. The best combination of computational parameters for dynamic capacitance calculations was determined to be a triangular window, a window length of 480, and an overlap length of 0. The dynamic capacitance-travel curve of SF6 circuit breaker tripping process under different ablation states is obtained in the final test, and the results show that: with the increase in contact ablation, the overall shape of the dynamic capacitance-travel curve is basically unchanged, and the capacitance value at the starting point increases and the travel value decreases, which provides a new idea for the evaluation of circuit breaker interrupter chamber’s electric life. This provides a new idea for the electrical life assessment of circuit breaker interrupters.

Availability of five hydraulic damper models for dynamics simulation and application of two types of high-speed electrical multiple units

ABSTRACT To attenuate oscillations of railway passenger vehicles, hydraulic dampers are widely employed in suspension structures, for which high-speed electrical multiple units (EMUs) with excellent dynamics performance are critical. This study employs a vehicle-track coupling model to predict damper loads with an operation speed of 400 km/h. Five models characterizing hydraulic damper dynamics, namely the simplification model, Maxwell model, the new damper model presented by Ren, and two new damper models presented in this paper, are employed to study the availability of the damper models in simulating vehicle dynamics. Field-tested loads of the damping forces for the dampers of two types of EMUs are used to fulfill the investigation. It indicates that the damping velocity and unloading velocity of the damper is critical to the damping load and vehicle dynamics. The simplification model and Maxwell model have some deficiencies in the vehicle dynamics calculation, especially as the unloading velocity of the damper is much low.

Photoinduced Electron-Nuclear Dynamics of Fullerene and Its Monolayer Networks in Solvated Environments.

The recently synthesized monolayer fullerene network in a quasi-hexagonal phase (qHP-C60) exhibits superior electron mobility and optoelectronic properties compared to molecular fullerene (C60), making it highly promising for a variety of applications. However, the microscopic carrier dynamics of qHP-C60 remain unclear, particularly in realistic environments, which are of significant importance for applications in optoelectronic devices. Unfortunately, traditional ab initio methods are prohibitive for capturing the real-time carrier dynamics of such large systems due to their high computational cost. In this work, we present the first real-time electron-nuclear dynamics study of qHP-C60 using velocity-gauge density functional tight binding, which enables us to perform several picoseconds of excited-state electron-nuclear dynamics simulations for nanoscale systems with periodic boundary conditions. When applied to C60, qHP-C60, and their solvated counterparts, we demonstrate that water/moisture significantly increases the electron-hole recombination time in C60 but has little impact on qHP-C60. Our excited-state electron-nuclear dynamics calculations show that qHP-C60 is extremely unique and enable exploration of time-resolved dynamics for understanding excited-state processes of large systems in complex, solvated environments.

Unraveling the effect of reagent vibrational excitation on the scattering mechanism of the benchmark H + H2 → H2 + H hydrogen exchange reaction in the coupled 12E' ground electronic manifold.

The hydrogen exchange reaction, H + H2 → H2 + H, along with its isotopic variants, has been the cornerstone for the development of new and novel dynamical mechanisms of gas-phase bimolecular reactions since the 1930s. The dynamics of this reaction are theoretically investigated in this work to elucidate the effect of reagent vibrational excitation on differential cross sections (DCSs) in a nonadiabatic situation. The dynamical calculations are carried out using a time-dependent quantum mechanical method, both on the lower adiabatic potential energy surface and employing a two-state coupled diabatic theoretical model to explicitly include all the nonadiabatic couplings present in the 12E' ground electronic manifold of the H3 system. Towards this effort, the Boothroyd-Keogh-Martin-Peterson (BKMP2) surface of the lower adiabatic component is coupled with the double many-body expansion (DMBE) surface of the upper one. The smooth variation of energy along the D3h seam of the conical intersections is explicitly confirmed. The coupled two-state calculations are performed only for H2 (v = 3-4, j = 0), as the minimum of the conical intersections becomes energetically accessible for these vibrational levels in the considered energy range. Initial state-selected total and state-to-state DCSs are calculated to elucidate various mechanistic aspects of reagent vibrational excitation. The latter enhances the forward scattering and makes the backward scattering less prominent. Important roles of collision energy in the vibrational energy disposal of both forward- and backward-scattered products are examined. Analysis of the state-to-state DCSs of the vibrationally excited reagents reveals an important correlation among scattering angle, and the product rotational angular momentum and its helicity state. Such an analysis establishes a novel mechanism for the forward scattering of the reaction.

