2017
DOI: 10.1103/physreve.96.013318
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In silico optimization of critical currents in superconductors

Abstract: For many technological applications of superconductors the performance of a material is determined by the highest current it can carry losslessly-the critical current. In turn, the critical current can be controlled by adding nonsuperconducting defects in the superconductor matrix. Here we report on systematic comparison of different local and global optimization strategies to predict optimal structures of pinning centers leading to the highest possible critical currents. We demonstrate performance of these me… Show more

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Cited by 16 publications
(20 citation statements)
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“…24 Based on the simplified global parameter set, nearoptimal pinscapes can be fine-tuned using conventional optimization methods. 27 Furthermore, one can sample critical currents for near-optimal parameter sets to determine the robustness of the configuration, and compare them to analytical results. 15,[31][32][33][34] Stage 3: Verification.…”
Section: Targeted Evolutionmentioning
confidence: 99%
See 1 more Smart Citation
“…24 Based on the simplified global parameter set, nearoptimal pinscapes can be fine-tuned using conventional optimization methods. 27 Furthermore, one can sample critical currents for near-optimal parameter sets to determine the robustness of the configuration, and compare them to analytical results. 15,[31][32][33][34] Stage 3: Verification.…”
Section: Targeted Evolutionmentioning
confidence: 99%
“…Only recently more systematic, computer-assisted approaches were developed, 24,25 leading to the critical-current-by-design methodology. 26 While sophisticated numerical optimization methods 27 and corresponding experiments can guide the design of superconductors with enhanced critical current densities, J c , the problem requires defining the general geometry of the vortex pinning landscape (or pinscape) a priori. Figure 1: Sketch of a targeted evolution of the pinning landscape.…”
Section: Introductionmentioning
confidence: 99%
“…It was found earlier that the optimal diameter of columnar defects is smaller than the optimal diameter of spherical defects by approximately one coherence length ξ. Since the optimal volume fraction f = 0.2 and diameter of defects d = 3ξ in both cases are similar, 39 we keep them constant in the following analysis, making the optimization problem manageable and effectively a two parameter optimization problem. Figure 1(b) demonstrates the dependency of the critical current on the distance with reduced defect density at the entrance l in and exit l out of vortices for a sample of width W = 64ξ.…”
Section: Resultsmentioning
confidence: 99%
“…Shallow peak both in Jc(B) and angular dependence of B. Shallow peak in Jc(f) and Jc(d) [59,65] Randomly placed spheroids || B and ⟂ J…”
Section: Robustness Of the Optimal Configurationmentioning
confidence: 99%