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We present an in situ PXRD investigation of the mechanochemical cocrystal formation of pyrazinamide with pimelic acid in two milling jar materials. DFT calculations of the two synthesized polymorphs suggest that the relative stability is based on a conformation change of pyrazinamide in the cocrystal.
High-throughput computations are nowadays an established way to suggest new candidate materials for applications to experimentalists. Due to new packages for automation and access to databases of computed materials properties, these studies became more and more complex over the last years. Besides suggesting new candidate materials for applications, they also offer a way to understanding the materials properties based on chemical bonds. For example, we have recently used orbital-based bonding analysis to understand the results of high-throughput studies for spintronic materials, ferroelectric materials and photovoltaic materials in detail. To do so, we have developed Python tools for high-throughput bonding analysis with the programs VASP and Lobster (see www.cohp.de). They are based on the Python packages pymatgen, atomate, and custodian. This implementation will be discussed within the talk. We also expect that these tools offer possibilities to arrive at new descriptors based on chemical bonds for materials properties.
Automation simplifies the use of computational materials science software and makes it accessible to a wide range of users. This enables high-throughput calcula-tionsand makesiteasier for non-specialists to enter computational materials science. However, in-creasing automation also poses threats that should be considered while interacting with automated procedures.
Chemical heuristics are essential to understanding molecules and materials in chemistry. The periodic table, atomic radii, and electronegativities are only a few examples. Initially, they have been developed by a combination of physical insight and a limited amount of data. It is now possible to test these heuristics and generate new ones using automation based on Materials Informatic tools like pymatgen and greater amounts of data from databases such as a Materials Project. In this session, I'll speak about heuristics and design rules based on coordination environments and the concept of chemical bonding. For example, we have tested the Pauling rules which describe the stability of materials based on coordination environments and their connections on 5000 oxides from the Materials Project. In addition, we have created automated processes for analyzing the chemical bonding situation in crystalline materials with Lobster (www.cohp.de) in order to discover new heuristics and design rules.
Next-generation thermal management requires the development of low lattice thermal conductivity materials, as observed in ionic conductors. For example, thermoelectric efficiency is increased when thermal conductivity is decreased. Detrimentally, high ionic conductivity leads to thermoelectric device degradation. Battery safety and design also require an understanding of thermal transport in ionic conductors. Ion mobility, structural complexity, and anharmonicity have been used to explain the thermal transport properties of ionic conductors. However, thermal and ionic transport are rarely discussed in direct comparison. Herein, the ionic conductivity of Ag+ argyrodites is found to change by orders of magnitude without altering the thermal conductivity. Thermal conductivity measurements and two-channel lattice dynamics modeling reveal that the majority of Ag+ vibrations have a non-propagating diffuson-like character, similar to amorphous materials. It is found that high ionic mobility is not a requirement for diffuson-mediated transport. Instead, the same bonding and structural traits that can lead to fast ionic conduction also lead to diffuson-mediated transport. Bridging the fields of solid-state ionics and thermal transport, it is proposed that a vibrational perspective can lead to new design strategies for functional ionic conducting materials. As a first step, the authors relate the so-called Meyer-Neldel behavior in ionic conductors to phonon occupations.
Highly anharmonic thermal vibrations may serve as a source of structural instabilities resulting in phase transitions, chemical reactions and even the mechanical disintegration of a material. Ab initio calculations model thermal motion within a harmonic or sometimes quasi-harmonic approximation and must be complimented by experimental data on temperature-dependent vibrational frequencies. Here multi-temperature atomic displacement parameters (ADPs), derived from a single-crystal synchrotron diffraction experiment, are used to characterize low-frequency lattice vibrations in the alpha-FOX-7 layered structure. It is shown that despite the limited quality of the data, the extracted frequencies are reasonably close to those derived from inelastic scattering, Raman measurements and density functional theory (DFT) calculations. Vibrational anharmonicity is parameterized by the Grüneisen parameters, which are found to be very different for in-layer and out-of-layer vibrations.
Mechanochemical reactions are driven by the direct absorption of mechanical energy by a solid (often crystalline) material. Understanding how this energy is absorbed and ultimately causes a chemical transformation is essential for understanding the elementary stages of mechanochemical transformations. Using as a model system the energetic material LiN3 we here consider how vibrational energy flows through the crystal structure. By considering the compression response of the crystalline material we identify the partitioning of energy into an initial vibrational excitation. Subsequent energy flow is based on concepts of phonon–phonon scattering, which we calculate within a quasi-equilibrium model facilitated by phonon scattering data obtained from Density Functional Theory (DFT). Using this model we demonstrate how the moments (picoseconds) immediately following mechanical impact lead to significant thermal excitation of crystalline LiN3, sufficient to drive marked changes in its electronic structure and hence chemical reactivity. This work paves the way towards an ab initio approach to studying elementary processes in mechanochemical reactions involving crystalline solids.
We created a workflow that fully automates bonding analysis using Crystal Orbital Hamilton Populations, which are bond-weighted densities of states. This enables understanding of crystalline material properties based on chemical bonding information. To facilitate data analysis and machine-learning research, our tools include automatic plots, automated text output, and output in machine-readable format.
A recent approach to measure electron radiation doses in the kGy range is the use of phosphors with an irradiation dose-dependent luminescence decay time. However, the applicability of the previously investigated material NaYF4:Yb3+,Er3+ is limited as it shows pronounced fading. Therefore, in this work, a modified SrF2 synthesis is presented that results in SrF2 nanoparticles codoped with Yb and either Er, Hm, or Tm. To assess their suitability as dosimeter material, dose response, as well as its degree of fading over 50 up to 140 days after irradiation were measured. Fading rates as small as 5% in SrF2:Er,Yb and 4% in SrF2:Ho,Yb were derived, which are comparable to established dosimeter materials. A combination of spectroscopy, diffraction and DFT calculations was used to elucidate the effect of irradiation, pointing towards the formation of a secondary phase of Yb2+ that we predict could be Yb2OF2. This irreversible formation of a secondary phase is considered to be the explanation for the low fading behavior in SrF2-based phosphors compared to NaYF4:Yb, Er, a highly attractive feature for electron beam dosimetry.