• Other research products close
• UK Research and Innovation close

In the presented study variable temperature Flowing Afterglow with Langmuir Probe - VT-FALP was used to study plasma decay in D_2/He mixture at temperatures down to 130 K and total pressure up to 10 Torr. Large extent of partial number densities of D_2 (10^12-3x10^15cm^-3) were used in the experiments. Langmuir probes and mass spectrometers were applied to monitor decay of the plasma during the afterglow. The study is continuation of our previous measurements of recombination rate coefficients of D_3^+ and D_5^+ ions. In these studies we observed dependence of the recombination rate coefficient on partial pressure of deuterium indicating that third-body assisted recombination is efficient and significantly contributes to recombination in decaying deuterium-containing plasma. In He/D_2 mixture at low D_2 number densities ions D_3^+ dominate the ion composition in the afterglow, the plasma decay is controlled by recombination of D_3^+ ions (with rate coefficient \alpha_3). At high D_2 number densities and lower temperatures ions D_5^+ are effectively formed and plasma decay is controlled by recombination of D_5^+ ions (\alpha_5). In the intermediate region the decay of plasma is governed by recombination of both ions with electrons and by ion molecule reactions (forward three-body association and reverse collision induced dissociation), which are keeping equilibrium between D_3^+ and D_5^+: D_3^+ + D_2 + He D_5^+ + He. In the equilibrium ratio [D_5^+]/[D_3^+]= K_C[D_2], where K_C is the equilibrium constant. If the mentioned four processes are dominant processes during the afterglow the decay of plasma can be described by an overall (apparent) effective recombination rate coefficient \alpha_eff, which can be expressed by equation: \alpha_eff= (\alpha_3 + \alpha_5K_C[D_2])/(1+ K_C[D_2]). The temperature dependence of observed recombination rate \alpha_eff is coupled with the temperature dependences of \alpha_3 and \alpha_5 and predominantly with strong temperature dependence of K_C given by van't Hoff equation. From the measurements at low partial number densities [D_2] (=10^12-3x10^13cm^-3) where influence of formation of D_5^+ can be neglected the dependence \alpha_3 = \alpha_3(T) was obtained. From the data at intermediate and higher [D_2] values K_C and \alpha_5 were estimated and are reported in the paper. Obtained results are in good agreement with thermodynamic data.

This invited paper considers a key next step in the design of radio architectures aimed at supporting low energy consumption in 5G heterogeneous radio access networks. State-of-the-art mobile radios usually require one RF transceiver per standard, each working separately at any given time. Software defined radios, while spanning a wide range of standards and frequency bands, also work separately at any specific time. In 5G radio access networks, where continuous, multiband connectivity is envisaged, this conventional radio architecture results in high network power consumption. In this paper, we propose the novel concept of a concurrent multiband frequency-agile radio (CM-FARAD) architecture, which simultaneously supports multiple standards and frequency bands using a single, tunable transceiver. We discuss the subsystem radio design approaches for enabling the CM-FARAD architecture, including antennas, power amplifiers, low noise amplifiers and analogue to digital converters. A working prototype of a dual-band CM-FARAD test-bed is also presented together with measured salient performance characteristics.

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. This white paper discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

Detailed $\gamma$-ray spectroscopy of the exotic neon isotope $^{28}$Ne has been performed for the first time using the one-neutron removal reaction from $^{29}$Ne on a liquid hydrogen target at 240~MeV/nucleon. Based on an analysis of parallel momentum distributions, a level scheme with spin-parity assignments has been constructed for $^{28}$Ne and the negative-parity states are identified for the first time. The measured partial cross sections and momentum distributions reveal a significant intruder $p$-wave strength providing evidence of the breakdown of the $N=20$ and $N=28$ shell gaps. Only a weak, possible $f$-wave strength was observed to bound final states. Large-scale shell-model calculations with different effective interactions do not reproduce the large $p$-wave and small $f$-wave strength observed experimentally, indicating an ongoing challenge for a complete theoretical description of the transition into the island of inversion along the Ne isotopic chain. Detailed γ-ray spectroscopy of the exotic neon isotope 28Ne has been performed for the first time using the one-neutron removal reaction from 29Ne on a liquid hydrogen target at 240 MeV/nucleon. Based on an analysis of parallel momentum distributions, a level scheme with spin-parity assignments has been constructed for 28Ne and the negative-parity states are identified for the first time. The measured partial cross sections and momentum distributions reveal a significant intruder p-wave strength providing evidence of the breakdown of the N=20 and N=28 shell gaps. Only a weak, possible f-wave strength was observed to bound final states. Large-scale shell-model calculations with different effective interactions do not reproduce the large p-wave and small f-wave strength observed experimentally, indicating an ongoing challenge for a complete theoretical description of the transition into the island of inversion along the Ne isotopic chain.

Detection of a gravitational-wave signal of non-astrophysical origin would be a landmark discovery, potentially providing a significant clue to some of our most basic, big-picture scientific questions about the Universe. In this white paper, we survey the leading early-Universe mechanisms that may produce a detectable signal -- including inflation, phase transitions, topological defects, as well as primordial black holes -- and highlight the connections to fundamental physics. We review the complementarity with collider searches for new physics, and multimessenger probes of the large-scale structure of the Universe. Detection of a gravitational-wave signal of non-astrophysical origin would be a landmark discovery, potentially providing a significant clue to some of our most basic, big-picture scientific questions about the Universe. In this white paper, we survey the leading early-Universe mechanisms that may produce a detectable signal—including inflation, phase transitions, topological defects, as well as primordial black holes—and highlight the connections to fundamental physics. We review the complementarity with collider searches for new physics, and multimessenger probes of the large-scale structure of the Universe.

The use of artificial intelligence and machine learning techniques across all disciplines has exploded in the past few years, with the ever-growing size of data and the changing needs of higher education, such as digital education. Similarly, online educational information systems have a huge amount of data related to students in digital education. This educational data can be used with artificial intelligence and machine learning techniques to improve digital education. This study makes two main contributions. First, the study follows a repeatable and objective process of exploring the literature. Second, the study outlines and explains the literature's themes related to the use of AI-based algorithms in digital education. The study findings present six themes related to the use of machines in digital education. The synthesized evidence in this study suggests that machine learning and deep learning algorithms are used in several themes of digital learning. These themes include using intelligent tutors, dropout predictions, performance predictions, adaptive and predictive learning and learning styles, analytics and group-based learning, and automation. artificial neural network and support vector machine algorithms appear to be utilized among all the identified themes, followed by random forest, decision tree, naive Bayes, and logistic regression algorithms.