Specific heat of UPdâ Siâ

The specific heat of single-crystal U Pd2 Si2 has been studied using both the step heating and continious heating methods for the temperature range 2 to 250 K. Successive phase transitions at Tl = 136I< and T2 = 108I< are reported, which are consistent with current publications. The transition at 40K, which was previously reported, has not been detected. Recent published elastic neutron scattering data, magnetic susceptibility and resistivity results suggest that U Pd2 Si2 may be a heavy fermion compound, however, the electronic specific heat coefficient I (= 18.97 ;~), obtained from the specific heat Cv measurements, is smaller than that of the conventional heavy fermion system. The Debye temperature of U Pd2Si2 is found to be 116.55K. The possibility is discussed that the maximum in CIT in the low-temperature range 2 to 4K corresponds to Schottky anomaly induced by localized magnetic impurities .

Changes of density, thermal conductivity, thermal diffusivity, and specific heat of plums during drying

The thermal properties of plums (Prunus domestica) and prunes were investigated in the moisture content of 14.2-80.4% (wet basis) near room temperature (approximately 28 degrees C). The apparent density of the fruits increased from 1042.9 to 1460.0 kg/m(3), and the bulk density increased from 706.6 to 897.5 kg/m(3) as the plums were dried, following classical empirical models as a function of moisture content. It was found that specific heat, effective thermal diffusivity, and effective thermal conductivity of the prunes increased with the moisture content of the samples, which can be represented by using different empirical models.

Magnetic field dependence of the magnetic susceptibility and the specific heat of the doped plasticized polyaniline (PANI-DB3EPSA)0.5

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Finite size effects in the specific heat of glass-formers

We report clear finite size effects in the specific heat and in the relaxation times of a model glass former at temperatures considerably smaller than the Mode Coupling transition. A crucial ingredient to reach this result is a new Monte Carlo algorithm which allows us to reduce the relaxation time by two order of magnitudes. These effects signal the existence of a large correlation length in static quantities.

Thermophysical Properties of Brazilian Orange Juice as Affected by Temperature and Water Content

The specific heat, thermal conductivity, thermal diffusivity and density of Brazilian orange juice were determined between 0.34 and 0.73 (w/w) water content and with temperatures from 0.5 to 62°C. The experimental data were fitted as functions of temperature and water content and all properties showed a linear dependency with these variables. In the tested range, the water content exhibited a greater influence on the analyzed properties than temperature. © 1998 Elsevier Science Limited. All rights reserved.

Measurement of the specific heat and determination of the thermodynamic functions of relaxed amorphous silicon

The specific heat, cp, of two amorphous silicon (a-Si) samples has been measured by differential scanning calorimetry in the 100–900K temperature range. When the hydrogen content is reduced by thermal annealing, cp approaches the value of crystalline Si (c-Si). Within experimental accuracy, we conclude that cp of relaxed pure a-Si coincides with that of c-Si. This result is used to determine the enthalpy, entropy, and Gibbs free energy of defect-free relaxed a-Si. Finally, the contribution of structural defects on these quantities is calculated and the melting point of several states of a-Si is predicted

Modeling thermal conductivity, specific heat, and density of milk: A neural network approach

The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better Suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0degreesC, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.

Critical behavior of the specific heat in glass formers

We show numeric evidence that, at low enough temperatures, the potential energy density of a glass-forming liquid fluctuates over length scales much larger than the interaction range. We focus on the behavior of translationally invariant quantities. The growing correlation length is unveiled by studying the finite-size effects. In the thermodynamic limit, the specific heat and the relaxation time diverge as a power law. Both features point towards the existence of a critical point in the metastable supercooled liquid phase.

A differential method for the determination of partial molal heat capacities and specific heats of dilute solutions /

Thesis (Ph.D.)--University of California, Berkeley, 1922.

Estimating the specific heat capacity of starch-water-glycerol systems as a function of temperature and compositions

Increasing interests in the use of starch as biodegradable plastic materials demand, amongst others, accurate information on thermal properties of starch systems particularly in the processing of thermoplastic starch (TPS), where plasticisers (water and glycerol) are added. The specific heat capacity of starch-water-glycerol mixtures was determined within a temperature range of 40-120degreesC. A modulated temperature differential scanning calorimeter (MTDSC) was employed and regression equations were obtained to predict the specific heat capacity as a function of temperature, water and glycerol content for four maize starches of differing amylose content (0 - 85%). Generally, temperature and water content are directly proportional to the specific heat capacity of the systems, but the influence of glycerol content on the thermal property varied according to the starch type.

Specific heat capacity of Australian honeys from 35 to 165C as a function of composition using differential scanning calorimetry

Modulated temperature differential scanning calorimetry was used to investigate the specific heat capacity (C-p) of 10 Australian honeys within the processing and handling temperatures. The values obtained were found to be different from the literature values at certain temperatures, and are not predictable by the additive model. The C-p of each honey exhibited a cubic relationship (P < 0.001) with the temperature (T, C). In addition, the moisture (M, %), fructose (F, %) and glucose (G, %) contents of the honeys influenced their C-p. The following equation (r(2) = 0.92) was proposed for estimating C-p of honey, and is recommended for use in the honey industry and in research: C = 996.7 + 1.4 x 10(-3)T + 5.6 x 10(-5)T(2) - 2.4 x 10(-7)T(3) - 56.5M - 25.8F - 31.0G + 1.5(M * F) + 1.8(M * G) + 0.8(F * G) - 4.6 x 10(-2) (M * F * G).