State-to-State Time-Dependent Quantum Dynamics Studies of the Si(3P) + OH(X 2Π) → OSi(X 1Σg+) + H(2S) Reaction Based on a New HOSi(X2A') Potential Energy Surface.

Quantum and quasi-classical dynamics calculations were conducted for the reaction of Si with OH on the latest potential energy surface (PES), which is obtained by fitting tens of thousands of ab initio energy points by using the many-body expansion formula. To obtain an accurate PES, all energy points calculated with aug-cc-pVQZ and aug-cc-pV5Z basis sets were extrapolated to the complete basis set limit. The accuracy of our new PES was verified by comparing the topographic characteristics and contour maps of potential energy with other works. In addition, the anharmonic vibrational frequencies of HOSi and HSiO based on the present ab initio and PES by means of quantum dynamics methods were calculated. Dynamics information such as reaction probability, integral cross sections (ICS), product distribution, and rate constants was obtained on the new HOSi(X2A') PES. The dynamic information calculated using the quasi-classical trajectory method and time-dependent wave packet method is generally in good agreement, except for the vibrational state-resolved ICSs of product. The calculated differential cross section and capture time reveal that the reaction is primarily governed by the complex formation mechanism.

Thermophysical properties of undercooled Zr–Fe–Nb alloys investigated by electrostatic levitation and molecular dynamics calculation

The density, surface tension, and viscosity of liquid Zr76.0−xFe24.0Nbx (x = 6.6, 10.0, 15.0) alloys were measured by using the electrostatic levitation technique. The maximum undercooling achieved for these alloys was 151, 91, and 119 K, respectively. To evaluate the thermophysical properties in a wider temperature range, molecular dynamics simulations were performed by using the embedded atom method potential. Both measured and simulated results indicate that the liquid density increases linearly with decreasing temperature and also gradually rises with increasing Nb content. Additionally, the simulated and experimental results for surface tension and viscosity were analyzed. In all three alloys, surface tension increases linearly with decreasing temperature. The relationship between viscosity and temperature follows an Arrhenius-type equation, with both surface tension and viscosity increasing as the Nb content increases. The calculated results of density, surface tension, and viscosity are in good agreement with the experimental results. Furthermore, the specific heat, emissivity, and diffusion coefficient of liquid alloys were calculated. The specific heat for liquid Zr76.0−xFe24.0Nbx (x = 6.6, 10.0, 15.0) alloys is (36.47 ± 1.68), (35.20 ± 2.28), and (41.04 ± 3.73) J mol−1 K−1, respectively. Emissivity decreases linearly with temperature. The diffusion coefficient decreases, while the diffusion activation energy increases with a higher Nb content.

Insights into polymer electrolyte stability and reaction pathways: A first-principle calculations study.

To identify suitable polymer candidates for electrolytes in solid-state batteries, this study investigates the electrochemical behavior and decomposition pathways of four monomers involving esters, ethers, and carbonates via first-principles calculations. In particular, we determine the oxidation and reduction potentials of these monomers near different ions (Li+, TFSI-, and [Li]+[TFSI]-) and the corresponding reorganization energies. The latter quantity is central to Marcus theory of electron transfer and, therefore, provides additional kinetic information. Our results reveal notable sensitivity of the monomers to reduction in a Li+-rich regime and to oxidation in a TFSI--rich regime. Additionally, the reactivity and decomposition pathways of the monomers were investigated for various electrochemical environments, focusing on the quantification of gaseous and ionic products during the initial stage of formation of interphasial layers. Based on the electrochemical windows and spontaneous Ab initio molecular dynamics calculations, we observe that monomers containing carbonate groups exhibit greater stability against decomposition caused by reduction, especially in different regimes, when compared to monomers with ester and ether groups.

