arXiv subjects

John Banhart

Publications and source records attributed to John Banhart.

4 recordsLinked to original sources

arXiv2026

Clustering in atom probe tomography data: coordination number metric, percolation-based parameter scaling, and size effects

The ability to identify nanometer-scale nuclei of new phases in atom probe tomography (APT) is often limited by the sensitivity of clustering algorithms to user-defined control parameters. Conventional approaches typically rely on the Euclidean distance metric and consider only solute atoms, thereby discarding the solvent atoms that contain most of the spatial information. Here, we introduce a coordination-number metric based on the composition and apply it to higher-order clustering. Using various metrics, we investigate percolation in typical APT structures. By scaling clustering properties to the corresponding percolation thresholds, we define a self-similar variable that is almost invariant with respect to metrics, clustering parameters, and structural disorder. This variable provides a relevant description of clustering and enables the formal transfer of optimal parameters between clustering methods. We also study the characteristic clustering behavior in small precipitates and quantify how the precipitate-matrix interface alters the composition spectrum and broadens the clustering curve. Finally, using simulations that incorporate finite spatial resolution, detection efficiency, and other APT reconstruction artifacts, we show that the approach based on coordination numbers effectively compensates for heterogeneous dilations and outperforms solute-density-based methods in all tested scenarios.

cond-mat.mtrl-sci↗

arXiv2022

Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

FIB/SEM tomography represents an indispensable tool for the characterization of three-dimensional nanostructures in battery research and many other fields. However, contrast and 3D classification/reconstruction problems occur in many cases, which strongly limits the applicability of the technique especially on porous materials, like those used for electrode materials in batteries or fuel cells. Distinguishing the different components like active Li storage particles and carbon/binder materials is difficult and often prevents a reliable quantitative analysis of image data, or may even lead to wrong conclusions about structure-property relationships. In this contribution, we present a novel approach for data classification in three-dimensional image data obtained by FIB/SEM tomography and its applications to NMC battery electrode materials. We use two different image signals, namely the signal of the angled SE2 chamber detector and the Inlens detector signal, combine both signals and train a random forest, i.e. a particular machine learning algorithm. We demonstrate that this approach can overcome current limitations of existing techniques suitable for multi-phase measurements and that it allows for quantitative data reconstruction even where current state-of the art techniques fail, or demand for large training sets. This approach may yield as guideline for future research using FIB/SEM tomography.

cond-mat.mtrl-sci↗

arXiv2020

Microscopic aspects of artificial ageing in Al-Mg-Si alloys

Al-Mg-Si alloys with total solute contents ranging from 0.8 to 1.4 wt.% were solutionised, quenched and then artificially aged (AA) at 180 °C, after which positron annihilation lifetime spectroscopy was applied to obtain information about precipitation and vacancy evolution during preceding ageing. Hardness and electrical resistivity measurements were carried out to complement these measurements. AA was carried out in four different heating media, which allowed for varying the heating rate from 2.4 K/s to 170 K/s. The main result of the study is that there is a competition between vacancy losses and precipitation. Any precipitation taking place during quenching or during heating to the AA temperature helps to prevent vacancies from going to sinks and allows them to assist in solute clustering. Higher solute content, slower heating to 180 °C and natural pre-ageing before AA were found to have a comparable effect.

cond-mat.mtrl-sci↗

arXiv2013

Nanoscale order in the frustrated mixed conductor La$_{5.4}WO$_{12-δ}$

We report a comprehensive investigation of the average and local structure of La$_{5.4}$WO$_{12-δ}$, which has excellent mixed proton, electron and oxide ion conduction suitable for device applications. Synchrotron X-ray and neutron powder diffraction show that a cubic fluorite supercell describes the average structure, with highly disordered lanthanum and oxide positions. On average the tungsten sites are six-fold coordinated, and we detect a trace (4.4(2) %) of anti-site disorder. In addition to sharp Bragg reflections, strong diffuse neutron scattering is observed, which hints at short-range order. We consider plausible local configurations, and show that the defect chemistry implies a simple 'chemical exchange' interaction that favours ordered WO6 octahedra. Our local model is confirmed by synchrotron x-ray pair distribution function analysis and EXAFS experiments performed at the La K and W L3-edges. We show that ordered domains of around ca. 3.5 nm are found, implying that mixed conduction in La$_{5.4}$WO$_{12-δ}$? is associated with a defective glassy-like anion sublattice. The origins of this ground state are proposed to lie in the non-bipartite nature of the fcc lattice and the pairwise interactions which link the orientation of neighbouring octahedral WO6 sites. This 'function through frustration' could provide a means of designing new mixed conductors.

cond-mat.mtrl-sci↗