MD Methods Research Articles

Determining the solubility parameter and thermodynamic properties of beta-carotene in superheated water solvent by experimental and MD simulation methods

In this study, for the first time, the solubility of beta-carotene in green solvent was simulated using the molecular dynamics method. Superheated water was used as a solvent. The simulations were performed at different temperatures and a constant pressure of 2 MPa using Lammps software. The behavior of beta-carotene in solvent was investigated. The results showed that the dissolution process of beta-carotene in superheated water is endothermic and non-spontaneous, and increasing the temperature increases the dissolution of beta-carotene in superheated water. To ensure the results, the solubility of beta-carotene in superheated water was calculated using the static experimental method. The absolute average relative deviation between simulated and experimental beta-carotene solubility data in superheated water was 14.5 %. By increasing the temperature to 408.15 K, water under pressure became a solvent with the same behavior as organic solvents, and the solubility of beta-carotene, which was a lipophilic and insoluble compound in water, increased by about 80 times compared to ambient temperature. Accurately determining the solubility of this valuable medicinal plant in a green solvent can be used in the wide production of pharmaceutical, food, and cosmetic products.

Study on the variability of oxygen adsorption behavior in coal gangue based on pore size structure

To investigate the adsorption and migration behavior of oxygen in coal gangue with different pore sizes, this study characterizes the multiscale morphology of coal gangue pores and fractures using SEM NMR, and low-temperature N2 (77 K) adsorption methods. As well, the study simulates the adsorption and diffusion behavior of O2 within the pore structures of coal gangue based on GCMC and MD methods. The study examines the oxygen adsorption characteristics across different pore sizes and analyzes the mass transfer mechanisms during oxygen diffusion. Results indicate that the pores in coal gangue are predominantly micropores within the 1–10 nm range. As pore size increases, the absolute adsorption amount of oxygen increases while the isosteric heat of adsorption decreases. The isosteric heat of adsorption in coal gangue models with different pore sizes is less than 42 kJ/mol, indicating the physical adsorption of oxygen within the pores. Oxygen shows adsorption layering perpendicular to the coal gangue surface, with adsorption density distribution differences decreasing and adsorption capacity weakening as pore size increases. The O2 adsorption isotherms in coal gangue follow Langmuir adsorption principles, with oxygen saturation adsorption decreasing as absolute adsorption increases. The confinement effect of coal gangue on oxygen weakens as pore size increases, and the impact of increasing pore size on oxygen diffusion is stronger than adsorption. These findings are significant for understanding the microscopic adsorption and diffusion behavior of O2 in coal gangue pores and fractures and are crucial for accurately preventing and managing spontaneous combustion in coal gangue piles.

Development of phytotherapeutic nanoformulation containing Gypsophila eriocalyx and its evaluation as a candidate formulation for osteoporosis treatment on human bone marrow stem cells.

Osteoporosis, one of the common bone diseases, manifests itself as a decrease in bone mass. Recently, the use of medicinal plants in the search for effective and low-toxicity therapeutics for the prevention or treatment of osteoporosis has become a trending topic. In this study, we aim to prepare a controlled drug carrier system loaded with Gypsophila eriocalyx to determine its potential for anti-osteoporosis applications. Gypsophila eriocalyx extract (GEE) was prepared, and components were determined. The molecular interactions of the components with Cathepsin K (CatK), which is used as a target in drug development against osteoporosis, were revealed by in silico molecular docking and MD methods. ADMET profiles were also examined. GEE-loaded chitosan nanoparticles (CNPs) were synthesized. The nanoparticles' morphology, encapsulation efficiency, loading capacity, release profile, average size, polydispersity index, and zeta potentials were determined. The cytotoxic effects of GEE and GEE-loaded CNPs on the L929 and osteogenic proliferation profiles on human bone marrow stem cells (hBMC) were examined. The MD analysis revealed no breaks or atomic changes in the dynamic system, and the docking analysis confirmed the continued interaction of identical residues. It was determined that the GEE-loaded CNP formulation was produced successfully, had no toxic effect on the L929, and had an osteogenic proliferation effect on hBMC. In line with the in vitro and in silico results obtained, it was evaluated that GEE-loaded CNPs can be used as a controlled drug release system as a candidate formulation with phytotherapeutic properties for osteoporosis treatment.q1.

