Related papers: Machine learning for analysis of plasma driven Ion…
A one dimensional model of the magnetic multipole volume plasma source has been developed for use in intense ion/neutral atom beam injectors. The model uses plasma transport coefficients for particle and energy flow to create a detailed…
Ion Beam Analysis (IBA) is an established tool for material characterization, providing precise information on elemental composition, depth profiles, and structural information in the region near the surface of materials. However,…
Ion beam analysis techniques are among the most powerful tools for advanced material characterization. Despite their growing relevance in a widening number of fields, most ion beam analysis facilities still rely on the oldest accelerator…
Machine learning is applied to derive microscopically parameters of the interacting boson model for nuclear spectroscopy. A physics-guided neural network is proposed, which is trained to map the potential energy landscapes that are…
A one dimensional model of the magnetic multipole volume plasma source has been developed for application to intense ion/neutral atom beam injectors. The model uses plasma transport coefficients for particle and energy flow to create a…
We use machine learning models to predict ion density and electron temperature from visible emission spectra, in a high energy density pulsed-power-driven aluminum plasma, generated by an exploding wire array. Radiation transport…
Beams of radioactive heavy ions allow researchers to study rare and unstable atomic nuclei, shedding light into the internal structure of exotic nuclei and on how chemical elements are formed in stars. However, the extraction and transport…
The design and characterization of a new laser-desorption molecular beam source, tailored for use in x-ray-free-electron-laser and ultrashort-pulse-laser imaging experiments, is presented. It consists of a single mechanical unit containing…
Machine learning is becoming a new paradigm for scientific research in various research fields due to its exciting and powerful capability of modeling tools used for big-data processing task. In this mini-review, we first briefly introduce…
The development of compact neutron sources for applications is extensive and features many approaches. Let alone ion-based approaches, several projects with different parameters exist. This article focuses on ion-based neutron production…
Ion sources are a critical component of all particle accelerators. They create the initial beam that is accelerated by the rest of the machine. This paper will introduce the many methods of creating a beam for high-power hadron…
Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the…
Compact, stable, and versatile laser-driven ion sources hold great promise for applications ranging from medicine to materials science and fundamental physics. While single-shot sources have demonstrated favorable beam properties, including…
Laser-driven ion acceleration provides ultra-short, high-charge, low-emittance beams, which are desirable for a wide range of high-impact applications. Yet after decades of research, a significant increase in maximum ion energy is still…
Modeling the ion concentration profile in nanochannel plays an important role in understanding the electrical double layer and electroosmotic flow. Due to the non-negligible surface interaction and the effect of discrete solvent molecules,…
Laser-driven operations are a common approach for engineering one- and two-qubit gates in trapped-ion arrays. Measuring key parameters of these lasers, such as beam sizes, intensities, and polarizations, is central to predicting and…
Fast ionic conduction is a defining property of solid electrolytes for all-solid-state batteries. Previous studies have suggested that liquid-like cation motion associated with fast ionic transport can disrupt crystalline symmetry, thereby…
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is…
The recent advent of deep artificial neural networks has resulted in a dramatic increase in performance for object classification and detection. While pre-trained with everyday objects, we find that a state-of-the-art object detection…
As the main $H^{-}$ ion source for the accelerator complex, magnetron ion sources have been used at Fermilab since the 1970s. At the offline test stand, new R&D is carried out to develop and upgrade the present magnetron-type sources of…