The energy consumption characteristics of a new type of energy dissipating vibration-damping fastener

To address the issue of inadequate energy dissipation capacity in current vibration-damping fasteners, this study examined the impact of stiffness and damping factor of vibration-damping fasteners on the vibration attenuation rate of rails, based on the theoretical model of a periodic double-layer support system. An intrinsic manganese–copper (Mn–Cu) damping alloy model was established, and the parameters for the Prony analysis and PRF model were determined to accurately define the hyperelastic and linear viscoelastic properties of the damping alloy in the finite element simulation software. A new type of energy dissipating vibration-damping fastener (NEDF) was designed based on these criteria and practical operational conditions. Static and dynamic stiffness simulation calculations were performed to examine the vibration isolation ability of NEDF, which was then installed in a rail system to conduct hammering tests, aiming to investigate its energy dissipation characteristics. The results indicated that NEDF exhibited a high damping factor and maintained significant vibration isolation capacity, notably enhancing the vibration attenuation rate of the rails and improving energy dissipation capacity.

Image encryption algorithm based on the dynamic RNA computing and a new chaotic map

Image encryption algorithm based on the dynamic RNA computing and a new chaotic map

Localized Heating Assisted Laser Shock Peening without Coating Enhances Mechanical Properties of Ti6Al4V Alloys

Room-temperature laser shock peening without coating (RT-LSPwoC) is the mainstream method for surface strengthening, yet it induces tensile residual stress on the surface during rapid heating and cooling. Warm LSPwoC, combining the benefits of dynamic strain aging and LSPwoC, exhibits higher performance than RT-LSPwoC. However, overall high-temperature is time- and resource-consuming, and it is prone to causing thermal stress relaxation during processing, making it unsuitable for large-scale applications. In this paper, a novel localized heating assisted LSPwoC (LHA-LSPwoC) method, utilizing a continuous wave laser for local heating, is proposed. Additionally, the deep physics-informed neural network model, embedded with physical formulas, is designed for process optimization. It enables rapid and accurate responses for an extensive number of cases (40 cases with an average deviation below 1%), overcoming the drawbacks of traditional numerical simulations that are time-consuming and difficult to efficiently handle numerous cases. Compared to RT-LSPwoC, LHA-LSPwoC samples have higher dislocation density and higher grain refinement, demonstrating higher hardness and residual stress, particularly superior fatigue performance. The mechanism of LHA-LSPwoC is discussed, and thermally coupled finite element simulations and molecular dynamics calculations are conducted to provide theoretical support. The proposed method is cost-effective and flexible, showing outstanding potential for industrial applications.

Ruthenium Nanoparticles Supported on Bentonite: Enhanced Crystallinity, Conductivity, and Dielectric Performance for Advanced Applications

We used the wet impregnation method to synthesize Ru nanoparticles supported on bentonite (Ru/Bento). The X-ray diffraction and Energy-Dispersive (EDX) Spectrometer characterisations of the synthesized structures revealed that the montmorillonite is the predominant phase. The reduced crystallite size and lower diffraction peak intensities for Ru/Bento indicate improvement in crystallinity. EDX confirmed the successful incorporation of Ru, suggesting fewer reactive hydroxyl groups on the bentonite surface. Dielectric studies show a decrease in permittivity with increasing frequency, consistent with the Maxwell-Wagner polarization mechanism. Ru/Bento exhibits higher permittivity at elevated temperatures due to enhanced interfacial polarization, and higher low-frequency dielectric loss attributed to resistive interfacial regions. Electric modulus analysis indicates significant relaxation processes in Ru/Bento at higher temperatures. Conductivity studies demonstrate increased charge carrier mobility with frequency and temperature, following a correlated barrier hopping mechanism, with Ru nanoparticles enhancing conductivity by reducing barrier height. HOMO and LUMO analysis suggest improved conductivity and reactivity for Ru/Bento due to lower energy gaps and chemical hardness. Molecular dynamics calculations confirm the geometric stability of Ru nanoparticles on bentonite, making Ru/Bento bentonite a promising material for high conductivity applications.

