Predicted Melting Temperature Research Articles

Machine Learning for Melting Temperature Predictions and Design in Polyhydroxyalkanoate-Based Biopolymers.

Diminishing fossil fuel-based resources and ever-growing environmental concerns related to plastic pollution demand for the development of sustainable and biodegradable polymeric material alternatives. Polyhydroxyalkanoates (PHAs) represent an eco-friendly and economically viable class of polymers with a wide range of applications. However, the chemical diversity combined with tunable physical properties available within PHAs poses discovery and optimization challenges with respect to identifying optimal application-specific chemical compositions. Here we use an example of melting temperature (Tm) prediction to demonstrate the promise of machine learning (ML)-based techniques for establishing efficient structure-property mappings in PHA-based chemical space. We employ a manually curated data set of experimentally measured Tm values for a wide range of PHA homo- and copolymer chemistries along with their reported polymer molecular weights and polydispersity indices. Descriptors based on topology, shape, and charge/polarity of specific motifs forming the polymer backbone were then used to numerically represent the polymers. The ML models developed by using available data were used to rapidly predict the property of multicomponent PHA-based copolymers, while estimating uncertainties underlying the predictions. Combined with a previously developed glass transition temperature (Tg) prediction model and an evolutionary algorithm-based search strategy, the approach is demonstrated to address polymer design with multiobjective optimization challenges.

Dominant mutations in the severe acute respiratory syndrome coronavirus-2 genome challenge polymerase chain reaction detection.

Dominant mutations in the severe acute respiratory syndrome coronavirus-2 genome challenge polymerase chain reaction detection.

Prediction of melting temperatures of wax gelators depending on their component composition

The study of wax gelators is a new direction with the potential for use in foods for special dietary uses. Waxes of both plant and animal origin, which consist of various combinations of organic compounds: hydrocarbons, wax esters, free fatty acids and free higher alcohols, are among the studied ones. One of the main characteristics of these gelling agents is their melting point, which largely depends on the component composition of the wax. However, at present there are no models capable to reliably predict this parameter depending on the gel-forming agent composition. The aim of this work was to build models predicting the influence of wax composition on its melting temperature. Material and methods. Preparative flash chromatography was used to obtain individual fractions of the beeswax (obtained from a Russian apiary). On the basis of these fractions, combinations were made and their melting temperatures were measured using the method of differential scanning calorimetry. Two approaches were used to predict the melting temperatures of wax gel-formers: multiple linear regression and the construction of artificial neural networks. Results. A total of 68 gelling agent combinations were analyzed. The model obtained on the basis of multiple linear regression was characterized by high values of the multiple correlation coefficient (r2=0.77). Nevertheless, high values of the standard deviation in the most cases led to false prediction results. The application of artificial neural networks made it possible to get a more reliable prognosticating system with high values of the correlation coefficient (r2=0.97) and the standard deviation not exceeding 3 °С. Conclusion. As a result of the conducted work it has been shown that it is possible to predict melting temperatures on the basis of the component composition of gel-forming fractions. The use of the data obtained in the article will allow to develop oleogels with the specified composition and properties for their use in new types of foodstuffs.

REGULARITIES OF CHANGES AND PREDICTION OF MELTING POINTS AND THERMOELECTRIC FIGURE OF MERIT FOR THE COMPOUNDS Tl4BIVC3 AND Tl9BVC6 (BIV – Si, Ge, Sn, Pb; BV – P, As, Sb, Bi; C – S, Se, Te)

