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We report on the high catalytic activity of iron based metallic glass (MG) particles in dissociating direct blue dye (C32H20N6Na4O14S4) (DBD), a toxic water pollutant. We adopted high speed mechanical milling to activate the FeMG particles (of nominal composition Fe48Cr15Mo14Y2C15B6) and optimized the morphology and the particle size to achieve complete degradation of DBD in less than 20 min. The surface morphology and the particle size of the activated particles were characterized using scanning electron microscopy and transmission electron microscopy. They were found to have corrugated edge like catalytically active surfaces after mechanical activation. The dye degradation rate of the activated MG powder was characterized via UV–visible absorption spectroscopy. The rate of dye degradation was significantly faster for the activated particles (within 20 min), compared to both pristine FeMG particles as well as elemental iron particles. In addition, the dye degradation mechanism was studied using Raman and infrared spectroscopy. The catalytically activated surfaces are believed to break the –C–H–, –C–N–, and –N=N– bonds, resulting in complete degradation of DBD.
In this paper, a novel method is proposed to determine surface residual stress components and their directions based on the spherical indentation. To obtain the direction and the components of a uniaxial or biaxial residual stress, the relationship between the pile-up deformation around an indentation after unloading and the residual stress was firstly systematically studied and established by using numerical simulation. Through theoretical analysis and numerical simulation, we found that the position of the maximum residual stress is dependent on the maximum pile-up around an indentation after unloading. The direction and components of residual stress can be correctly determined by the unique relationship between pile-up after unloading and biaxial residual stress. This conclusion has been verified by the experiment results in the residual stress measurements of a welded specimen with spherical indentation and x-ray diffraction methods. Meanwhile, the influences of friction between the object surface and the indenter, the material hardening exponent of the specimen, and the elastic deformation upon the residual stress are discussed.
The Ag3PO4/C3N4 composites with improved photocatalytic activity were prepared by a facile in situ deposition of Ag3PO4 particles on the surface of C3N4 sheets and characterized by x-ray diffraction, field emission scanning electron microscopy, transmission electron microscopy, x-ray photoelectron spectroscopy, UV–vis diffuse reflectance absorption spectra, Fourier transform infrared spectra, and photoluminescence spectra. The photocatalytic degradation of Rhodamine B (RhB) over the Ag3PO4/C3N4 composites was investigated and optimized, indicating that the optimal amount of Ag3PO4 in the composites was 90 wt%. The remarkably improved photocatalytic activity of Ag3PO4/C3N4 composites could be attributed to the effective separation of photogenerated charge carriers. The photoelectrochemical measurements confirmed that the charge separation efficiency was improved for the formation of composites. Moreover, the tests of radical scavengers demonstrated that h+ and ·O2− were the main active species for the degradation of RhB.
This paper provides an overview of advanced scanning transmission electron microscopy (STEM) techniques used for characterization of irradiated BCC Fe-based alloys. Advanced STEM methods provide the high-resolution imaging and chemical analysis necessary to understand the irradiation response of BCC Fe-based alloys. The use of STEM with energy dispersive x-ray spectroscopy (EDX) for measurement of radiation-induced segregation (RIS) is described, with an illustrated example of RIS in proton- and self-ion irradiated T91. Aberration-corrected STEM-EDX for nanocluster/nanoparticle imaging and chemical analysis is also discussed, and examples are provided from ion-irradiated oxide dispersion strengthened (ODS) alloys. Finally, STEM techniques for void, cavity, and dislocation loop imaging are described, with examples from various BCC Fe-based alloys.
The term “solids” denotes materials that generally have the following properties. From a microscopic perspective, the molecules in a solid are in a condensed, closely packed state, and they vibrate around a fixed equilibrium position. That is, molecules can be considered tethered near a specific location in space, since their diffusion is very slow relative to the time scales of observation. From a macroscopic point of view, solids have an elastic modulus. This means that the application of a stress to the material produces a strain as well as an opposing force that tends to return the solid to its original, unstrained state once the stress is removed. This contrasts with viscous behavior in which an applied stress results in continuous, permanent deformation, such as the flow of a liquid.
Generally speaking, there are two primary classes of solids. Crystalline solids are equilibrium states of matter in which the microscopic structure has a well-defined geometric pattern with long-range order: a crystalline lattice. In contrast to crystals, amorphous solids have no long-range order, meaning that they lack a lattice structure and regular positioning of the molecules. Glasses and many polymeric materials are amorphous. Frequently these systems are not at equilibrium, but evolve very slowly in time and are metastable with respect to a crystalline phase. They might be considered liquids of extremely high viscosity that are slowly en route to crystallization. However, typically the time scale to reach equilibrium is so long (perhaps longer than the age of the universe) that for all practical purposes the amorphous state appears solid and stable. Thus, in an empirical sense, often we can treat such systems as in quasi-equilibrium.
In Chapter 3 we discussed the way the world works at a microscopic level: the interactions and laws governing the time evolution of atoms and molecules. We found that an important, unifying perspective for both quantum and classical descriptions is the concept of energy. Now we take a macroscopic point of view. What happens when many (~1023) molecules come together, when we cannot hope to measure individual atomic properties but can probe only bulk material ones? As the title of this chapter suggests, the relevant concept at the macro-resolution is entropy.
Remember that from a macroscopic perspective, we care about macrostates, that is, states of a system characterized by a few macroscopic variables, like E, V, N, T, or P. Empirical measurements generally establish values for properties that are the net result of many atomic interactions averaged over time, and we are thus able to describe a system only in terms of these large-scale, reduced-information metrics that smooth over the molecular world. The statement that a system is at one specific macrostate actually implies that it is evolving through a particular ensemble of many microscopic configurations.
