One of the critical challenges in future high-current tokamaks is the avoidance of runaway electrons during disruptions. Here, we investigate disruptions mitigated with combined deuterium and noble gas injection in SPARC. We use multi-objective Bayesian optimisation of the densities of the injected material, taking into account limits on the maximum runaway current, the transported fraction of the heat loss and the current quench time. The simulations are conducted using the numerical framework Dream (disruption runaway electron analysis model). We show that during deuterium operation, runaway generation can be avoided with material injection, even when we account for runaway electron generation from deuterium–deuterium induced Compton scattering. However, when including the latter, the region in the injected-material-density space corresponding to successful mitigation is reduced. During deuterium–tritium operation, acceptable levels of runaway current and transported heat losses are only obtainable at the highest levels of achievable injected deuterium densities. Furthermore, disruption mitigation is found to be more favourable when combining deuterium with neon, compared with deuterium combined with helium or argon.

Accurate modelling of runaway electron generation and losses during tokamak disruptions is crucial for the development of reactor-scale tokamak devices. In this paper, we present a reduced model for runaway electron losses due to flux surface scrape-off caused by the vertical motion of the plasma. The model is made compatible with computationally inexpensive one-dimensional models averaging over a fixed flux-surface geometry, by formulating it as a loss term outside an estimated time-varying minor radius of the last closed flux surface. We then implement this model in the disruption modelling tool DREAM and demonstrate its impact on selected scenarios relevant for ITER. Our results indicate that scrape-off losses may be crucial for making complete runaway avoidance possible even in a $15\,\rm MA$ DT H-mode ITER scenario. The results are however sensitive to the details of the runaway electron generation and phenomena affecting the current density profile, such as the current profile relaxation at the beginning of the disruption.

When simulating runaway electron dynamics in tokamak disruptions, fluid models with lower numerical cost are often preferred to more accurate kinetic models. The aim of this work is to compare fluid and kinetic simulations of a large variety of different disruption scenarios in ITER. We consider both non-activated and activated scenarios; for the latter, we derive and implement kinetic sources for the Compton scattering and tritium beta decay runaway electron generation mechanisms in our simulation tool Dream (Hoppe et al., Comput. Phys. Commun., vol. 268, 2021, 108098). To achieve a diverse set of disruption scenarios, Bayesian optimization is used to explore a range of massive material injection densities for deuterium and neon. The cost function is designed to distinguish between successful and unsuccessful disruption mitigation based on the runaway current, current quench time and transported fraction of the heat loss. In the non-activated scenarios, we find that fluid and kinetic disruption simulations can have significantly different runaway electron dynamics, due to an overestimation of the runaway seed by the fluid model. The primary cause of this is that the fluid hot-tail generation model neglects superthermal electron transport losses during the thermal quench. In the activated scenarios, the fluid and kinetic models give similar predictions, which can be explained by the significant influence of the activated sources on the runaway dynamics and the seed.

As mental health issues continue to rise in Latin America, the need for research in this field becomes increasingly pressing. This study aimed to explore the perceived barriers and resources for research and publications among psychiatrists and psychiatry trainees from nine Spanish-speaking countries in South America. Data was collected through an anonymous online survey and analyzed using descriptive methods and the SPSS Statistical package. In total, 214 responses were analyzed. Among the participating psychiatrists, 61.8% reported having led a research project and 74.7% of them reported having led an academic publication. As for the psychiatry trainees, 26% reported having conducted research and 41.5% reported having published or attempted to publish an academic paper. When available, having access to research training, protected research time and mentorship opportunities were significant resources for research. Further support is needed in terms of funding, training, protected research time and mentorship opportunities. However, despite their efforts to participate in the global mental health discussion, Latin American psychiatrists and psychiatry trainees remain largely underrepresented in the literature.

A Bayesian optimization framework is used to investigate scenarios for disruptions mitigated with combined deuterium and neon injection in ITER. The optimization cost function takes into account limits on the maximum runaway current, the transported fraction of the heat loss and the current quench time. The aim is to explore the dependence of the cost function on injected densities, and provide insights into the behaviour of the disruption dynamics for representative scenarios. The simulations are conducted using the numerical framework Dream (Disruption Runaway Electron Analysis Model). We show that, irrespective of the quantities of the material deposition, multi-megaampere runaway currents will be produced in the deuterium–tritium phase of operations, even in the optimal scenarios. However, the severity of the outcome can be influenced by tailoring the radial profile of the injected material; in particular, if the injected neon is deposited at the edge region it leads to a significant reduction of both the final runaway current and the transported heat losses. The Bayesian approach allows us to map the parameter space efficiently, with more accuracy in favourable parameter regions, thereby providing us with information about the robustness of the optima.