Density functional theory and ReaxFF MD study on steam-induced nitrogen migration mechanism during char gasification

The formation of nitrogen-containing species during char gasification is crucial for emission of nitrogenous pollutants. In this work, the detailed nitrogen migration mechanism during char gasification is studied. Density functional theory (DFT) coupled with ReaxFF MD methods are used to conduct an in-depth analysis on the intrinsic reaction mechanism during Char(N) and steam interaction. DFT results show that orbital electrons of carbon atoms on char surface are driven towards nitrogen atoms by nitrogen functional groups. The electron density of adjacent carbon atoms is weakened, which has a positive charge. Orbital electron properties show that the band energy gaps of three Char(N) models are 3.063 eV, 1.092 eV and 3.328 eV, indicating the reactivity order for three Char(N) models is as follows: Char(N)-2＞Char(N)-1＞Char(N)-3. DFT calculation indicates that the interaction between Char(N) and steam reduces unsaturated carbon atoms and lower the char decomposition activity, which will inhibit the yield of HCN. In contrast, through hydrogen transfer reactions, nitrogen atoms are easily combined with hydrogen atoms, which is more conducive to the formation of ammonia. ReaxFF MD modeling proves that HCN is the main product for Char(N) decomposition under inert atmosphere. Under steam atmosphere, nitrogen atoms in char are more likely to be converted into amino products. The induction of steam provides a large number of active hydrogen radicals, which is able to attack the nitrogen atoms of char and form N–H bonds, thus promoting the formation of ammonia.

Impact of SOFC anode carbon deposition and hydrogen adsorption on the cell performance by molecular simulation.

This study primarily investigates the changes in carbon adsorption capacity and hydrogen adsorption capacity on the anode catalyst surface when using methane fuel and mixed gas fuel as the anode fuel for SOFC systems. To reduce the carbon adsorption capacity of the commonly used anode catalyst-nickel-based catalysts-towards hydrocarbon fuels, copper and gold are doped into the nickel-based catalysts to compare the effects on carbon and hydrogen adsorption capacities. Moreover, aside from calculating the carbon and hydrogen adsorption capacities, this project also evaluates the impact of mixed gas effects and doping effects on SOFC performance through the analysis of hydrogen diffusion coefficients and performance polarization curves. The findings reveal a noteworthy enhancement in the diffusion coefficient of syngas within the Au-doped Ni catalyst, showing an improvement of up to 45.46% at 973K. Furthermore, the electrical power generated by syngas in the Au-doped Ni catalyst at 973K demonstrates an increase of up to 12.06%. This study primarily employs DFT to calculate the carbon and hydrogen adsorption energies on methane, utilizing CASTEP for the calculations. During these calculations, the adsorption energy is determined through a three-layer surface approach, in conjunction with the Kohn-Sham equations, combining the Generalized Gradient Approximation and ultrasoft pseudopotentials for TS-search calculations. On the other hand, this project will analyze the diffusion coefficient of hydrogen on the anode catalyst using MD methods combined with the ReaxFF potential field, with GULP being utilized to complete all dynamics calculation theories. Finally, the project will analyze the performance of SOFC cells, incorporating relevant numerical equations with Matlab for numerical analysis.

A computational method for rapid analysis polymer structure and inverse design strategy (RAPSIDY).

Tailoring polymers for target applications often involves selecting candidates from a large design parameter space including polymer chemistry, molar mass, sequence, and architecture, and linking each candidate to their assembled structures and in turn their properties. To accelerate this process, there is a critical need for inverse design of polymers and fast exploration of the structures they can form. This need has been particularly challenging to fulfill due to the multiple length scales and time scales of structural arrangements found in polymers that together give rise to the materials' properties. In this work, we tackle this challenge by introducing a computational framework called RAPSIDY - Rapid Analysis of Polymer Structure and Inverse Design strategY. RAPSIDY enables inverse design of polymers by accelerating the evaluation of stability of multiscale structure for any given polymer design (sequence, composition, length). We use molecular dynamics simulations as the base method and apply a guiding potential to initialize polymers chains of a selected design within target morphologies. After initialization, the guiding potential is turned off, and we allow the chains and structure to relax. By evaluating similarity between the target morphology and the relaxed morphology for that polymer design, we can screen many polymer designs in a highly parallelized manner to rank designs that are likely to remain in that target morphology. We demonstrate how this method works using an example of a symmetric, linear pentablock, AxByAzByAx, copolymer system for which we determine polymer sequences that exhibit stable double gyroid morphology. Rather than trying to identify the global free-energy minimum morphology for a specific polymer design, we aim to identify candidates of polymer design parameter space that are more stable in the desired morphology than others. Our approach reduces computational costs for design parameter exploration by up to two orders-of-magnitude compared to traditional MD methods, thus accelerating design and engineering of novel polymer materials for target applications.

