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Polarization of ionic and electronic defects in response to high electric fields plays an essential role in determining properties of materials in applications such as memristive devices. However, isolating the polarization response of individual defects has been challenging for both models and measurements. Here the authors quantify the nonlinear dielectric response of neutral oxygen vacancies, comprised of strongly localized electrons at an oxygen vacancy site, in perovskite oxides of the form ABO

Machine learning has demonstrated great power in materials design, discovery, and property prediction. However, despite the success of machine learning in predicting discrete properties, challenges remain for continuous property prediction. The challenge is aggravated in crystalline solids due to crystallographic symmetry considerations and data scarcity. Here, the direct prediction of phonon density‐of‐states (DOS) is demonstrated using only atomic species and positions as input. Euclidean neural networks are applied, which by construction are equivariant to 3D rotations, translations, and inversion and thereby capture full crystal symmetry, and achieve high‐quality prediction using a small training set of ≈103 examples with over 64 atom types. The predictive model reproduces key features of experimental data and even generalizes to materials with unseen elements, and is naturally suited to efficiently predict alloy systems without additional computational cost. The potential of the network is demonstrated by predicting a broad number of high phononic specific heat capacity materials. The work indicates an efficient approach to explore materials' phonon structure, and can further enable rapid screening for high‐performance thermal storage materials and phonon‐mediated superconductors., A machine‐learning‐based predictive model allows a direct output of phonon density‐of‐states (DOS) by inputting atomic coordinates. The implemented Euclidean neural network preserves crystallographic symmetry and enables high‐quality prediction with small training data. The model allows for fast DOS calculation, reaching ab initio accuracy for 70–80% materials with much lowered computational cost, facilitating materials design especially in alloy systems.

Phonon density‐of‐states is a key property that governs materials thermal properties but is nontrivial to compute or measure. A neural network that carries full crystal symmetry allows a prediction of phonon density‐of‐states using a small volume of training data, approaching ab initio accuracy but with significantly increased efficiency, as demonstrated in article number 2004214, by Mingda Li, Zhantao Chen, Nina Andrejevic, Tess Smidt, and co‐workers. This work enables direct structure‐property design of materials with superior thermal properties. [Image: see text]

Non-stoichiometric oxides are used in a wide variety of applications including solid oxide fuel cells (SOFCs), lithium ion batteries (LIBs), gas sensors, and catalysis. Through the capacity of such materials to support large point defect concentrations, these functional oxides can readily store, transport, and exchange ions. An important consequence of this non-stoichiometry is a tendency toward chemomechanical coupling, particularly in the form of chemical expansion, or the coupling between material volume and defect concentration. Thin films of non-stoichiometric oxides are of particular interest in such device designs, given the potential for strain engineering. For example, it has been shown for several materials that tensile strain can increase the ionic conductivity or gas exchange reactivity for oxygen by up to an order of magnitude, potentially enabling enhanced device efficiency or decreased operating temperatures1. In electrochemical devices, chemical expansion can generate stress or strain that can lead to mechanical failure, and/or changes in mechanical properties including elastic moduli. Given the extreme environments and range of non-stoichiometric oxides in which chemical expansion can be expected, robust device design requires accurate, flexible, and rapid characterization of environmental conditions and materials that maximize (or minimize) chemical expansion in situ. However, methods used at present for characterizing chemomechanical expansion, such as dilatometry, synchrotron techniques, reflectometry, and others, are not amenable to thin films or are difficult to implement in standard laboratory settings. Recently, Swallow et al. described an approach for characterizing thin film non-stoichiometric oxide chemical expansion at high temperatures by way of electrochemically induced actuation that addresses the above needs2. That work characterized volume change within a fluorite film of PrxCe1-xO2-δ (PCO) and structural deflection of the PCO/YSZ (yttria-stablized zirconia) bilayer during electrochemical pumping of oxygen ions into the PCO film. It also demonstrated a positive attribute of such chemical expansion in the form of high temperature oxide actuators, which harness electrochemically generated chemical strain to produce measurable, nanoscale device deflections. The actuation produced ranged between 5-15 nm of displacement amplitude depending on the experimental conditions2. Here, we provide an extended and graphically rich analysis of electrical and mechanical response data from such experiments. We model the current and mechanical response of PCO to an electrochemical driving force using previously established defect equilibria and kinetic relationships for that oxide, demonstrating the contributions that material properties and sample geometries make to device deflection and electrochemical pumping. We also extend the measurement approach to an additional material system, the perovskite-structured oxide SrTi0.65Fe0,35O3-δ (STF) used as part of magnetic memory devices, gas transport membranes, and fuel cells. This case study demonstrates the broad applicability of this measurement method, as well as means to leverage chemical expansion effects at elevated temperatures for diverse actuating and functional devices. Yildiz, B. ‘Stretching’ the energy landscape of oxides—Effects on electrocatalysis and diffusion. MRS Bull. 39, 147–156 (2014). Swallow, J. G. et al. Dynamic chemical expansion of thin-film non-stoichiometric oxides at extreme temperatures. Nat Mater (2017). doi:10.1038/nmat4898

Objective.Radiopharmaceutical production process must adhere to current good manufacturing process (CGMP) compliance to ensure the quality of precursor, prodrug (active pharmaceutical ingredient, API), and the final drug product that meet acceptance criteria. We aimed to develop an automated system for production of CGMP grade of PET radiopharmaceuticals.Methods.The hardware and software of the automated synthesizer that fit in the hot cell under cGMP requirement were developed. Examples of production yield and purity for68Ga-DOTATATE and18F-FDG at CGMP facility were optimized. Analytical assays and acceptance criteria for cGMP grade of68Ga-DOTATATE and18F-FDG were established.Results.CGMP facility for the production of PET radiopharmaceuticals has been established. Radio-TLC and HPLC analyses of68Ga-DOTATATE and18F-FDG showed that the radiochemical purity was 92% and 96%, respectively. The products were sterile and pyrogenic-free.Conclusion.CGMP compliance of radiopharmaceuticals has been reviewed.68Ga-DOTATATE and18F-FDG were synthesized with high radiochemical yield under CGMP process.

Radiopharmaceutical production process must adhere to current good manufacturing process (CGMP) compliance to ensure the quality of precursor, prodrug (active pharmaceutical ingredient, API), and the final drug product that meet acceptance criteria. We aimed to develop an automated system for production of CGMP grade of PET radiopharmaceuticals.The hardware and software of the automated synthesizer that fit in the hot cell under cGMP requirement were developed. Examples of production yield and purity for (68)Ga-DOTATATE and (18)F-FDG at CGMP facility were optimized. Analytical assays and acceptance criteria for cGMP grade of (68)Ga-DOTATATE and (18)F-FDG were established.CGMP facility for the production of PET radiopharmaceuticals has been established. Radio-TLC and HPLC analyses of (68)Ga-DOTATATE and (18)F-FDG showed that the radiochemical purity was 92% and 96%, respectively. The products were sterile and pyrogenic-free.CGMP compliance of radiopharmaceuticals has been reviewed. (68)Ga-DOTATATE and (18)F-FDG were synthesized with high radiochemical yield under CGMP process.