Predictive modeling of critical temperatures in magnesium compounds using transfer learning

This study presents a transfer learning approach for discovering potential Mg-based superconductors utilizing a comprehensive target dataset.Initially,a large source dataset(Bandgap dataset)comprising approximately∼75k compounds is utilized for pretraining,followed by fine-tuning with a smaller Critical Temperature(T_(c))dataset containing∼300 compounds.Comparatively,there is a significant improvement in the performance of the transfer learning model over the traditional deep learning(DL)model in predicting Tc.Subsequently,the transfer learning model is applied to predict the properties of approximately 150k compounds.Predictions are validated computationally using density functional theory(DFT)calculations based on lattice dynamics-related theory.Moreover,to demonstrate the extended predictive capability of the transfer learning model for new materials,a pool of virtual compounds derived from prototype crystal structures from the Materials Project(MP)database is generated.T_(c) predictions are obtained for∼3600 virtual compounds,which underwent screening for electroneutrality and thermodynamic stability.An Extra Trees-based model is trained to utilize E_(hull)values to obtain thermodynamically stable materials,employing a dataset containing Ehull values for approximately 150k materials for training.Materials with Ehull values exceeding 5 meV/atom were filtered out,resulting in a refined list of potential Mg-based superconductors.This study showcases the effectiveness of transfer learning in predicting superconducting properties and highlights its potential for accelerating the discovery of Mg-based materials in the field of superconductivity.

An integrated machine learning model for accurate and robust prediction of superconducting critical temperature

Discovering new superconductors via traditional trial-and-error experimental approaches is apparently a time-consuming process,and the correlations between the critical temperature(Tc) and material features are still obscure.The rise of machine learning(ML) technology provides new opportunities to speed up inefficient exploration processes,and could potentially uncover new hints on the unclear correlations.In this work,we utilize open-source materials data,ML models,and data mining methods to explore the correlation between the chemical features and Tcvalues of superconducting materials.To further improve the prediction accuracy,a new model is created by integrating three basic algorithms,showing an enhanced accuracy with the coefficient of determination(R2) score of 95.9 % and root mean square error(RMSE) of 6.3 K.The average marginal contributions of material features towards Tcvalues are estimated to determine the importance of various features during prediction processes.The results suggest that the range thermal conductivity plays a critical role in Tcprediction among all element features.Furthermore,the integrated ML model is utilized to screen out potential twenty superconducting materials with Tcvalues beyond 50.0 K.This study provides insights towards Tcprediction to accelerate the exploration of potential high-Tcsuperconductors.

Effects of charge size on explosives thermal initiation critical temperature under constrained conditions

In order to study the relationship between charge size and thermal initiation critical temperature of explosive in defined conditions,cook-off test about JH explosive was carried out at a heating rate of 1 ℃/min using self-designed cook-off experiment setup based on thermostatic control technology.Numerical simulation was conducted to study the effects of different charge sizes on thermal initiation critical temperature of explosives with FLUENT software.Experiment results show that there is a thermal initiation critical temperature in cook-off bomb.Simulation results show that when the ratio of the length to diameter of explosives grains is a fixed value,the thermal initiation critical temperature of explosives decreases with the increase of the diameter of explosives grains.When the grains diameter of explosives increase up to a certain value,the influence of charge size on thermal initiation critical temperature tends to be weakened.Charge size has no influence on the ignition point of explosives.The ignition point is always in the center of the grain.

