Eike Gericke | Searcharxiv

arXiv2025

GAMMA_FLOW: Guided Analysis of Multi-label spectra by MAtrix Factorization for Lightweight Operational Workflows

GAMMA_FLOW is an open-source Python package for real-time analysis of spectral data. It supports classification, denoising, decomposition, and outlier detection of both single- and multi-component spectra. Instead of relying on large, computationally intensive models, it employs a supervised approach to non-negative matrix factorization (NMF) for dimensionality reduction. This ensures a fast, efficient, and adaptable analysis while reducing computational costs. gamma_flow achieves classification accuracies above 90% and enables reliable automated spectral interpretation. Originally developed for gamma-ray spectra, it is applicable to any type of one-dimensional spectral data. As an open and flexible alternative to proprietary software, it supports various applications in research and industry.

cs.LG↗

arXiv2020

Quantification of nanoscale density fluctuations in hydrogenated amorphous silicon

The nanostructure of hydrogenated amorphous silicon (a Si:H) is studied by a combination of small-angle X-ray (SAXS) and neutron scattering (SANS) with a spatial resolution of 0.8 nm. The a-Si:H materials were deposited using a range of widely varied conditions and are representative for this class of materials. We identify two different phases which are embedded in the a-Si:H matrix and quantified both according to their scattering cross-sections. First, 1.2 nm sized voids (multivacancies with more than 10 missing atoms) which form a superlattice with 1.6 nm void-to-void distance are detected. The voids are found in concentrations as high as 6*10^19 ccm in a-Si:H material that is deposited at a high rate. Second, dense ordered domains (DOD) that are depleted of hydrogen with 1 nm average diameter are found. The DOD tend to form 10-15 nm sized aggregates and are largely found in all a-Si:H materials considered here. These quantitative findings make it possible to understand the complex correlation between structure and electronic properties of a-Si:H and directly link them to the light-induced formation of defects. Finally, a structural model is derived, which verifies theoretical predictions about the nanostructure of a-Si:H.

cond-mat.mtrl-sci↗