The study is a continuation of the systematic investigation of the compounds which are the crystal chemical analogues of the Tl5Te3 structure, crystallizing in the tetragonal space groups I4/mcm or P4/ncc. The studies conducted by the staff of the Uzhhorod National University over the past decades have found that these compounds exhibit a number of physical properties that are promising for practical use in modern technology. The subject of this work was the relationship between some physicochemical properties of the ternary chalcogenide compounds, such as Tl4BIVC3 and Tl9BVC6 (where BIV = Si, Ge, Sn, Pb; BV = P, As, Sb, Bi; and C = S, Se, Te), and the average charge (Zave) of the compouns’ atomic nuclei. Some of the predicted values of the melting temperature presented in the work may correspond to the temperature of the peritectic (or other type) transformation, as the nature of the formation and properties of this type of compounds have not yet been studied.
 For the first time, based on the results of collecting the literature data, detailed analysis and conclusions from them, the predicted melting temperature (Tm) values for 24 chalcogenide compounds of the Tl4BIVC3 (I) and Tl9BVC6 (II) compositions were established. There are five separate groups of the ternary chalcogenides of the both aforementioned types with a linear dependence of the changes in properties in the coordinates Tm – Zave, which include the analogues with both space groups, P4/ncc and I4/mcm. The limiting range of the Zave values of transformation of the above compounds from the space group P4/ncc to the I4/mcm one has been established; the defined range is within the Zave of ~60-62. The ternary compounds Tl9P(As,Sb,Bi)S6, Tl9P(As)Se6, Tl4Si(Ge,Sn,Pb)S3 and Tl4Si(Ge,Sn)Se3 belong to the space group P4/ncc, while the chalcogenides Tl9P(As,Sb,Bi)Te6, Tl9Sb(Bi)Se6, Tl4Si(Ge,Sn,Pb)S3 and Tl4PbSe3 belong to the space group I4/mcm. There is a clear tendency to increase the value of the thermoelectric figure of merit ZT for individual thio-, seleno- and tellurium-derived compounds at the substitution of the elements Si → Ge → Sn → Pb. Similar changes in the ZT values were also found for the vast majority of the type (II) compounds at the P → As → Sb → Bi transitions. The exceptions to this trend are thio-, selenium- and tellurium bismuth derivatives.

The Thermal Agitated Phase Transitions on the Ti32 Nanocluster: a Molecular Dynamics Simulation Study

ABSTRACT Molecular dynamics simulations were performed to investigate the stability with respect to increasing the simulated temperature from 300 to 2400 K of an isolated cluster composed of 32 titanium atoms. The interatomic interactions were modelled using Gupta potentials as implemented within the classical molecular dynamics simulation software DL_POLY. The radial distribution functions (RDF), diffusion coefficient, and density profiles were examined to study the structural changes as a function of temperature. It was found that the Ti32 nanocluster exhibits temperature structural transition. The icosahedron and pentagonal bi-pyramid structures were found to be the most dominant building block fragments. Deformation of the nanocluster was also measured by diffusion coefficient, and it was found that the Ti32 are mobile above the bulk melting point. The phase transitions from solid to liquid have been identified by a simple jump in the total energy curve, with the predicted melting temperature near the bulk melting point (1941.15 K). As expected, the RDF's and density profile peaks decrease with increasing temperature. Keywords: Molecular dynamics, titanium cluster, radial distribution functions, diffusion coefficient, mean square displacement.

The Mechanical Behaviors of Polyethylene/Silver Nanoparticle Composites: an Insight from Molecular Dynamics study

This research uses molecular dynamics simulation (MD) to study the mechanical properties of pristine polyethylene (PE) and its composites which include silver nanoparticles (PE/AgNPs) at two AgNP weight fractions of 1.05 wt% and 3.10 wt%. The stress-strain distribution of the tensile process shows that the embedded AgNPs can significantly improve the Young’s modulus and tensile strength of the pristine PE, due to improvements in the local density and strength of the PE near the AgNP surface in the range of 12 Å. Regarding the effect of temperature on the mechanical properties of pristine PE and PE/AgNP composites, the Young’s modulus and the strength of the pristine PE and PE/AgNP composites decreased significantly at 350 K and 450 K, respectively, consistent with predicted melting temperature of pristine PE, which lies at around 360 K. At such temperatures as these, PE material has stronger ductility and a higher mobility of AgNPs in the PE matrix than those at 300 K. With the increase of tensile strain, AgNPs tend to be close, and the fracture of PE leads to a similarity between both the Young’s modulus and ultimate strength found for the pristine PE and those found for the PE/AgNP composites at 350 K and 450 K, respectively.

Performance of the standard exchange-correlation functionals in predicting melting properties fully from first principles: Application to Al and magnetic Ni

We apply the efficient two-optimized references thermodynamic integration using Langevin dynamics method [Phys. Rev. B 96, 224202 (2017)] to calculate highly accurate melting properties of Al and magnetic Ni from first principles. For Ni we carefully investigate the impact of magnetism on the liquid and solid free energies including longitudinal spin fluctuations and the reverse influence of atomic vibrations on magnetic properties. We show that magnetic fluctuations are effectively canceling out for both phases and are thus not altering the predicted melting temperature. For both elements, the generalized gradient approximation (GGA) and the local-density approximation (LDA) are used for the exchange-correlation functional revealing a reliable ab initio confidence interval capturing the respective experimental melting point, enthalpy of fusion, and entropy of fusion.

