Interpretation of the impedance spectroscopy of cement paste via computer modelling

The d.c. conductivity, , and low-frequency relative dielectric constant, k, of Portland cement paste were monitored, using impedance spectroscopy, during cooling from room temperature down to -50 °C. Dramatic decreases in the values of and k, as great as two orders of magnitude, occurred at the initial freezing point of the aqueous phase in the macropores and larger capillary pores. This result provides strong experimental support for the dielectric amplification mechanism, proposed in Part II of this series, to explain the high measured low-frequency relative dielectric constant of hydrating Portland cement paste. Only gradual changes in the electrical properties were observed below this sudden drop, as the temperature continued to decrease. The values of and k of frozen cement paste, at a constant temperature of -40 °C, were dominated by properties of calcium-silicate-hydrate (C-S-H) and so increased with the degree of hydration of the paste, indicating a C-S-H gel percolation threshold at a volume fraction of approximately 15%–20%, in good agreement with previous predictions. Good agreement was found between experimental results and digital-image-based model computations of at -40 °C. Freeze-thaw cycling caused a drop in the dielectric constant of paste in the unfrozen state, indicating that measurements of k could be useful for monitoring microstructural changes during freeze-thaw cycling and other processes that gradually damage parts of the cement paste microstructure.     

Characterization of shock-hardened Al-8090 alloy

The structure and mechanical properties of Al-Li8090 alloy, that was dynamically deformed and then age hardened, were studied as a function of the changes in the nature and amount of precipitates produced. A comparison was made between two groups of samples, one group that was solution heat treated (SHT) and quenched from 530°C before the dynamic deformation and the other group that was dynamically deformed in the as-received (AR) condition. The higher values for microhardness and ultimate tensile strength observed (138 and 140 VHN, and 405 and 458 MPa, respectively), subsequent to shock treatment (ST), have been attributed to the increase in dislocation density and grain-boundary precipitation produced due to shock deformation. Dislocations and grain boundaries were assumed to act as precipitation sites and an increase in dislocation density, due to ST, was expected to increase precipitation density of (Al₃Li), S(Al₂CuMg), and T₁(Al₂CuLi) phases which, in turn, are expected to increase strength properties of the alloy. Differential scanning calorimetry showed that, for the species that precipitate below 180°C, (Al₃Li) and GP zones, an increase in the amount of deformation increased the precipitation temperatures. However, for the species that precipitate at 197°C, S(Al₂CuMg), an increase in the amount of deformation produced a decrease in its precipitation temperature. These results have been partially confirmed by the activation energy calculations for temperatures below 197 °C, which show a decrease of precipitation energies with an increase in the amount of deformation. Activation energies calculated from ageing curves showed that when ageing at low temperature (165–180 °C range), activation energies for the precipitation process are decreased upon increase in cold work. Shock treatment of SHT samples exhibited decreased activation energy values of precipitation, from 36.14 kcal mol^–1 for the SHT sample to 24.18, 24.08, and 21.00 kcal mol^–1 for SHT + ST samples 1, 2, and 3, respectively (corresponding to 1, 2, and 3 sheets of explosive). Activation energies of precipitation for AR + ST samples showed even lower values; 9.45, 9.95, and 8.21 kcal mol^–1 for samples 4, 5, and 6, respectively. These activation energies strongly corroborate the role of defect substructure on the age-hardening kinetics of this alloy.     

Citation histories of related papers in the field of chemical correlation analysis

Four cases of citation histories of highly cited related papers from the field of chemical correlation analysis indicate that authors have been citing preferably fashionable, but less relevant references.     

Grain size effects on cyclic fatigue and crack-growth resistance behaviour of partially stabilized zirconia

Cyclic fatigue crack growth and crack-resistance behaviour was studied in partially stabilized zirconia (PSZ) with three different cubic-phase grain sizes following sub-eutectoid heat treatments. Raman spectroscopy was used to determine the extent of phase transformation around the cracks for both cyclic and monotonic loading conditions. All tests were on long, through thickness cracks using compact-tension specimens. Predictions of crack-tip shielding were made following determination of toughening parameters using crackresistance data. It was found that the dominant factors affecting cyclic fatigue-crack growth were the level of crack-tip shielding, as a result of phase transformation, and the intrinsic toughness of the material. Grain size did not appear to significantly affect fatigue crack-growth behaviour.     

Low-temperature formation mechanism of double oxides Fe x Zr(Ti)1−0.75x O2−δ prepared from alkoxides and acetylacetonates

As a result of titanium and zirconium alcoholates hydrolysis in the presence of dissolved Fe(acac)₃, amorphous iron-containing gels have been synthesized. Their heat treatment has led to polycrystalline double oxides Fe _x Zr_1–0.75x O_2– (C) and Fe _x Ti_1–0.75x O_2– (T) formation. It has been shown that oxides (C) and (T) are likely to be solid solutions with 0.01<x<0.17 and 0.01<x<0.14, respectively. On the basis of X-ray diffraction and extended X-ray absorption fine structure data, iron-zirconium and iron-titanium crystallite models for gels and oxides have been proposed. It has been found that the crystallization process does not lead to a significant change in interatomic distances typical for local structures detected in gels.     