Estimation of Critical Temperature of Thermal Explosion for Energetic Materials Based on Non-isothermal Kinetic Equation dα/dt =A_0 exp(bT)[1+(T–T_0 )b]f(α)

Critical temperature（Tb） of thermal explosion for energetic materials is estimated from Semenov＇s thermal explosion theory and the non-isothermal kinetic equation da/dt=Aoexp（bT）[1＋（T-T0）b][（a） deduced via reasonable hypotheses, where To is the initial point of the deviation from the baseline of DSC curve. The final formula is （Tb-Te0）{ 1＋1/[1＋（ Tb-T00）b]}=1. We can easily obtain the initial temperature（T0/） and onset temperature（Tci） from the non-isothermal DSC curves, the values of Too and Tc0 from the equation TOi or ei=T00 or c0＋α1βi＋a2βi^2＋…＋aL-2L-2βiL-2, i=1,2,…L, the value of b from the equation： In[β/（Tei-T0i）]=ln[A0/G（a）]＋bTei, so as to calculate the value of Tb. The result obtained with this method coincides completely with the value of Tb obtained by Hu-Yang-Liang-Wu method.

A Study of Estimating the Safe Storage Life, Self-accelerating Decomposition Temperature and Critical Temperature of Thermal Explosion of Double-base Propellant Using Isothermal and Non-isothermal Decomposition Behaviours

A method of estimating the safe storage life （τ）, self-accelerating decomposition temperature （TsADT） and critical temperature of thermal explosion （Tb） of double-base propellant using isothermal and non-isothermal decomposition behaviours is presented. For double-base propellant composed of 56±1wt% of nitrocellulose （NC）, 27±0.5wt% of nitroglycerine （NG）, 8.15±0.15wt% of dinitrotoluene （DNT）, 2.5±0.1wt% of methyl centralite, 5.0±0.15wt% of catalyst and 1.0±0.1wt% of other, the values of r of 49.4 years at 40℃, of TSAOT of 151.35℃ and of Tb of 163.01℃ were obtained.

Determination of the Critical Temperature and Critical Pressure of Five Compounds

The critical properties of five compounds, including propanal,butanal, 1-pentanal, 2-methel butanal and trimer of ethanal, weredetermined for the first time by a new capillary quick-flow method.The apparatus was improved with a capillary tube and checked withhexane and 10heptene as standard reagents. The experimental resultsproved that the determination of critical properties by quick-flowmethod with a capillary tube apparatus was successful.

Minimum secure speed of fully mechanized coal face based on critical temperature of coal spontaneous combustion

The critical temperature theory of spontaneous combustion of coal and the numerical simulation method are used to explore the minimum secure speed of fully mechanized coal face to prevent the spontaneous combustion in goaf. Combined with the actual situation of workface 31005 in a coal mine, the highest temperatures in goal at different advancing speeds were obtained by the numerical simulation of spontaneous combustion in goal, and then a power function equation between the highest temperature and the advancing speed was achieved by regression analysis. The advancing speed corresponding to the critical temperature value was taken as the minimum safe speed of workface based on the equation. Finally, the accuracy and reliability of the speed were verified by the actual advancing process of workface 31005. The results of this research show that the new judgment method of the minimum safety speed has a higher value to be applied in the field.

Estimation of Critical Rate of Temperature Rise for Thermal Explosion of First Order Autocatalytic Decomposition Reaction Systems by Using Non-isothermal DSC

A method of estimating the critical rate of temperature rise for the thermal explosion of first order autocatalytic decomposition reaction systems by using non-isothermal DSC is presented. The information was obtained on the increasing rate of temperature for the first order autocatalytic decomposition of nitrocellulose containing 13.86% nitrogen converting into the thermal explosion.

STUDY ON AUSTENITE-FERRITE TRANSFORMATION WITHIN CRITICAL TEMPERATURE REGION

his paper deals with the phase trans formation of austenite to ferrite within the critical temperature region(between Ac1 and Ac3).The results show that the volume fraction of trans formation of ferrite formed isothermally from austenite is mainly varied with the austenitizing temperature.The higher the austenitizing temperature,the more volume fraction of the ferrite formed isothermally from austenite.Besides,the phase trans formation of austenite to ferrite within the critical temperature region was checked by austenitizing isothermal time.The volume fraction of ferrite formed isothermally from austenite within the critical temperature region for different isothermal time has heen examined experimen tally.The lglg(l-fv)-1 vs lgt relation does not follow the Avrami equation strictly and consists of two straight lines.