Thermodynamic modeling and experimental verification of new eutectic salt mixtures as thermal energy storage materials

In this work, modified BET model was applied to obtain phase diagrams and to design new eutectic mixtures. As a result, the eutectic composition and the melting point of two mixtures based on salt hydrates: LiNO3·3H2O–NaNO3–Mn(NO3)2·6H2O and LiNO3·3H2O–Mn(NO3)2·6H2O–Mg(NO3)2·6H2O were predicted. Both mixtures present the same predicted melting temperature of 10.8 °C. Experimental verifications by T-history method showed satisfactory accordance of the predicted temperatures values with a difference of 0 °C and +2.3 °C for the mixtures, with sodium nitrate and magnesium nitrate, respectively. It is added that the thermal and physical properties such as density, the heat capacity for solid and liquid phases, as well as viscosity and volume change during the fusion of the new PCMs were evaluated. The results of the characterization, the energy storage density (about 300 MJ m−3) and material cost estimation show that both mixtures are promising candidates for use in low temperature energy storage systems.

Effects of Strontium incorporation to Mg-Zn-Ca biodegradable bulk metallic glass investigated by molecular dynamics simulation and density functional theory calculation

Molecular dynamics (MD) simulation and density functional theory (DFT) calculations were used to predict the material properties and explore the improvement on the surface corrosion resistance for the Mg66Zn30Ca3Sr1 bulk metallic glass (BMG). The Mg66Zn30Ca4 BMG was also investigated to realize the influence of the addition of Sr element on the material behaviors of Mg66Zn30Ca4. The Mg-Zn-Ca-Sr parameters of the next nearest-neighbor modified embedded atom method (2NN MEAM) potential were first determined by the guaranteed convergence particle swarm optimization (GCPSO) method based on the reference data from the density functional theory (DFT) calculation. Besides, using the 2NN MEAM parameters of the Mg-Zn-Ca-Sr system, the structures of Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1 were predicted by the simulated-annealing basin-hopping (SABH) method. The local atomic arrangements of the predicted BMG structures are almost the same as those measured in some related experiments from a comparison with the calculated and experimental X-ray diffraction (XRD) profiles. Furthermore, the HA index analysis shows that the fractions of icosahedra-like local structures are about 72.20% and 72.73% for Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1, respectively, indicating that these two BMG structures are entirely amorphous. The uniaxial tensile MD simulation was conducted to obtain the stress-strain relationship as well as the related mechanical properties of Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1. Consequently, the predicted Young’s moduli of both BMGs are about 46.4 GPa, which are very close to the experimental values of 48.8 ± 0.2 and 49.1 ± 0.1 GPa for Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1, respectively. However, the predicted strengths of Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1 are about 850 and 900 MPa, both are slightly higher than the measured experimental values about 747 ± 22 and 848 ± 21 MPa for Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1. Regarding the thermal properties, the predicted melting temperature of Mg66Zn30Ca3Sr1 by the square displacement (SD) profile is about 620 K, which is very close to the experimental melting temperature of about 613 K. The self-diffusion coefficients of Mg, Zn, Ca, and Sr elements were also calculated for temperatures near their melting points by means of the Einstein equation. The methodology can determine the diffusion barriers for different elements by utilizing these diffusion coefficients resulting in a fact that the diffusion barriers of Ca and Sr elements of Mg66Zn30Ca3Sr1 are relatively high. For the electronic properties predicted by the DFT calculation, the projected density of states (PDOS) profiles of surface Mg, Zn, Ca, and Sr elements clearly show that the addition of Sr into Mg66Zn30Ca4 effectively reduces the s and p orbital states of surface Mg and Zn elements near the Fermi level, particularly the p orbits, which suppresses the electron transfer as well as increases the surface corrosion resistance of Mg66Zn30Ca4. Consequently, this study has provided excellent 2NN MEAM parameters for the Mg, Zn, Ca, and Sr system by the GCPSO method to predict real BMG structures as well as by means of the DFT calculation to explore the electronic properties. Eventually, through our developed numerical processes the material properties of BMGs with different compositions can be predicted accurately for the new BMG design.

