Despite low resistivity (~ 1 m cm), metallic electrical transport has not been commonly observed in the inverse spinel NiCo2O4, except in certain epitaxial thin films. Previous studies have stressed the effect of valence mixing and degree of spinel inversion on the electrical conduction of NiCo2O4 films.In this work, we studied the effect of nanostructural disorder by comparing the NiCo2O4 epitaxial films grown on MgAl2O4 (111) and on Al2O3 (001) substrates. Although the optimal growth conditions are similar for the NiCo2O4 (111)/MgAl2O4 (111) and the NiCo2O4 (111)/Al2O3 (001) films, they show metallic and semiconducting electrical transport respectively. Post-growth annealing decreases the resistivity of NiCo2O4 (111)/Al2O3 (001) films, but the annealed films are still semiconducting. While the semiconductivity and the large magnetoresistance in NiCo2O4 (111)/Al2O3 (001) films cannot be accounted for in terms of the non-optimal valence mixing and spinel inversion, the presence of * Corresponding authors. 2 anti-phase boundaries between nano-sized crystallites, generated by the structural mismatch between NiCo2O4 and Al2O3, may explain all the experimental observations in this work. These results reveal nanostructural disorder as another key factor in controlling the electrical transport of NiCo2O4, with potentially large magnetoresistance for spintronics applications.

Purpose A treatment planning system (TPS) produces volumetric modulated arc therapy (VMAT) plans by applying an optimization process to an objective function, followed by an accurate calculation of the final, deliverable dose. However, during the optimization step, a rapid dose calculation algorithm is required, which reduces its accuracy and its representation of the objective function space. Monte Carlo (MC) routines, considered the gold standard in accuracy, are currently too slow for practical comprehensive VMAT optimization. Therefore, we propose a novel approach called enhanced optimization (EO), which employs the TPS VMAT plan as a starting point, and applies small perturbations to nudge the solution closer to a true objective minimum. The perturbations consist of beamlet dose matrices, calculated using MC routines on a distributed‐computing framework. Methods DICOM files for clinical VMAT plans files are exported from the TPS and used to generate input files for the EGSnrc MC toolkit. Beamlet doses are calculated using the MC routines, each corresponding to a single multileaf collimator leaf from a single control point traveling 0.5 cm in or out of the field. A typical VMAT plan requires 5000 to 10 000 beamlets, which may be calculated overnight. This results in a ternary‐valued objective function, which may use the same clinical objectives as the original VMAT plan. A simple greedy search algorithm is applied to minimize this function and determine the optimal set of ternary variables. The resulting modified control point parameters are imported into the TPS to calculate the final, deliverable dose, and to compare the EO plan with the original. EO was evaluated retrospectively on seven VMAT plans (two adult brain, one pediatric brain, two head and neck, and two prostate). Additionally, the use of stricter objectives was investigated for two of the cases: the left cochlea planning organ at risk (OAR) volume objective for the pediatric brain case, and the rectum objective for a prostate case. Results EO produced improved objective scores (by 6% to 60%) and dose‐volume histograms (DVH) for the brain plans and the head and neck plans. For each of these plans, the target dose minimum and homogeneity were preserved, while one or more of the OAR DVH’s was reduced. Although EO also reduced the objective scores for the prostate plans (by 46% and 79%), their absolute score and DVH improvements were not substantial. The stricter objective on the pediatric brain case resulted in lower dose to the OAR without compromising the target dose. However, the rectum dose in the prostate case could not be improved without reducing dose homogeneity to the planning target volume, suggesting that VMAT prostate cases may already be highly optimized by the TPS. Conclusion We have developed a novel approach to improving the dose distribution of VMAT plans, which relies on MC calculations to provide small modifications to the control points. This method may be particularly useful for complex treatments in which a certain OAR is of c...

To use the open‐source Monte Carlo (MC) software calculations for TPS monitor unit verification of VMAT plans, delivered with the Varian TrueBeam linear accelerator, and compare the results with a commercial software product, following the guidelines set in AAPM Task Group 219. The TrueBeam is modeled in EGSnrc using the Varian‐provided phase‐space files. Thirteen VMAT TrueBeam treatment plans representing various anatomical regions were evaluated, comprising 37 treatment arcs. VMAT plans simulations were performed on a computing cluster, using 107–109 particle histories per arc. Point dose differences at five reference points per arc were compared between Eclipse, MC, and the commercial software, MUCheck. MC simulation with 5 × 107 histories per arc offered good agreement with Eclipse and a reasonable average calculation time of 9–18 min per full plan. The average absolute difference was 3.0%, with only 22% of all points exceeding the 5% action limit. In contrast, the MUCheck average absolute difference was 8.4%, with 60% of points exceeding the 5% dose difference. Lung plans were particularly problematic for MUCheck, with an average absolute difference of approximately 16%. Our EGSnrc‐based MC framework can be used for the MU verification of VMAT plans calculated for the Varian TrueBeam; furthermore, our phase space approach can be adapted to other treatment devices by using appropriate phase space files. The use of 5 × 107 histories consistently satisfied the 5% action limit across all plan types for the majority of points, performing significantly better than a commercial MU verification system, MUCheck. As faster processors and cloud computing facilities become even more widely available, this approach can be readily implemented in clinical settings.

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