Related papers: PGNAA Spectral Classification of Aluminium and Cop…
For environmental, sustainable economic and political reasons, recycling processes are becoming increasingly important, aiming at a much higher use of secondary raw materials. Currently, for the copper and aluminium industries, no method…
There is a pressing market demand to minimize the test time of Prompt Gamma Neutron Activation Analysis (PGNAA) spectra measurement machine, so that it could function as an instant material analyzer, e.g. to classify waste samples…
High Purity Germanium (HPGe) detectors are powerful detectors for gamma-ray spectroscopy. The sensitivity to low-intensity gamma-ray peaks is often hindered by the presence of Compton continuum distributions, originated by gamma-rays…
We describe here an efficient machine-learning based approach for the optimization of parameters used for extracting the arrival time of waveforms, in particular those generated by the detection of 511 keV annihilation gamma-rays by a 60…
Metallic materials such as brass, copper, and aluminum are used in numerous applications, including industrial manufacturing. The vibration characteristics of these objects are unique and can be used to identify these objects from a…
High Purity Germanium (HPGe) detectors have been golden standard for gamma spectrometry in Low level radioactive waste (LLW) analysis; however, their notable shortcoming is prolonged measurement durations for weak radioactive waste…
Machine learning offers remarkable benefits for improving workplaces and working conditions amongst others in the recycling industry. Here e.g. hand-sorting of medium value scrap is labor intensive and requires experienced and skilled…
Neutrinoless double beta decay ($0\nu\beta\beta$) offers a sensitive probe of neutrino mass and its Majorana nature. Orthogonal-strip high-purity germanium (HPGe) detectors with high spatial resolution provide a promising approach for…
A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate…
We report a framework for spectroscopic follow-up design for optimizing supernova photometric classification. The strategy accounts for the unavoidable mismatch between spectroscopic and photometric samples, and can be used even in the…
The Majorana Demonstrator is a leading experiment searching for neutrinoless double-beta decay with high purity germanium detectors (HPGe). Machine learning provides a new way to maximize the amount of information provided by these…
Diagnostics are critical on the path to commercial fusion reactors, since measurements and characterisation of the plasma is important for sustaining fusion reactions. Gamma spectroscopy is commonly used to provide information about the…
In the dynamic and rapidly advancing battery field, alloy anode materials are a focal point due to their superior electrochemical performance. Traditional screening methods are inefficient and time-consuming. Our research introduces a…
The analog signals generated in the read-out electronics of radiation detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital…
The discovery of complex concentrated alloys has unveiled materials with diverse atomic environments, prompting the exploration of solute segregation beyond dilute alloys. Data-driven methods offer promising for modeling segregation in such…
Experiments to search for neutrinoless double-beta (0{\nu}\b{eta}\b{eta}) decay of 76Ge using a high-purity germanium (HPGe) detector rely heavily on background suppression technologies to enhance their sensitivities. In this work, we…
Pulse-shape discrimination (PSD) in high-purity germanium (HPGe) detectors is central to rare-event searches such as neutrinoless double-beta decay (0vBB), yet conventional approaches compress each waveform into a small set of summary…
Pollution and climate change are some of the biggest challenges that humanity is facing. In such a context, efficient recycling is a crucial tool for a sustainable future. This work is aimed at creating a system that can classify different…
Refractory high-entropy alloys can function at temperatures exceeding those of nickel-based superalloys. Aluminum, as an alloying element, contributes multiple advantageous characteristics to various high-temperature alloys. The Aluminum…
Laser induced breakdown spectroscopy technique is employed for quantitative analysis of aluminum samples by different classical machine learning approaches. A Q-switch Nd:YAG laser at fundamental harmonic of 1064 nm is utilized for creation…