Modelling for the Prediction of Melting Temperature for Metallic Nanoparticles

At nano level, materials show very interesting physical properties with the variation of shape and size. The prediction of this behaviour has been a burning issue in the recent years in the scientific community as well. Even the physical properties of these materials are poorly investigated experimentally. To explain the sharp change in the properties of metals, as reported by some investigators, at their nanolevel, different models have been proposed. It is observed that in their theoretical prediction, they have not considered the exact arrangement of atoms in the lattice. In our attempt to understand the behaviour of the nanomaterials, we have studied the melting temperature of some nanosolids having face centered cubic lattice such as Aluminium (Al), Copper (Cu), Paladium (Pd), Platinum (Pt) and Gold (Au), considering different shapes with their sizes ranging from 30 nm to more smaller dimensions. For modelling analysis, we have considered the very basic and fundamental relation of cohesive energy with melting temperature along with modification with two realistic physical quantities-packing fraction and particle shape factor simultaneously to account the arrangements of atoms within the nanoparticle and on the surface as well. Our study shows that there is a very marked change in the melting temperature of the metallic nanosolids below 20 nm. Although in the earlier reported works, it has been claimed that this variation occurs at somewhat higher values. In this variation, the tetrahedral structure exhibits maximum variation of melting temperature while spherical one corresponds to the minimum change. In case of gold, our simulated data has been compared with available experimental values which is found in good agreement with it. This agreement between experimental and computed data validates our proposed model for the prediction of melting temperature of nanoparticles at varying dimensions viz, shape and size. Thus our proposed modification in the existing model is more appropriate in the prediction of melting point of nanoparticles with its varying shape and size.

Molecular Dynamics Simulations of the Hypoxia-Inducible Factor PAS-B Domain Confirm That Internally Bound Water Molecules Function To Stabilize the Protein Core for Ligand Binding.

Hypoxia-inducible factors (HIFs) are heterodimeric transcription factors that are induced in many cancer types, promoting tumor-forming pathways. The HIF-2α PAS-B domain of the human HIF-2 complex contains a large buried hydrophilic cavity that is filled with eight ordered water molecules, making the domain a promising drug target. Recent work has led to the hypothesis that these buried water molecules act as an internal scaffold that stabilizes the buried cavity, holding it open to ease ligand binding. Here we show that extensive molecular dynamics simulations of the HIF-2α PAS-B domain strongly support this hypothesis. If water is prevented from entering the buried cavity, several amino acid side chains lining the cavity undergo a major conformational change that shrinks the cavity volume by an average of ∼45% relative to the hydrated cavity. The structural change within the cavity is due mainly to side chain rearrangements; the absence of bound water has only minor effects on the protein backbone conformation. Moreover, when the cavity lacks internally bound water, the side chain of Tyr307 rotates such that it blocks a major route for entry of the ligand into the cavity, greatly raising the free energy barrier for binding of an artificial ligand compared to when the cavity contains water. Finally, there is no difference in global protein stability of PAS-B when the cavity lacks water, as indicated by the same degree of protein flexibility and identical predicted melting temperatures. These findings help to explain further how water stabilizes large internal cavities, a relatively underexamined feature of proteins.

Ultra-high temperature ceramics melting temperature prediction via machine learning

Melting temperature has great influence on the high temperature properties and working temperature limits of ultra-high temperature ceramics (UHTCs) In order to bypass the challenge in the measurement of ultra-high melting points, this paper proposed a novel method to predict UHTCs melting temperature via machine learning. A dataset including more than ten thousand melting temperature data has been established, which covers 8 elements and most of the known non-oxide UHTCs. We built up an element to ceramic system framework by back propagation artificial neural network (BPANN) with the accuracy approaching to 90% and the correlation coefficients approaching to 0.95. Our work provides a probability to get the high accuracy melting temperature of UHTCs, and a more convenient way to develop novel materials with higher working temperature. The given case of melting temperature prediction of Hf-C-N ceramics proves the generality of the artificial neural network (ANN). An inter-validation of melting temperature prediction using our network with materials thermodynamics and density functional theory (DFT) has been demonstrated, indicating that our network is of powerful prediction ability.

