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Register a new userUnderstanding glassy phenomena in materials
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David Sherrington
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A basis for understanding and modelling glassy behaviour in martensitic alloys and relaxor ferroelectrics is discussed from the perspective of spin glasses.
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Both structural glasses and disordered crystals are known to exhibit anomalous thermal, vibrational, and acoustic properties at low temperatures or low energies, what is still a matter of lively debate. To shed light on this issue, we studied the halomethane family C-Br_n-Cl_4-n (n = 0,1,2) at low temperature where, despite being perfectly translationally ordered stable monoclinic crystals, glassy dynamical features had been reported from experiments and molecular dynamics simulations. For n = 1,2 dynamic disorder originates by the random occupancy of the same lattice sites by either Cl or Br atoms, but not for the ideal reference case of CCl4. Measurements of the low-temperature specific heat (Cp) for all these materials are here reported, which provide evidence of the presence of a broad peak in Debye-reduced Cp/T^3 and in the reduced density of states g(w)/w^2 determined by means of neutron spectroscopy, as well as a linear term in Cp usually ascribed in glasses to two-level systems in addition to the cubic term expected for a fully ordered crystal. Being CCl4 a fully ordered crystal, we also performed density functional theory (DFT) calculations, which provide unprecedented detailed information about the microscopic nature of vibrations responsible for that broad peak, much alike the boson peak of glasses, finding it to essentially arise from a piling up (at around 3 - 4 meV) of low-energy optical modes together with acoustic modes near the Brillouin-zone limits.
Doping mobile carriers into ordinary semiconductors such as Si, GaAs, and ZnO was the enabling step in the electronic and optoelectronic revolutions. The recent emergence of a class of Quantum Materials, where uniquely quantum interactions between the components produce specific behaviors such as topological insulation, unusual magnetism, superconductivity, spin-orbit-induced and magnetically-induced spin splitting, polaron formation, and transparency of electrical conductors, pointed attention to a range of doping-related phenomena associated with chemical classes that differ from the traditional semiconductors. These include wide-gap oxides, compounds containing open-shell d electrons, and compounds made of heavy elements yet having significant band gaps. The atomistic electronic structure theory of doping that has been developed over the past two decades in the sub-field of semiconductor physics has recently been extended and applied to quantum materials. The present review focuses on explaining the main concepts needed for a basic understanding of the doping phenomenology and indeed peculiarities in quantum materials from the perspective of condensed matter theory, with the hope of forging bridges to the chemists that have enabled the synthesis of some of the most interesting compounds in this field.
Chalcogenide alloys are materials of interest for optical recording and non-volatile memories. We perform ab-initio molecular dynamics simulations aiming at shading light onto the structure of amorphous Ge2Sb2Te5 (GST), the prototypical material in this class. First principles simulations show that amorphous GST obtained by quenching from the liquid phase displays two types of short range order. One third of Ge atoms are in a tetrahedral environment while the remaining Ge, Sb and Te atoms display a defective octahedral environment, reminiscent of cubic crystalline GST.
Phase diagrams are an invaluable tool for material synthesis and provide information on the phases of the material at any given thermodynamic condition. Conventional phase diagram generation involves experimentation to provide an initial estimate of thermodynamically accessible phases, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to inaccessible regions. Such an approach, combined with first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases albeit at distinct thermodynamic equilibria. In contrast, materials during their synthesis, operation, or processing, may not reach their thermodynamic equilibrium state but, instead, remain trapped in a local free energy minimum, that may exhibit desirable properties. Mapping these metastable phases and their thermodynamic behavior is highly desirable but currently lacking. Here, we introduce an automated workflow that integrates first principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the metastable phases of a given elemental composition. Using a representative material, carbon, with a vast number of metastable phases without parent in equilibrium, we demonstrate automatic mapping of hundreds of metastable states ranging from near equilibrium to those far-from-equilibrium. Moreover, we incorporate the free energy calculations into a neural-network-based learning of the equations of state that allows for construction of metastable phase diagrams. High temperature high pressure experiments using a diamond anvil cell on graphite sample coupled with high-resolution transmission electron microscopy are used to validate our metastable phase predictions. Our introduced approach is general and broadly applicable to single and multi-component systems.
Soft glassy materials are out of thermodynamic equilibrium and show time dependent slowing down of the relaxation dynamics. Under such situation these materials follow Boltzmann superposition principle only in the effective time domain, wherein time dependent relaxation processes are scaled by a constant relaxation time. In this work we extend effective time framework to successfully demonstrate time - temperature superposition of creep and stress relaxation data of a model soft glassy system comprised of clay suspension. Such superposition is possible when average relaxation time of the material changes with time and temperature without affecting shape of the spectrum. We show that variation in relaxation time as a function of temperature facilitates prediction of long and short time rheological behavior through time - temperature superposition from the experiments carried out over experimentally accessible timescales.
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