Estimation of Critical Temperature of Thermal Explosion for Trinitromethyl Explosives by Non-isothermal DSC

Two general expressions and their six derived formulae for estimating the critical temperature（Tb） of thermal explosion for energetic materials（EMs） were derived from the Semenov＇s thermal explosion theory and eight non-isothermal kinetic equations via reasonable hypothesis. We can easily obtain the values of the initial temperature（T0i） at which DSC curve deviates from the baseline of the non-isothermal DSC curve of EMs, the onset temperature（Tei）, the exothermic decomposition reaction kinetic parameters and the values of Too and Te0 from the equation Toiorei=Tooore0＋α1β1＋α2β2＋...＋αL-2βi^L-2, i=1, 2, …, L and then calculate the values of Tb by means of the six derived formulae. The results obtained with the six derived calculating methods for six trinitromethyl explosives： bis（2,2,2- trinitroethyl-N-nitro） ethylene diamine（BTNEDA）, 2,2,2-trinitroethyl-4,4,4-trinitrobutyrate（TNETB）, bis（2,2,2- trinitroethyl） formal（BNTF）, bis（2,2,2-trinitroethyl-nitramine）（BTNNA）, 2,2,2-trinitroethyl-2,2,2-trinitroethyl-N- nitroamino acetate（TNTNNA） and tetrakis [2,2,2-trinitroethyl] orthoester（TTNOE） agree well with each other.

Size Effects of the Critical Temperature in Ferroelectric Thin Films

The size effects of the critical behaviors for the systems of interacting spins are discussed extensively inliterature.In this paper,the finite-size dependence of the critical temperature and susceptibility of the ferroelectric thinfilm are investigated numerically based on the four-state Potts model with the nearest-neighbor interactions between thedipole moments.The four orientations of the domains exist in the ferroelectric film and the movement of the domainwalls determines the polarization switching process besides the boundary conditions of the film.The critical exponentsare obtained and our investigations show that the boundary conditions play the important roles for the ferroelectricproperties of the thin films and the critical behavior of the thin films strongly depends on the feature of the surface.

A comparison of the pitting corrosion resistances of the 304 and new 200 series of stainless steels by potential dependent critical pitting corrosion temperatures

This study researched the relationship between the applied potential and the critical pitting temperature （CPT） of the 304 and new 200 series of stainless steels. The fluctuation about the potential dependent CPT for the stainless steels was investigated and the CPT range was obtained. The difference between the potential dependent CPTs of the 304 and 200 series of stainless steels with an applied potential of 100 mV （ vs SCE）, were presented, and by this means the pitting corrosion resistances of them were compared.

CALCULATION OF CRITICAL EXPONENT β(L) OF MAGNETIC THIN FILMS BY USING ISING MODEL

The variational cumulant expansion developed in recent years has been extended to treat the Ising model in statistical physics.In this paper,a detailed calculation of the critical temperature T c (L) and critical exponent β(L) for the magnetic film of L layers are presented by means of the variational cumulant expansion.For L >1,the results of our theoretical calculations are in approximate coincidence with the experimental ones made before,and for the special case of L =1 (2 D),the results of the calculation are identical to the data from other reports.

Crystal structure graph neural networks for high-performance superconducting critical temperature prediction

The utilization of machine learning methods to predict the superconducting critical temperature(T_(c))traditionally necessitates manually constructing elemental features,which challenges both the provision of meaningful chemical insights and the accuracy of predictions.In this work,we introduced crystal structure graph neural networks to extract structure-based features for T_(c)prediction.Our results indicated that these structure-based models outperformed all previously reported models,achieving an impressive coefficient of determination(R^(2))of 0.962 and a root mean square error(RMSE)of 6.192 K.From the existing Inorganic Crystal Structure Database(ICSD),our model successfully identified 76 potential high-temperature superconducting compounds with T_(c)≥77 K.Among these,Tl_(5)Ba_(6)Ca_(6)Cu_(9)O_(29)and TlYBa_(2)Cu_(2)O_(7)exhibit remarkably high T_(c)values of 108.4 and 101.8 K,respectively.This work provides a perspective on the structure-property relationship for reliable T_(c)prediction.