Parametrization of embedded-atom method potential for liquid lithium and lead-lithium eutectic alloy

Liquid lead-lithium eutectic remains as a promising candidate for various breeding-blanket designs in future nuclear-fusion technologies. The lack of a generalized theory of interatomic forces in the liquid state is reflected on the wide variety of proposed functional forms to describe interatomic interactions even in simple liquids. Computer simulations facilitate the study of liquid metal properties, due to mathematical and experimental challenges. A classical-MD EAM potential is parametrized using mechanical and non-mechanical (melting-point) properties to minimize the arbitrariness of functional forms, where the employed pair potential stems from the liquid-state theory to avoid the issue of the uniqueness of the potential. Enhanced performance is obtained for liquid density, energy, structure, diffusivity and shear viscosity of Li, and their temperature-dependencies. In a similar manner, reference experimental and ab initio MD data are used to parametrize a functional to describe Pb-Li pairwise interactions in liquid Pb-Li alloy, which is used with the derived EAM of liquid Li and a reference EAM of liquid Pb to investigate properties of liquid Pb-Li alloy. Enhanced transferability characteristics are obtained for low-in-lithium liquid Pb-Li melts, where Coulombic interactions are negligible. In specific, the exhibited behaviour of Li in liquid lead-lithium eutectic is consistent with findings from ab initio MD methods, and drastically different from predictions of previous C-MD studies which suggested a substantial segregation of Li atoms instead of dispersion. It is concluded that the functional form of the pair potential and its uniqueness influence both the pure liquid-metal properties and the validity of the potential transferability in multi-component systems, where a theoretical functional results in enhanced performance in pure and alloyed liquid systems.

Molecular dynamics simulations and machine-learning assisted study of the reaction path bifurcation: Application to the intramolecular Diels–Alder cycloaddition between cyclobutadiene and butadiene

The intramolecular Diels–Alder cycloaddition between cyclobutadiene and butadiene, which involves post-transition-state bifurcation (PTSB), has been investigated using the ring-polymer molecular dynamics (RPMD), classical MD and quasi-classical trajectory (QCT) simulations, and supervised machine-learning (ML) technique. The branching fraction of this reaction strongly depends on the simulation temperature. While QCT, classical MD and RPMD simulations performed at room temperature, starting from the ambimodal transition state (TS), showed the similar dynamics, QCT overestimated the minor branching fraction at low temperature. The supervised machine-learning analysis revealed that the initial coordinates and momenta for low frequency modes at the ambimodal TS contribute to the branching dynamics. The classical MD and RPMD methods follow similar conditions to quantum Boltzmann distributions, whereas the artificially localized phase distribution, considering that the zero-point energy is wedged into the classical particles. As a result, the QCT method can provide inadequate bifurcation dynamics, such as the overestimation of the minor product.

States of silicon nanoclusters containing carbon impurities

The structural and electronic states of defective complexes in the Si29 cluster with the participation of carbon and hydrogen atoms were determined by the method of non-conventional strong binding (MNSB) in combination with the method of molecular dynamics. It is shown that carbon atoms in silicon clusters form a bridge bond with two silicon atoms and localized in a hexagonal position at the center of the cell, forming a defect of the Si29 : Ci type. The introduction of hydrogen into a silicon cluster results in the formation of a defective Ci-H-Si complex and a decrease of binding energy of the Si29 : Ci defect. Based on the calculations, it was found that presence of leads to carbon gives shallow levels in the band gap of nano-silicon, and the defective carbon-hydrogen complex in a hydrogenated cluster, depending on the charge state of the defective complex. Moreover this exhibits both deep and shallow levels. Keywords: MD and MNSB methods, silicon nano-clusters, hydrogenated cluster, structural defects, ab initio methods, carbon and hydrogen atoms, spatial structure, shallow and deep levels.