Nearest-neighbour parameters optimized for melting temperature prediction of DNA/RNA hybrids at high and low salt concentrations

Gene editing technologies sparked a renewed interest in the hybridization of DNA/RNA duplexes, yet little improvement on nearest-neighbour parameters was made over the past two decades. For low sodium concentration no parameter set was yet calculated. Here, we revised the existing experimental datasets and used an expanded set of sequences from which we recalculated the nearest-neighbour parameters, reducing the average temperature prediction uncertainty to 1.6 °C. Two experimental sets using temperatures extracted via different methods were used with similar results, with the curve-fitting method achieving a slight advantage in prediction quality over other methods. Additionally, we obtained new parameters for low salt with an average uncertainty of 0.98 °C. We also tested several types of salt correction factors and concluded that it is advisable to use those originally developed for RNA/RNA rather than for DNA/DNA.

First-principles study of the melting temperature of MgO

Using first-principles only, we calculate the melting point of MgO, also called periclase or magnesia. The random phase approximation (RPA) is used to include the exact exchange as well as local and non-local many-body correlation terms, in order to provide high accuracy. Using the free energy method, we obtain the melting temperature directly from the internal energies calculated with DFT. The free energy differences between the ensembles generated by the molecular dynamics simulations are calulated with thermodynamic integration or thermodynamic perturbation theory. The predicted melting temperature is $T_m^\text{RPA} =3043\pm 86$ K, and the values obtained with the PBE and SCAN functionals are $T_m^\text{PBE} = 2747 \pm 59$ K and $T_m^\text{SCAN} = 3032\pm 53 $ K.

Advanced predictions of solidification in cryogenic natural gas and LNG processing

The formation and deposition of solids during the cryogenic processing of natural gas is a perennial risk for operators. Several tools are available for predicting the temperatures at which heavy hydrocarbon solids will form in cryogenic processing equipment; of these the Kohn and Luks Solids Solubility Program (KLSSP) from GPA Midstream has become an industry standard tool for predicting solid-fluid equilibria (SFE) in cryogenic processes. However, although it describes well many of the data sets generated as part of the GPA’s research program in the 1970s and 1980s, the KLSSP suffers from limitations including fixed ranges of temperature, mixture composition, no dependence on pressure and a limited set of possible freeze-out components. Here, a new software tool called ThermoFAST is presented, which overcomes these limitations and has been endorsed by GPA Midstream to replace the KLSSP. This model uses a cubic equation of state and efficient flash algorithms to enable rapid calculations of solid-liquid, solid-vapour, and solid-liquid-vapour equilibrium conditions in addition to normal vapour-liquid phase envelopes. The model has been tuned to the available solid-fluid equilibrium literature data for 58 binary mixtures and is able to represent them with an average root-mean-squared temperature deviation of only 1.7 K. It was thoroughly tested against available SLE data for multi-component LNG mixtures, and improved the accuracy of predicted melting temperatures by a factor of 7 relative to KLSSP, with an average rms deviation of only 2.0 K. The rapid flash algorithm was used to identify 26 distinct transition pathways involving solidification phenomena in LNG-relevant fluids: this includes the prediction of retrograde solidification in multiple systems (including the methane + benzene binary) where a decrease in system temperature produces a reduction in the amount of solid phase present.

Determination and measurement of solid–liquid equilibrium for binary fatty acid mixtures based on NRTL and UNIQUAC activity models

The estimation of solid–liquid phase equilibrium is important for the design, development, and operation of many industrial processes because of application in many manufacturing fields such as cosmetic, pharmaceutic, and biotechnology industries. In this work, we measured solid–liquid phase equilibrium of six fatty acid binary mixtures using the DSC technique and developed thermodynamic approaches for binary fatty acid mixtures to estimate melting temperatures as a function of mole fraction in solid–liquid phase equilibrium. Derivation of NRTL and UNIQUAC activity models was developed to predict melting temperatures and latent heat to achieve eutectic points of undecylic acid, pentadecylic acid, margaric acid, and stearic acid six pairwise binary mixtures. The fatty acids eutectic mixtures are appropriate for heat water systems, phase clothes, concrete, and other similar applications. The results showed low deviations from experimental data measured in this study.

Melting curve of Si by means of the Z-method

The melting curve of silicon is investigated through classical molecular dynamics simulations. We explore pressures from 0 to 20 GPa using the EDIP, Stillinger-Weber, and Tersoff interactomic potentials. Using the Z method, we demonstrate that the predicted melting temperature Tm can be significantly overestimated, depending on the potential chosen. Our results show that none of the potentials explored is able to reproduce the experimental melting curve of silicon by means of the Z-method. However, the EDIP potential does predict the change in the Clapeyron slope, associated with the diamond to β-tin phase transition.