We will focus on classical isolated systems because these offer the simplest introductory perspective. Let us imagine that a closed, insulated container of molecules evolves in time.
We began our discussion of equilibrium by considering how the entropy emerges in isolated systems, finding that it is maximized under constant E, V, N conditions. In practical settings, however, systems are not often isolated and it is difficult to control their energy and volume in the presence of outside forces. Instead, it is easier to control so-called field parameters like temperature and pressure.
In this chapter, we will discuss the proper procedure for switching the independent variables of the fundamental equation for other thermodynamic quantities. In doing so, we will consider non-isolated systems that are held at constant temperature, pressure, and/or chemical potential through coupling to various kinds of baths. In such cases, we find that entropy maximization requires us to consider the entropy of both the system and its surroundings. Moreover, new thermodynamic quantities will naturally emerge in this analysis: additional so-called thermodynamic potentials.
To achieve conditions of constant temperature, pressure, or chemical potential, one couples a system to a bath. As discussed before, a bath is a large reservoir that can exchange energy, volume, or particles with the system of interest. While exchanging volume/energy/particles alters the system state, such changes are so minuscule for the bath that it is essentially always at the same equilibrium condition.
For the first time evidence is provided that a nanocrystalline and stacking-disordered, chemically stabilized β-cristobalite form of AlPO4 occurs in a sewage sludge ash (SSA). This proof is based on a combined X-ray powder diffraction and X-ray fluorescence investigation of an SSA produced at a large-scale fluidized bed incineration facility serving a catching area with a population of 2 million. The structural and chemical characterization was carried out on ‘as received’ SSA samples as well as on solid residues remaining after leaching this SSA in sodium hydroxide solution. Thus, it was ascertained that the observed nanocrystalline and stacking-disordered cristobalite-like component belongs to the aluminum phosphate component of this SSA, rather than to its silicon dioxide component. In addition, a direct proof is presented that the chemically stabilized β-cristobalite form of AlPO4 does crystallize from X-ray amorphous precursors under conditions that mimic the huge heating rate and short retention time (just seconds at T ≈ 850°C), typical for fluidized bed incinerators.
In Chapters 4 and 5 we introduced the molecular basis for the first two laws of thermodynamics. In particular, we developed a physical interpretation for the entropy in terms of microstates. However, we have yet to address two subtle questions regarding this relationship. Is there any such thing as an absolute value of the entropy? That is, does it make sense to identify an exact numerical value of S for a particular system and a particular state point, as opposed to the more modest calculation of a change in entropy between two state points? Furthermore, what is the behavior of the entropy and other thermodynamic functions as the temperature approaches absolute zero?
As we shall see in this chapter, both of these questions cannot be addressed using the first two laws alone. Instead, we must introduce a third law of thermodynamics that provides a context for understanding absolute entropies and absolute zero. The third law is not conceptually as straightforward as the others, first because it is not needed in many practical calculations far away from absolute zero, and second and more importantly, because it can be presented in several quite different ways. In particular, we will describe a number of distinct formulations of the third law and attempt to provide some molecular interpretation for their rationale. Unlike the first and second laws, however, there are many subtleties associated with these formulations that in some cases remain actively discussed. We will not attempt to synthesize and reconcile the details here, but present only the main ideas. The interested reader is referred to the references at the end of the chapter for further information.
Until now, most of what we have discussed has involved general relationships among thermodynamic quantities that can be applied to any system, such as the fundamental equation, reversibility, Legendre transforms, and Maxwell equations. In this and the coming chapters, we begin to investigate properties of specific types of substances. We will mostly consider very simple models in which only the essential physics is included; these give insight into the basic behaviors of solids, liquids, and gases, and actually are sufficient to learn quite a bit about them. Of course, there are also many detailed theoretical and empirical models for specific systems, but very often these theories simply improve upon the accuracy of the approaches rather than introduce major new concepts and qualitative behaviors.
Statistical mechanics provides a systematic route to state- and substance-specific models. If one can postulate a sufficiently simple description of the relevant atomic interaction energetics, the entropy or free energy can be determined in fundamental form. Ultimately our strategy for most of these simple models will be to determine the chemical potential μ(T, P) in single-component systems or μ(T, P, {x}) for multicomponent ones, where {x} gives the mole fractions. In both cases, knowledge of the chemical potentials does indeed give a fundamental perspective, allowing us to extract all of the intensive thermodynamic properties. Moreover, for problems involving phase equilibrium, the chemical potential is the natural starting point, as we will see in Chapter 10.
Like so many texts, this book grew out of lecture notes and problems that I developed through teaching, specifically, graduate thermodynamics over the past seven years. These notes were originally motivated by my difficulty in finding a satisfactory introductory text to both classical thermodynamics and statistical mechanics that could be used for a quarter-long course for first-year chemical engineering graduate students. However, as the years pressed forward, it became apparent that there was a greater opportunity to construct a new presentation of these classic subjects that addressed the needs of the modern student. Namely, few existing books seem to provide an integrated view of both classical and molecular perspectives on thermodynamics, at a sufficient level of rigor to address graduate-level problems.
It has become clear to me that first-year graduate students respond best to a molecular-level “explanation” of the classic laws, at least upon initial discussion. For them this imparts a more intuitive understanding of thermodynamic potentials and, in particular, entropy and the second law. Moreover, students’ most frequent hurdles are conceptual in nature, not mathematical, and I sense that many older presentations are inaccessible to them because concepts are buried deep under patinas of unnecessarily complex notation and equations.