A comprehensive insight into the effects of caffeic acid (CA) on pepsin: Multi-spectroscopy and MD simulations methods

The interaction between caffeic acid (CA) and pepsin was investigated using multi-spectroscopy approaches and molecular dynamic simulations (MDS). The effects of CA on the structure, stability, and activity of pepsin were studied. Fluorescence emission spectra and UV–vis absorption peaks all represented the static quenching mechanism of pepsin by CA. Moreover, the fluorescence spectra displayed that the interaction of CA exposed the tryptophan chromophores of pepsin to a more hydrophilic micro-environment. Consistent with the simulation results, thermodynamic parameters revealed that CA was bound to pepsin with a high binding affinity. The Van der Waals force and Hydrogen bond interaction were the dominant driving forces during the binding process. The circular dichroism (CD) spectroscopy analysis showed that the CA binding to pepsin decreased the contents of α-Helix and Random Coil but increased the content of β-sheet in the pepsin structure. Accordingly, MD simulations confirmed all the experimental results. As a result, CA is considered an inhibitor with adverse effects on pepsin activity.

Conformational Analysis of Tyrosyl-Lysyl-Threonine Tripeptide Using MM, MD and QM Methods and Its Hyperpolarizability Study

Peptides are important structures that offer important opportunities for therapeutic interventions in various diseases. Tyrosyl-Lysyl-Threonine is an important peptide structure that contains the antiviral, antioxidant and anticancer properties of the amino acids in its structure. Examination of the conformational structure, which has great importance on both the ability of the molecule to fulfill its biological functions and electronic properties, is important for molecular studies. In this study, determination of the stable conformations and optimization of the most stable structure of Tyrosyl-Lysyl-Threonine molecule was carried out using molecular mechanical and quantum mechanical methods. With molecular dynamics simulation studies, the changes in conformational structure, RMSD and Rg values in different environments were monitored for 10 ns. Additionally, the hyperpolarizability study of Tyrosyl-Lysyl-Threonine were carried out. As a result of this study, it was aimed to determine the optimized geometry of the tripeptide, its conformational changes and nonlinear optical properties.

The role of Acinetobacter baumannii CarO outer membrane protein in carbapenems influx

The gram-negative strain Acinetobacter baumannii is a cocobacillus, non-motile and aerobic organism that is often found in nosocomial infections. Many institutions worldwide such as WHO are grappling with antibiotic resistance A. baumannii. Therefore, in recent years, there have been many studies in the literature about antibiotic resistance mechanisms. We studied the specificity of carbapenems for CarO, an outer membrane protein associated with imipenem-resistance that was strongly related to a decrease in CarO expression level or changes in protein structure. The specificity of five different carbapenems, imipenem, biapenem, ertapenem, faropenem, and meropenem, against the A. baumannii ATCC-17978 CarO protein, as well as the specificity of imipenem for five different types Type-1, Type-2, Type-3, Type-4, and ATCC-17978 CarO protein, were investigated using computational methods. In this study, homology modeling, molecular docking, membrane–protein complex building, and 800 ns long MD simulation methods were followed. The interactions of imipenem with the extracellular region of five different forms of CarO protein were investigated in this study, as well as five different antibiotic binding profiles to the model organism ATCC-17978 CarO protein. The mechanism of CarO influx has been revealed with this study at the molecular level and this data is intended to be used in future research, mutagenesis, and clinical trials.

The effect and mechanism of four drying methods on the quality of tilapia fillet products

AbstractTilapia (Oreochromis niloticus) holds a major position in the fishery market worldwide. This study aimed to investigate the effect of four drying methods, namely vacuum freeze (VFD), vacuum microwave (VMD), hot air (HAD) and microwave (MD), on texture, amino acids, microstructure, lipid oxidation and protein degradation of tilapia fillets. The results showed that vacuum combined with refrigeration (VFD) or VMD had better color, chromatic aberration, shrinkage ratio and microstructure. The total essential amino acid content (31.16%), α‐helical (28.06%) structure and protein denaturation temperature of nonthermal VFD were higher than the VMD, HAD and MD methods. In thermal drying processing, VMD had some advantages in protein stability, microstructure, lipid oxidation and flavor compared with HAD and MD products. Therefore, a combined drying method was discovered to have prospects for use in tilapia processing. VFD was considered the appropriate nonthermal drying method of fillets with high product quality and protein stability. Meanwhile, considering the advantages of its efficiency, quality and energy consumption, the VMD had the best potential of the four methods employed to dry tilapia fillets.