First principles study of ceramic materials (IVB group carbides) under ultrafast laser irradiation**Project supported by the National Natural Science Foundation of China (Grant Nos. 11474207 and 11374217).

Group IVB carbides have been applied in extreme aerospace environments as hard ceramic coatings; ZrC is being considered as a replacement for SiC in nuclear reactors. Therefore, a thorough understanding of the laser irradiation response of group IVB carbides is of clear significance. However, the existing knowledge on the fundamental properties of IVB group carbides is limited and insufficient with regard to both irradiated and non-irradiated characteristics. We investigate the effect of ultrafast laser irradiation on the lattice stability of ceramic materials (IVB group carbides) using the density functional perturbation theory (DFPT). The calculated phonon frequencies of TiC and ZrC at the ground state are in good agreement with previous calculations and experimental values. The phonon frequencies of IVB group carbides are positive, even though the electronic temperature reached 5 eV. Thus, IVB group carbides are more stable under ultrafast laser irradiation, which has greater benefits in nuclear and aeronautical applications compared to metals (W, Na), semimetals (Bi), and semiconductors (Si, SiC). The thermodynamic properties of ZrC are calculated as functions of their lattice temperature at different electronic temperatures. The elastic shear constants of IVB group carbides satisfy the Born stability criteria at Te = 5 eV. In addition, a comparison of the predicted melting temperatures of IVB group carbides, reveal that HfC is better suited for extreme high-temperature environments.

Investigating mechanical properties of polymethylmethacrylate/silver nanoparticle composites by molecular dynamics simulation

The molecular dynamics simulation (MD) was carried out to investigate the mechanical properties of pristine polymethylmethacrylate (PMMA) and the composites of PMMA mixed with the silver nanoparticles (PMMA/AgNPs) at two AgNP weight fractions at 0.60 and 1.77 wt%. From the stress–strain profiles by the tensile process, it can be seen that the improvement on Young’s modulus is insignificant at these lower AgNP fractions. The tensile strength of pristine PMMA can be slightly improved by the embedded AgNPs at 1.77 wt%, because the local density and strength of PMMA in the vicinity of AgNP surface within about 8.2 A are improved. For the temperature effect on the mechanical properties of pristine PMMA and PMMA/AgNP composite, the Young’s moduli and strength of pristine PMMA and PMMA/AgNP composite significantly decrease at temperatures of 450 and 550 K, which are close to the predicted melting temperature of pristine PMMA about 460 K. At these temperatures, the PMMA materials become more ductile and the AgNPs within the PMMA matrix display higher mobility than those at 300 K. When the tensile strain increases, the AgNPs tend to get closer and the fracture appears at the PMMA part, leading to the close values of Young’s modulus and ultimate strength for pristine PMMA and PMMA/AgNP composite at 450 and 550 K.

Thermal-Stability and Reconstitution Ability of Listeria Phages P100 and A511.

The study evaluated the thermal-stability of Listeria phages P100 and A511 at temperatures simulating the preparation of ready-to-eat meats. The phage infectivity after heating to 71°C and holding for a minimum of 30 s, before eventually cooling to 4°C were examined. Higher temperatures of 75, 80, and 85°C were also tested to evaluate their effect on phages thermal-stability. This study found that despite minor differences in the amino acid sequences of their structural proteins, the two phages responded differently to high temperatures. P100 activity declined at least 10 log (PFU mL-1) with exposure to 71°C (30 s) and falling below the limit of detection (1 log PFU mL-1) while, A511 dropped from 108 to 105 PFU mL-1. Cooling resulted in partial reconstitution of P100 phage particles to 103 PFU mL-1. Exposure to 75°C (30 s) abolished A511 activity (8 log PFU mL-1) and both phages showed reconstitution during cooling phase after exposure to 75°C. P100 exhibited reconstitution after treatment at 80°C (30 s), conversely A511 showed no reconstitution activity. Heating P100 to 85°C abolished the reconstitution potential. Substantial differences were found in thermal-stability and reconstitution of the examined phages showing A511 to be more thermo-stable than P100, while P100 exhibited reconstitution during cooling after treatment at 80°C which was absent in A511. The differences in predicted melting temperatures of structural proteins of P100 and A511 were consistent with the observed differences in thermal stability and morphological changes observed with transmission electron microscopy.