Uncertainties of critical temperatures based on higher-order fluctuations of the largest fragment charge

The new signature of liquid-gas phase transition has been well indicated by the higher-order fluctuations of the largest fragment charge,but the uncertainties of critical temperatures based on this signature have not been revealed.This study extracts the critical temperatures of liquid-gas phase transition in nuclear reactions and investigates their uncertainties.Utilizing the isospin-dependent quantum molecular dynamics model in conjunction with the statistical model GEMINI enables us to describe the dynamical path from the initial to the final state.An isotope thermometer and a quantum fluctuation thermometer are employed to extract the nuclear temperature.The higher-order fluctuations of the largest fragment charge and critical temperatures are studied in^(124)Sn+^(120)Sn collisions ranging from 400 to 1000 MeV/nucleon and^(124)Sn+AZ collisions at 600 MeV/nucleon.Observations revealed that the pseudo-critical point is robustly indicated by the higher-order fluctuations of the largest fragment charge.The critical temperatures extracted by the isotope thermometer are relatively consistent,with an uncertainty of 15%,while those obtained by the quantum fluctuation thermometer are heavily influenced by the incident energy and mass number of target nuclei.The excitation energy E∗and bound charge Zbound are used for event-sorting.These two ensembles represent the statistical properties of the initial and final states of the system,respectively.The initial-final correlations of statistical properties might lead to two phenomena.First,the size distribution of the largest fragment at the pseudo-critical point based on the Zbound ensemble is wide,while that based on E∗ensemble exhibits bimodality,which is a typical characteristic in the liquid-gas coexistence of a finite system.Second,the temperature at the pseudo-critical point based on the Zbound ensemble is higher than that based on the E∗ensemble.Furthermore,the projectile-like system exhibits a significant dynamical effect in its evolution path from the initial to final state,closely associated with the fluctuation of critical temperature.

The temperature-dependent fracture strength model for ultra-high temperature ceramics

Breaking down the entire structure of a material implies severing all the bonds between its atoms either by applying work or by heat transfer. Because bond-breaking is indifferent to either means, there is a kind of equivalence between heat energy and strain energy. Based on this equivalence, we assume the existence of a constant maximum storage of energy that includes both the strain energy and the corresponding equivalent heat energy. A temperaturedependent fracture strength model is then developed for ultrahigh temperature ceramics （UHTCs）. Model predictions for UHTCs, HfB2, TiC and ZrB2, are presented and compared with the experimental results. These predictions are found to be largely consistent with experimental results.

Determination of Critical Parameters of Carbon Dioxide+Butyraldehyde System with Different Compositions

Supercritical carbon dioxide（SC-CO2 ） is considered in green chemistry as a substitute for conventional solvents in chemical reactions due to its environmentally benign character. Recently we have reported the homogeneous hydroformylation of propylene in supercritical carbon dioxide（ SC-CO2 ） , which is an example of this kind of application of carbon dioxide. The determination for the critical parameters of carbon dioxide ＋ butyraldehyde mixtures is necessary for this reaction design which is the focus of the present paper. The critical parameters of the binary systems were determined via the static visual method at a constant volume with the molar fraction of butyraldehyde ranging from 1.0% to 2. 2% and the pressure ranging from 5 to 10 MPa. The experimental results show that the critical pressure and temperature increased with increasing the molar fraction of butyraldehyde. The bubble（dew） temperatures and the bubble （dew） pressures for the binary systems were also determined experimentally. The p-T Figures at different compositions of the binary systems were described. In addition, the critical compressibility factors Zc of the binary systems at different concentrations of n-butyraldehyde were calculated. It was found that the critical compressibility factor values of the binary systems decreased with increasing the molar fraction of n-butyraldehyde in the experimental range.

