Kinetic Control of Ultrafast Transient Liquid Assisted Growth of Solution-Derived YBa2 Cu3 O7 -x Superconducting Films.

Transient liquid assisted growth (TLAG) is an ultrafast non-equilibrium growth process mainly governed by kinetic parameters, which are only accessible through fast in situ characterizations. In situ synchrotron X-ray diffraction (XRD) analysis and in situ electrical resistivity measurements are used to derive kinetic diagrams of YBa2 Cu3 O7- x (YBCO) superconducting films prepared via TLAG and to reveal the unique peculiarities of the process. In particular, diagrams for the phase evolution and the YBCO growth rates have been built for the two TLAG routes. It is shown that TLAG transient liquids can be obtained upon the melting of two barium cuprate phases (and not just one), differentiated by their copper oxidation state. This knowledge serves as a guide to determine the processing conditions to reach high performance films at high growth rates. With proper control of these kinetic parameters, films with critical current densities of 2-2.6 MA cm-2 at 77 K and growth rates between 100-2000 nm s-1 are reached. These growth rates are 1.5-3 orders of magnitude higher than those of conventional methods.

Defining inkjet printing conditions of superconducting cuprate films through machine learning.

The design and optimization of new processing approaches for the development of rare earth cuprate (REBCO) high temperature superconductors is required to increase their cost-effective fabrication and promote market implementation. The exploration of a broad range of parameters enabled by these methods is the ideal scenario for a new set of high-throughput experimentation (HTE) and data-driven tools based on machine learning (ML) algorithms that are envisaged to speed up this optimization in a low-cost and efficient manner compatible with industrialization. In this work, we developed a data-driven methodology that allows us to analyze and optimize the inkjet printing (IJP) deposition process of REBCO precursor solutions. A dataset containing 231 samples was used to build ML models. Linear and tree-based (Random Forest, AdaBoost and Gradient Boosting) regression algorithms were compared, reaching performances above 87%. Model interpretation using Shapley Additive Explanations (SHAP) revealed the most important variables for each study. We could determine that to ensure homogeneous CSD films of 1 micron thickness without cracks after the pyrolysis, we need average drop volumes of 190-210 pl, and no. of drops between 5000 and 6000, delivering a total volume deposited close to 1 µl.

Semimechanistic models to relate noxious stimulation, movement, and pupillary dilation responses in the presence of opioids.

Intraoperative targeting of the analgesic effect still lacks an optimal solution. Opioids are currently the main drug used to achieve antinociception, and although underdosing can lead to an increased stress response, overdose can also lead to undesirable adverse effects. To better understand how to achieve the optimal analgesic effect of opioids, we studied the influence of remifentanil on the pupillary reflex dilation (PRD) and its relationship with the reflex movement response to a standardized noxious stimulus. The main objective was to generate population pharmacodynamic models relating remifentanil predicted concentrations to movement and to pupillary dilation during general anesthesia. A total of 78 patients undergoing gynecological surgery under general anesthesia were recruited for the study. PRD and movement response to a tetanic stimulus were measured multiple times before and after surgery. We used nonlinear mixed effects modeling to generate a population pharmacodynamic model to describe both the time profiles of PRD and movement responses to noxious stimulation. Our model demonstrated that movement and PRD are equally depressed by remifentanil. Using the developed model, we changed the intensity of stimulation and simulated remifentanil predicted concentrations maximizing the probability of absence of movement response. An estimated effect site concentration of 2 ng/ml of remifentanil was found to inhibit movement to a tetanic stimulation with a probability of 81%.

Combinatorial Screening of Cuprate Superconductors by Drop-On-Demand Inkjet Printing.

Combinatorial and high-throughput experimentation (HTE) is achieving more relevance in material design, representing a turning point in the process of accelerated discovery, development, and optimization of materials based on data-driven approaches. The versatility of drop-on-demand inkjet printing (IJP) allows performing combinatorial studies through fabrication of compositionally graded materials with high spatial precision, here by mixing superconducting REBCO precursor solutions with different rare earth (RE) elements. The homogeneity of combinatorial Y1-xGdxBa2Cu3O7 samples was designed with computational methods and confirmed by energy-dispersive X-ray spectroscopy (EDX) and high-resolution X-ray diffraction (XRD). We reveal the advantages of this strategy in the optimization of the epitaxial growth of high-temperature REBCO superconducting films using the novel transient liquid-assisted growth method (TLAG). Advanced characterization methods, such as in situ synchrotron growth experiments, are tailored to suit the combinatorial approach and demonstrated to be essential for HTE schemes. The experimental strategy presented is key for the attainment of large datasets for the implementation of machine learning backed material design frameworks.