Solar Wind Ion Sputtering from Airless Planetary Bodies: New Insights into the Surface Binding Energies for Elements in Plagioclase Feldspars

Our understanding of the ion-sputtering contribution to the formation of exospheres on airless bodies has been hindered by the lack of accurate surface binding energies (SBEs) of the elements in the various mineral and amorphous compounds expected to be on the surfaces of these bodies. The SBE for a given element controls the predicted sputtering yield and energy distribution of the ejecta. Here, we use molecular dynamics computations to provide SBE data for the range of elements sputtered from plagioclase feldspar crystalline end members, albite and anorthite, which are expected to be important mineral components on the surfaces of the Moon and Mercury. Results show that the SBE is dependent on the crystal orientation and the element’s coordination, meaning multiple SBEs are possible for a given element. Variation in the SBEs among the different surface positions has a significant effect on the predicted yield and energy distribution of the ejecta. We then consider sputtering by H, He, and a solar wind mixture of 96% H and 4% He. For each of these cases, we derive best-fit elemental SBE values to predict the ejecta energy distribution from each of the (001), (010), and (011) cleavage planes. We demonstrate that the He contribution to the sputtering yield cannot be accounted for by multiplying the 100% H results by some factor. Lastly, we average our results over all three possible lattice orientations and provide best-fit elemental SBE values that can be easily incorporated into sputtering yield models.

Dynamics Performance Research and Calculation of Speed Threshold Curve for High-Speed Trains Under Unsteady Wind Loads

Affected by strong wind environments, the vibration of trains will significantly intensify, which will severely impact the running quality of trains. To address such challenges, an improved wind load model is proposed in this paper to simulate the shock of strong wind on trains. The proposed model employs the integral approach to calculate the equivalent wind load on trains and applies it to the body of trains during the dynamics simulation process. Eventually, the two-level running quality threshold curve for passenger and freight trains is acquired through the conditional probability density function and the regularized regression model. This achievement covers train speed restrictions for wind speeds ranging from 0~25 m/s, providing a scientific basis for railway departments to adjust train speeds based on real-time wind speeds. It is of utmost importance for ensuring the safe and efficient operation of trains under strong wind conditions.

VALIDATION OF DYNAMIC MESSAGE VARIANT IN ADAPTIVE LOGGING METHOD

Technology, and software technology in particular, is one of the main drivers of progress in human society. It allows us to solve existing tasks more efficiently and find solutions for problems that were previously too complex to deal with. The outreach and importance of its influence on everyday life is hard to overstate. To be able to satisfy ever-growing demand software solutions become more complex and sophisticated, reaching millions users and solving numerous day to day tasks. But as a result new challenges appear, especially related to cybersecurity. And it is not only about integrity, availability and confidentiality aspects, but also – equally important – about control and observability. As the scale of software systems grows more and more, tracking their state and behavior becomes more challenging. This research takes a closer look at observability aspect of cybersecurity, in particular at adaptive logging method for software systems and its dynamic message variant which introduced the ability to have dynamic computations executed before outputting observational information about the system. The flexibility it introduces also makes possible for undesirable side effects to occur as the dynamic nature of such messages allows for execution of virtually any valid code samples. The main purpose of this work is to demonstrate a solution that would allow validation and prevent unwanted code execution. To achieve this an approach that uses analysis of abstract syntax trees with JSON-based validation logic is demonstrated. The natural tree-like structure of ASTs, as well as close resemblance between generated representation and JSON-schemas, allows for precise and easily configurable processing that reduces the possibility of unexpected behaviors. The integration into an existing formal basis of adaptive logging method is also demonstrated with provided justification for required additions and their specifics.

Priority/Demand-Based Resource Management with Intelligent O-RAN for Energy-Aware Industrial Internet of Things