Preparation and characterization of TiO2-BaO-ZnO-B2O3 glass systems for optical devices

We study the TiO₂-BaO-ZnO-B₂O₃ glass system, where the ZnO and B₂O₃ compositions were constant and the ratio TiO₂/BaO was varied from 0.87 to 1.76. A super kanthal resistance furnace was used to melt the compounds inside an alumina crucible, at 1200 °C, for 10 min. After melting, the glasses were poured out into steel moulds and rapidly cooled by quenching. The glasses obtained were homogeneous, bubble free and transparent. They were characterized by X-ray diffractometry, Fourier transform infrared spectroscopy (FTIR), UV-VIS spectroscopy, dilatometry, density and linear refractive index. An infrared cut off caused by the composition influence was found in both IR and UV-vis spectra. From dilatometry T _d and T _g were verified as being anomalous. The linear thermal expansion coefficient presented an anomalous behaviour in relation to TiO₂ concentrations. The density and linear refractive index increased with increasing TiO₂/BaO ratio arriving at their peak value of TiO₂/BaO=1.5 and then decreasing. The dependence of softening point T _d on the ratio TiO₂/BaO exhibited the same behaviour. It is suggested that Ti⁴⁺ plays a dual part in the glass system, assuming a predominantly tetrahedral coordination in the low titania region and a predominantly octahedral coordination in the high titania region. With a heat treatment of the glass around 600 °C, we observed a rapid change of refractive index with increasing temperature.     

Analysis of intermediate boson spectra from FIR data for HTSC and heavy fermion systems

Calculations of the effect of intermediate bosons on the optical properties of the normal state are used to analyze the spectra of these bosons. For high temperature superconductors these spectra are in agreement with the standard electron-phonon model (the end of the spectrum is near 800 cm^–1) with a moderate coupling constant =1–1.5. For the heavy fermion compound UPt₃ the spectrum of intermediate bosons is consistent with neutron data for spin fluctuations.This work was partially supported by ISF and RFFI (No 94-02-04186a) grants.     

Clonality in hepatocellular carcinoma: analysis of methylation pattern of polymorphic X-chromosome-linked phosphoglycerate kinase gene in females

Analysis of X-chromosome inactivation patterns in women has been used to assess the clonality of various tumors. In this report, we analyzed 27 liver tumors in women, including 18 samples obtained by the performance of ultrasonically guided thin-needle biopsies. By analysis of the heterogeneity of phosphoglycerate kinase gene, 11 of 27 (41%) cases were found to be heterozygous at the gene. Of these informative 11 cases with liver tumors, 7 cases were "large" tumors (> 25 mm in diameter) and 4 cases were "small" tumors (< 25 mm in diameter). All 7 large tumors showed monoclonal patterns by the phosphoglycerate kinase gene analysis. Of the 4 small tumors, 2 showed monoclonal, and 2 showed polyclonal patterns. The 2 with monoclonal patterns were pathologically diagnosed as hepatocellular carcinoma despite their small sizes (20 mm and 23 mm). Of the two with polyclonal patterns, the smallest one (15 mm) was diagnosed as benign adenomatous hyperplasia, and the other as hepatocellular carcinoma heavily infiltrated by lymphocytes. These data suggest that analysis of the methylation pattern of the phosphoglycerate kinase gene may be helpful on rare occasions in elucidating the nature of liver tumors but must in fact be used in conjunction with histological appearances to avoid errors secondary to inflammatory infiltrates.     