Diamane quasicrystals

Here we propose the first two-dimensional carbon quasicrystal made entirely of sp3-hybridized atoms, namely diamane quasicrystal. This nanostructure is based on incommensurate lattice of two graphene layers twisted by 30° with respect to each other (well-known graphene quasicrystal) with totally hydrogenated or fluorinated surfaces of bilayer graphene (similar to formation of AB-stacked diamane by means of applying high pressure treatment). We describe in detail the features of atomic structure appearing during the formation of quasicrystal. Thermodynamic stability, electronic and mechanical characteristics in comparison with both periodic approximants and AB-stacked diamanes via DFT and MD methods are studied and discussed. Proposed diamane quasicrystals exhibit unique mechanical properties: they are stiffer and more brittle than AB-stacked diamane. Our study shows that quasicrystalline diamane is a prospective material that opens a new way towards the synthesis of inorganic quasicrystals of various compositions with unique set of physical and chemical properties.

Comparison of atomic simulation methods for computing thermal conductivity of n-decane at sub/supercritical pressure

n-Decane is the most commonly used component in surrogate to study the properties of RP-3 aviation kerosene for regenerative cooling systems and the engine injection systems. In this paper, the equilibrium molecular dynamics (EMD) and the reverse non-equilibrium MD (RNEMD) methods are adopted and compared in the prediction of the thermal conductivity of the sub/supercritical n-decane. Four different united atom (UA) force field models and four all-atomic force field models are compared in the EMD simulations. It is found that the UA models predict much better than the all-atom force field models and EMD methods show better prediction accuracy than the RNEMD methods with the same UA models. The SKS model has the best prediction accuracy among all the force field models for EMD and RNEMD simulations. The MD results are compared with experimental data of RP-3 aviation kerosene; it is obtained that the overall averaged absolute relative deviation (AARD) of EMD simulations with the SKS force field model for the single component substitute of aviation kerosene by n-decane is 2.05%. Moreover, the radial distribution functions are calculated via MD simulations to make a better understanding of the temperature dependences of the thermal conductivity at sub/supercritical pressure of n-decane at a molecular level. The findings of this work could provide important guidance for the investigation of thermal conductivity of n-alkanes and n-alkane-based fuels.

Computational study of Li3BO3 and Li3BN2 I: Electrolyte properties of pure and doped crystals

Both ${\mathrm{Li}}_{3}{\mathrm{BO}}_{3}$ and ${\mathrm{Li}}_{3}{\mathrm{BN}}_{2}$ materials have promising properties for use in all-solid-state batteries and other technologies dependent on electrolytes with significant ionic conductivity. As the first of a two-part study, this paper reports the analysis of detailed simulations of Li ion diffusion in the monoclinic forms of these materials. Using both NEB and MD methods, it is clear that Li ion migration via vacancy mechanisms provides the most efficient ion transport in each material. While the results suggest that interstitial defects in these materials do not play a direct role in Li ion migration, their relative stability seems to enhance vacancy production via the formation of Frenkel-type defects. This may partially explain why the Li ion conductivities computed from MD simulations of samples initially containing a single Li ion vacancy are in reasonable agreement with measured values of this work for ${\mathrm{Li}}_{3}{\mathrm{BO}}_{3}$ and those reported in the literature for poorly crystalline samples of both materials. The possibility of increasing vacancy concentrations by substitutional doping (F for O in ${\mathrm{Li}}_{3}{\mathrm{BO}}_{3}$ and C for B in ${\mathrm{Li}}_{3}{\mathrm{BN}}_{2}$) is also examined, finding simulated conductivities comparable to those of the ideal vacancy model.

Carbon-Free Solution-Based Doping for Silicon.

Molecular doping is a method to dope semiconductors based on the use of liquid solutions as precursors of the dopant. The molecules are deposited on the material, forming a self-ordered monolayer that conforms to the surfaces, whether they are planar or structured. So far, molecular doping has been used with precursors of organic molecules, which also release the carbon in the semiconductor. The carbon atoms, acting as traps for charge carriers, deteriorate the doping efficiency. For rapid and extensive industrial exploitation, the need for a method that removes carbon has therefore been raised. In this paper, we use phosphoric acid as a precursor of the dopant. It does not contain carbon and has a smaller steric footprint than the molecules used in the literature, thus allowing a much higher predetermined surface density. We demonstrate doses of electrical carriers as high as 3 × 1015 #/cm2, with peaks of 1 × 1020 #/cm3, and high repeatability of the process, indicating an outstanding yield compared to traditional MD methods.