The last decade has witnessed the explosive growth of the internet of things (IoT), demonstrating the utilization of ubiquitous sensing and computation services. Hence, the industrial IoT (IIoT) is integrated into IoT devices. IIoT is concerned with the limitation of computation and battery life. Therefore, mobile edge computing (MEC) is a paradigm that enables the proliferation of resource computing and reduces network communication latency to realize the IIoT perspective. Furthermore, an open radio access network (O-RAN) is a new architecture that adopts a MEC server to offer a provisioning framework to address energy efficiency and reduce the congestion window of IIoT. However, dynamic resource computation and continuity of task generation by IIoT lead to challenges in management and orchestration (MANO) and energy efficiency. In this article, we aim to investigate the dynamic and priority of resource management on demand. Additionally, to minimize the long-term average delay and computation resource-intensive tasks, the Markov decision problem (MDP) is conducted to solve this problem. Hence, deep reinforcement learning (DRL) is conducted to address the optimal handling policy for MEC-enabled O-RAN architectures. In this study, MDP-assisted deep q-network-based priority/demanding resource management, namely DQG-PD, has been investigated in optimizing resource management. The DQG-PD algorithm aims to solve resource management and energy efficiency in IIoT devices, which demonstrates that exploiting the deep Q-network (DQN) jointly optimizes computation and resource utilization of energy for each service request. Hence, DQN is divided into online and target networks to better adapt to a dynamic IIoT environment. Finally, our experiment shows that our work can outperform reference schemes in terms of resources, cost, energy, reliability, and average service completion ratio.

Theoretical study of the synergistic effect between glyceryl monooleate lubricant and carboxymethylcellulose in reducing the coefficient of friction of water-based drilling fluids.

Drilling fluids must reduce the coefficient of friction between the drilling equipment and the drilled rock or well casing. Friction forces become particularly relevant in drilling with a high angle gain, in which cases oil-based fluids are generally used. The latter are highly lubricating, but harmful to the environment. For environmental and economic reasons, there is great interest in the development of new additives that enable the use of water-based drilling fluids in all phases of well drilling. Preliminary experimental results show that there is a synergistic effect between glyceryl monooleate (GMO), normally used as lubricant additive, and carboxymethyl cellulose (CMC), a polysaccharide normally used in water-based drilling fluids as a rheological modifier, resulting in extremely low friction coefficients. This work aimed to clarify, through theoretical calculations, the interaction between CMC and GMO, as well as their role in reducing the coefficient of friction between the drilling equipment and the drilled rock when added to water-based fluids. Calculations based on density functional theory (DFT) were used to predict which, CMC or GMO, preferentially binds to the metal surface. The interactions between the polysaccharide and the surfactant were studied through a combination of classical molecular dynamics and DFT calculations. Finally, dynamic calculations were carried out involving fragments of the polysaccharide, the surfactant and hematite (Fe2O3) representing the metal surface, since in the experimental conditions the metal surface will be covered by a primary oxide layer. The results pointed to the preferential binding of CMC to hematite. Regarding the interaction between polymer and surfactant, it was found that the polar part of the GMO interacts with the CMC through hydrogen bonds while the nonpolar carbon chain remains close to the polymer due to hydrophobic interactions. Molecular dynamics calculations showed that GMO increases the binding energy of CMC to hematite and also that this increase in the binding energy is highly influenced by electrostatic interactions.

Systems biology and molecular modeling assisted exploration of the underlying mechanism of Safflower (Carthamus tinctorius L.) in the treatment of hearing loss

Hearing loss is the incapability to hear sound, either partially or fully. One potential natural remedy for hearing loss is the use of Carthamus tinctorius, commonly known as safflower, contains bioactive compounds, including flavonoids, phenolic acids, and terpenoids, which possess potent antioxidant and anti-inflammatory activities. This study uses network pharmacology to identify the potential therapeutic effects of these compounds on hearing loss. We identified 17 active compounds of C. tinctorius with favorable ADME properties through a litrature search. Potential targets for these compounds were found using databases like STITCH and Swiss Target Prediction, as well as the GeneCards database to retrieve hearing loss-related potential targets. A Venn diagram was drawn to determine shared targets, and GO enrichment and KEGG pathways analysis of 64 key targets were conducted DAVID database. Protein-protein interactions (PPIs) were analyzed via STRING database, and a compound-target-pathway network was created in Cytoscape. Molecular docking studies focused on one hub gene, namely, tumor necrosis factor (TNF) revealing that C. tinctorius’s compounds have high affinity for TNF, suggesting a potential therapeutic link to hearing loss. Finally, molecular dynamics simulations and calculations of binding free energy showed TNF_Beta Sitosterol and TNF_Campesterol were more stable than TNF_Cholesterol. Our findings indicate that C. tinctorius may have therapeutic potential for hearing loss by targeting key genes and pathways. However, further in-vivo and in-vitro studies are needed to confirm these findings and determine optimal treatment parameters.