The E3 ubiquitin ligase CSIT1 regulates critical sterility-inducing temperature by ribosome-associated quality control to safeguard two-line hybrid breeding in rice

Two-line hybrid breeding can fully utilize heterosis in crops.In thermo-sensitive genic male sterile(TGMS)lines,low critical sterility-inducing temperature(CSIT)is vital to safeguard the production of two-line hybrid seeds in rice(Oryza sativa),but the molecular mechanism determining CSIT is unclear.Here,we report the cloning of CSIT1,which encodes an E3 ubiquitin ligase,and show that CSIT1 modulates the CSIT of thermo-sensitive genic male sterility 5(tms5)-based TGMS lines through ribosome-associated quality control(RQC).Biochemical assays demonstrated that CSIT1 binds to the 80S ribosomes and ubiquitinates abnormal nascent polypeptides for degradation in the RQC process.Loss of CSIT1 function inhibits the possible damage of tms5 to the ubiquitination system and protein translation,resulting in enhanced accumulation of anther-related proteins such as catalase to suppress abnormal accumulation of reactive oxygen species and premature programmed cell death in the tapetum,thereby leading to a much higher CSIT in the tms5-based TGMS lines.Taken together,our findings reveal a regulatory mechanism of CSIT,providing new insights into RQC and potential targets for future two-line hybrid breeding.

Holographic energy loss near critical temperature in an anisotropic background

We study the energy loss of a quark moving in a strongly coupled quark gluon plasma under the influence of anisotropy.The heavy quark drag force,diffusion coefficient,and jet quenching parameter are calculated using the Einstein–Maxwell-dilaton model,where the anisotropic background is characterized by an arbitrary dynamical parameter A.Our findings indicate that as the anisotropic factor A increases,the drag force and jet quenching parameter both increase,while the diffusion coefficient decreases.Additionally,we observe that the energy loss becomes more significant when the quark moves perpendicular to the anisotropy direction in the transverse plane.The enhancement of the rescaled jet quenching parameters near critical temperature Tc,as well as drag forces for a fast-moving heavy quark is observed,which presents one of the typical features of quantum chromodynamics phase transition.

Manipulating the Phase Transition Behavior of Dual Temperature-Responsive Block Copolymers by Adjusting Composition and Sequence

Temperature-responsive polymers have garnered significant attention due to their ability to respond to external stimuli.In this work,dual temperature-responsive block copolymers are synthesized via reversible addition-fragmentation chain transfer polymerization(RAFT)polymerization utilizing zwitterionic monomer methacryloyl ethyl sulfobetaine(SBMA) and N-isopropyl acrylamide(NIPAAm) as monomers.The thermal responsive behaviors can be easily modulated by incorporating additional hydrophobic monomer benzyl acrylate(BN) or hydrophilic monomer acrylic acid(AA),adjusting concentration or pH,or varying the degree of polymerization of the block chain segments.The cloud points of the copolymers are determined by UV-Vis spectrophotometry,and these copolymers exhibit both controlled upper and lower critical solu bility temperatures(LCST and UCST) in aqueous solution.This study analyzes and summarizes the influencing factors of dual temperature responsive block copolymers by exploring the effects of various conditions on the phase transition temperature of temperature-sensitive polymers to explore the relationship between their properties and environment and structure to make them more selective in terms of temperature application range and regulation laws.It is very interesting that the introduction of poly-acrylic acid(PAA) segments in the middle of di-block copolymer PSBMA_(55)-b-PNIPAAm_(80) to form PSBMA_(55)-b-PAA_(x)-b-PNIPAAm_(80) results in a reversal of temperature-responsive behaviors from 'U'(LCST UCST) type,while the copolymer PSBMA_(55)-b-P(NIPAAm_(80)-co-AA_(x)) not.This work provides a clue for tuning the phase transition behavior of polymers for manufacture of extreme smart materials.