Kinetic and Thermodynamic Characteristics of Torrefied Acer palmatum.

The goal of this research was to investigate the effects of torrefying temperature (220, 260, and 300 °C) on the physicochemical properties, kinetics, thermodynamic parameters, and reaction processes of Acer palmatum (AP) during the pyrolysis process. The kinetics of raw materials and torrefied biomass were studied by using three kinetic models, and the main function graph approach was employed to find the reaction mechanism. The torrefied biomass produced at temperatures of 220 °C (AP-220), 260 °C (AP-260), and 300 °C (AP-300) was thermogravimetrically analyzed at four different heating rates (5, 10, 15, and 20 °C/min). In comparison to the raw material, the average activation energy of torrefied biomass declined with increasing temperature, from 174.13 to 84.67 kJ/mol (FWO), 172.52 to 81.24 kJ/mol (KAS and DAEM). The volatile contents of AP and AP-220 are higher than those of AP-260 and AP-300, indicating that the random nucleation model occupies the central position. Compared with the raw biomass, the average Gibbs free energy (ΔG) of torrefied biomass increased from 157.97 to 195.38 kJ/mol. The mean enthalpy change (ΔH) during the torrefaction process is positive, while the mean entropy change (ΔS) of the torrefaction of biomass is negative, decreasing from 16.93 to -151.53 kJ/mol (FWO) and from 14.36 to -156.06 kJ/mol (KAS and DAEM). Overall, the findings provide a comprehensive understanding of the kinetics and improved features of torrefied biomass as a high-quality solid fuel.

Data-driven approach for synchrotron X-ray Laue microdiffraction scan analysis.

A novel data-driven approach is proposed for analyzing synchrotron Laue X-ray microdiffraction scans based on machine learning algorithms. The basic architecture and major components of the method are formulated mathematically. It is demonstrated through typical examples including polycrystalline BaTiO3, multiphase transforming alloys and finely twinned martensite. The computational pipeline is implemented for beamline 12.3.2 at the Advanced Light Source, Lawrence Berkeley National Laboratory. The conventional analytical pathway for X-ray diffraction scans is based on a slow pattern-by-pattern crystal indexing process. This work provides a new way for analyzing X-ray diffraction 2D patterns, independent of the indexing process, and motivates further studies of X-ray diffraction patterns from the machine learning perspective for the development of suitable feature extraction, clustering and labeling algorithms.

Performance analysis of energy conversion via caloric effects in first-order ferroic phase transformations.

A finite-time thermodynamic model of ferroic refrigerators and generators, based on first order phase transformation, is given. We use this model to evaluate a novel method of converting heat directly into electricity based on the martensitic phase transformation accompanied by an abrupt change in magnetic ordering recently discovered [Srivastava et al., Adv. Energy Mater., 2011, 1, 97]. In this paper, we study the efficiency and power output of this method. The formulas of efficiency and power output in terms of material constants, design parameters, and working conditions are derived. The Clausius-Clapeyron coefficient is shown to be important to the efficiency. The figure of merit, as a dimensionless parameter, of energy conversion using the new method is introduced. It is shown that, as the figure of merit goes to infinity, the efficiency approaches the Carnot efficiency. Thermodynamic cycles of the new energy conversion method are optimized for a maximum power output. The matching criteria between materials and working temperatures of such optimized cycles are derived. Using these criteria, one can choose the most suitable materials under given working conditions, or decide the best working conditions for available materials.

Enhanced reversibility and unusual microstructure of a phase-transforming material.

Materials undergoing reversible solid-to-solid martensitic phase transformations are desirable for applications in medical sensors and actuators, eco-friendly refrigerators and energy conversion devices. The ability to pass back and forth through the phase transformation many times without degradation of properties (termed 'reversibility') is critical for these applications. Materials tuned to satisfy a certain geometric compatibility condition have been shown to exhibit high reversibility, measured by low hysteresis and small migration of transformation temperature under cycling. Recently, stronger compatibility conditions called the 'cofactor conditions' have been proposed theoretically to achieve even better reversibility. Here we report the enhanced reversibility and unusual microstructure of the first martensitic material, Zn45Au30Cu25, that closely satisfies the cofactor conditions. We observe four striking properties of this material. (1) Despite a transformation strain of 8%, the transformation temperature shifts less than 0.5 °C after more than 16,000 thermal cycles. For comparison, the transformation temperature of the ubiquitous NiTi alloy shifts up to 20 °C in the first 20 cycles. (2) The hysteresis remains approximately 2 °C during this cycling. For comparison, the hysteresis of the NiTi alloy is up to 70 °C (refs 9, 12). (3) The alloy exhibits an unusual riverine microstructure of martensite not seen in other martensites. (4) Unlike that of typical polycrystal martensites, its microstructure changes drastically in consecutive transformation cycles, whereas macroscopic properties such as transformation temperature and latent heat are nearly reproducible. These results promise a concrete strategy for seeking ultra-reliable martensitic materials.