Global optimization methods for engineering applications: A review

A review of the methods for global optimization reveals that most methods have been developed for unconstrained problems. They need to be extended to general constrained problems because most of the engineering applications have constraints. Some of the methods can be easily extended while others need further work. It is also possible to transform a constrained problem to an unconstrained one by using penalty or augmented Lagrangian methods and solve the problem that way. Some of the global optimization methods find all the local minimum points while others find only a few of them. In any case, all the methods require a very large number of calculations. Therefore, the computational effort to obtain a global solution is generally substantial. The methods for global optimization can be divided into two broad categories: deterministic and stochastic. Some deterministic methods are based on certain assumptions on the cost function that are not easy to check. These methods are not very useful since they are not applicable to general problems. Other deterministic methods are based on certain heuristics which may not lead to the true global solution. Several stochastic methods have been developed as some variation of the pure random search. Some methods are useful for only discrete optimization problems while others can be used for both discrete and continuous problems. Main characteristics of each method are identified and discussed. The selection of a method for a particular application depends on several attributes, such as types of design variables, whether or not all local minima are desired, and availability of gradients of all the functions.Notation Number of equality constraints - () ^T A transpose of a vector - A A hypercubic cell in clustering methods - Distance between two adjacent mesh points - Probability that a uniform sample of sizeN contains at least one point in a subsetA ofS - A(v, x) Aspiration level function - A The set of points with cost function values less thanf(x _G ^* ) +. Same asA _f () - A _f () A set of points at which the cost function value is within off(x _G ^* ) - A () A set of points x with[f(x)] smaller than - A _N The set ofN random points - A _q The set of sample points with the cost function value f _q - _Q The contraction coefficient; –1 _Q 0 - _R The expansion coefficient; _E > 1 - _R The reflection coefficient; 0 < _R 1 - A _x () A set of points that are within the distance from x _G ^* - D Diagonal form of the Hessian matrix - det() Determinant of a matrix - d _j A monotonic function of the number of failed local minimizations - d _t Infinitesimal change in time - d _x Infinitesimal change in design - A small positive constant - (t) A real function called the noise coefficient - ₀ Initial value for(t) - exp() The exponential function - f ^(c) The record; smallest cost function value over X^(C) - [f(x)] Functional for calculating the volume fraction of a subset - Second-order approximation tof(x) - f(x) The cost function - An estimate of the upper bound of global minimum - f ^E The cost function value at x^E - f ^L The cost function value at x^L - f _opt The current best minimum function value - f ^P The cost function value at x ^P - f ^Q The cost function value at x ^Q - f _q A function value used to reduce the random sample - f ^R The cost function value at x ^R - f ^S The cost function value at x^S - f _{T F min} A common minimum cost function value for several trajectories - f _{TF opt} The best current minimum value found so far forf _{TF min} - f ^W The cost function value at x ^W - G Minimum number of points in a cell (A) to be considered full - The gamma function - A factor used to scale the global optimum cost in the zooming method - Minimum distance assumed to exist between two local minimum points - gi(x) Constraints of the optimization problem - H The size of the tabu list - H(x^*) The Hessian matrix of the cost function at x^* - h _j Half side length of a hypercube - h _m Minimum half side lengths of hypercubes in one row - I The unity matrix - ILIM A limit on the number of trials before the temperature is reduced - J The set of active constraints - K Estimate of total number of local minima - k Iteration counter - The number of times a clustering algorithm is executed - L Lipschitz constant, defined in Section 2 - L The number of local searches performed - _i The corresponding pole strengths - log () The natural logarithm - LS Local search procedure - M Number of local minimum points found inL searches - m Total number of constraints - m(t) Mass of a particle as a function of time - m() TheLebesgue measure of thea set - Average cost value for a number of random sample of points inS - N The number of sample points taken from a uniform random distribution - n Number of design variables - n(t) Nonconservative resistance forces - n _c Number of cells;S is divided inton _c cells - NT Number of trajectories - Pi (3.1415926) - P _i ^(j) Hypersphere approximating thej-th cluster at stagei - p(x ⁽ⁱ⁾⁾ Boltzmann-Gibbs distribution; the probability of finding the system in a particular configuration - pg A parameter corresponding to each reduced sample point, defined in (36) - Q An orthogonal matrix used to diagonalize the Hessian matrix - _i (i = 1, K) The relative size of thei-th region of attraction - r _i ^(j) Radius of thej-th hypersp here at stagei - R _x ^* Region of attraction of a local minimum x^* - r _j Radius of a hypersphere - r A critical distance; determines whether a point is linked to a cluster - R ⁿ A set ofn tuples of real numbers - A hyper rectangle set used to approximateS - S The constraint set - A user supplied parameter used to determiner - s The number of failed local minimizations - T The tabu list - t Time - T(x) The tunneling function - T _c (x) The constrained tunneling function - T _i The temperature of a system at a configurationi - TLIMIT A lower limit for the temperature - TR A factor between 0 and 1 used to reduce the temperature - u(x) A unimodal function - V(x) The set of all feasible moves at the current design - v(x) An oscillating small perturbation. - V(y⁽ⁱ⁾) Voronoi cell of the code point y⁽ⁱ⁾ - v^–1 An inverse move - v _k A move; the change from previous to current designs - w(t) Ann-dimensional standard. Wiener process - x Design variable vector of dimensionn - x^# A movable pole used in the tunneling method - x⁽⁰⁾ A starting point for a local search procedure - X^(c) A sequence of feasible points {x⁽¹⁾, x⁽²⁾,,x^(c)} - x(t) Design vector as a function of time - X^* The set of all local minimum points - x^* A local minimum point forf(x) - x^*(i) Poles used in the tunneling method - x _G ^* A global minimum point forf(x) - Transformed design space - The velocity vector of the particle as a function of time - Acceleration vector of the particle as a function of time - x ^C Centroid of the simplex excluding x ^L - x ^c A pole point used in the tunneling method - x ^E An expansion point of x ^R along the direction x ^C x ^R - x ^L The best point of a simplex - x ^P A new trial point - x ^Q A contraction point - x ^R A reflection point; reflection of x ^W on x ^C - x ^S The second worst point of a simplex - x ^W The worst point of a simplex - The reduced sample point with the smallest function value of a full cell - Y The set of code points - y ⁽ⁱ⁾ A code point; a point that represents all the points of thei-th cell - z A random number uniformly distributed in (0,1) - Z ^(c) The set of points x where [f ^(c) – ] is smaller thanf(x) - []₊ Max (0,) - | | Absolute value - The Euclidean norm - f[x(t)] The gradient of the cost function