Sphingomonas sp. KT-1 PahZ2 Structure Reveals a Role for Conformational Dynamics in Peptide Bond Hydrolysis.

Poly(aspartic acid) (PAA) is a common water-soluble polycarboxylate used in a broad range of applications. PAA biodegradation and environmental assimilation were first identified in river water bacterial strains, Sphingomonas sp. KT-1 and Pedobacter sp. KP-2. Within Sphingomonas sp. KT-1, PahZ1KT-1 cleaves β-amide linkages to oligo(aspartic acid) and then is degraded by PahZ2KT-1. Recently, we reported the first structure for PahZ1KT-1. Here, we report novel structures for PahZ2KT-1 bound to either Gd3+/Sm3+ or Zn2+ cations in a dimeric state consistent with M28 metallopeptidase family members. PahZ2KT-1 monomers include a dimerization domain and a catalytic domain with dual Zn2+ cations. MD methods predict the putative substrate binding site to span across the dimerization and catalytic domains, where NaCl promotes the transition from an open conformation to a closed conformation that positions the substrate adjacent to catalytic zinc ions. Structural knowledge of PahZ1KT-1 and PahZ2KT-1 will allow for protein engineering endeavors to develop novel biodegradation reagents.

PseKNC and Adaboost-Based Method for DNA-Binding Proteins Recognition

DNA-binding proteins are an essential part of the DNA. It also an integral component during life processes of various organisms, for instance, DNA recombination, replication, and so on. Recognition of such proteins helps medical researchers pinpoint the cause of disease. Traditional techniques of identifying DNA-binding proteins are expensive and time-consuming. Machine learning methods can identify these proteins quickly and efficiently. However, the accuracies of the existing related methods were not high enough. In this paper, we propose a framework to identify DNA-binding proteins. The proposed framework first uses PseKNC (ps), MomoKGap (mo), and MomoDiKGap (md) methods to combine three algorithms to extract features. Further, we apply Adaboost weight ranking to select optimal feature subsets from the above three types of features. Based on the selected features, three algorithms (k-nearest neighbor (knn), Support Vector Machine (SVM), and Random Forest (RF)) are applied to classify it. Finally, three predictors for identifying DNA-binding proteins are established, including [Formula: see text], [Formula: see text], [Formula: see text]. We utilize benchmark and independent datasets to train and evaluate the proposed framework. Three tests are performed, including Jackknife test, 10-fold cross-validation and independent test. Among them, the accuracy of ps+md is the highest. We named the model with the best result as psmdDBPs and applied it to identify DNA-binding proteins.

Atomic insights into the thermal runaway process of hydrogen peroxide and 1,3,5-trimethybenzene mixture: Combining ReaxFF MD and DFT methods

The explosive hazard of hydrogen peroxide (H2O2) and organics mixtures had drawn much attention, but the mechanism is still unclear. In this work, the atomic insights into the thermal runaway process of H2O2 and 1,3,5-trimethylbenzene (TMB) mixture was conducted using a new approach of combining reactive molecular dynamics (ReaxFF MD) and density function theory (DFT). The detailed reaction pathways were obtained through ReaxFF MD. The kinetic and thermal properties of main reaction steps were examined by DFT. This work divided the thermal runaway process into two stages. In stage I, H2O2 molecules were decomposed first to generate ·OOH and ·OH free radicals. The ·OH radicals induced the initial oxidation of TMB molecular through H-abstraction and ·OH-combine reaction steps with the highest thermal energy of 921.76 kJ/mol released, evoking the opening and cracking of benzene ring. In stage II, once the generated small molecules were further oxidized, the reactions showed a runaway for the massive thermal energy released, which explains the mechanism of larger potential risk of H2O2-organics mixture. Notably, ·OH is the most crucial free radical carrier for the whole reaction process, the explosion hazard will be inhibited or weakened if the concentration of ·OH radical is controlled. It is expected that this work will help researchers and industrial practitioners to better understand the intrinsic thermal hazard of H2O2-organics, and provide valuable guidance for the further development of efficient explosion suppression methods.