Plasma-terminating disruptions in future fusion reactors may result in conversion of the initial current to a relativistic runaway electron beam. Validated predictive tools are required to optimise the scenarios and mitigation actuators to avoid the excessive damage that can be caused by such events. Many of the simulation tools applied in fusion energy research require the user to specify input parameters that are not constrained by the available experimental information. The conventional approach, where an expert modeller calibrates these input parameters based on domain knowledge, is prone to lead to an intractable validation challenge without systematic uncertainty quantification. Bayesian inference algorithms offer a promising alternative approach that naturally includes uncertainty quantification and is less subject to user bias in choosing the input parameters. The main challenge in using these methods is the computational cost of simulating enough samples to construct the posterior distributions for the uncertain input parameters. This challenge can be overcome by combining probabilistic surrogate modelling, such as Gaussian process regression, with Bayesian optimisation, which can reduce the number of required simulations by several orders of magnitude. Here, we implement this type of Bayesian optimisation framework for a model for analysis of disruption runaway electrons, and explore for simulations of current quench in a JET plasma discharge with an argon induced disruption. We use this proof-of-principle framework to explore the optimum input parameters with uncertainties in optimisation tasks ranging from one to seven dimensions. The relevant Python codes that are used in the analysis are available via https://github.com/aejarvin/BO_FOR_RE_SIMULATIONS/.

Tokamak start-up is characterized by low electron densities and strong electric fields, in order to quickly raise the plasma current and temperature, allowing the plasma to fully ionize and magnetic flux surfaces to form. Such conditions are ideal for the formation of superthermal electrons, which may reduce the efficiency of ohmic heating and prevent the formation of a healthy thermal fusion plasma. This is of particular concern in ITER where engineering limitations put restrictions on the allowable electric fields and limit the prefill densities during start-up. In this study, we present a new 0D burn-through simulation tool called STREAM (STart-up Runaway Electron Analysis Model), which self-consistently evolves the plasma density, temperature and electric field, while accounting for the generation and loss of relativistic runaway electrons. After verifying the burn-through model, we investigate conditions under which runaway electrons can form during tokamak start-up as well as their effects on the plasma initiation. We find that Dreicer generation plays a crucial role in determining whether a discharge becomes runaway-dominated or not, and that a large number of runaway electrons could limit the ohmic heating of the plasma, thus preventing successful burn-through or further ramp-up of the plasma current. The runaway generation can be suppressed by raising the density via gas fuelling, but only if done sufficiently early. Otherwise a large runaway seed may have already been built up, which can avalanche even at relatively low electric fields and high densities.

The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.

Synchrotron radiation images from runaway electrons (REs) in an ASDEX Upgrade discharge disrupted by argon injection are analysed using the synchrotron diagnostic tool Soft and coupled fluid-kinetic simulations. We show that the evolution of the runaway distribution is well described by an initial hot-tail seed population, which is accelerated to energies between 25–50 MeV during the current quench, together with an avalanche runaway tail which has an exponentially decreasing energy spectrum. We find that, although the avalanche component carries the vast majority of the current, it is the high-energy seed remnant that dominates synchrotron emission. With insights from the fluid-kinetic simulations, an analytic model for the evolution of the runaway seed component is developed and used to reconstruct the radial density profile of the RE beam. The analysis shows that the observed change of the synchrotron pattern from circular to crescent shape is caused by a rapid redistribution of the radial profile of the runaway density.

Integrated modelling of electron runaway requires computationally expensive kinetic models that are self-consistently coupled to the evolution of the background plasma parameters. The computational expense can be reduced by using parameterized runaway generation rates rather than solving the full kinetic problem. However, currently available generation rates neglect several important effects; in particular, they are not valid in the presence of partially ionized impurities. In this work, we construct a multilayer neural network for the Dreicer runaway generation rate which is trained on data obtained from kinetic simulations performed for a wide range of plasma parameters and impurities. The neural network accurately reproduces the Dreicer runaway generation rate obtained by the kinetic solver. By implementing it in a fluid runaway-electron modelling tool, we show that the improved generation rates lead to significant differences in the self-consistent runaway dynamics as compared to the results using the previously available formulas for the runaway generation rate.

In the 2015 review paper ‘Petawatt Class Lasers Worldwide’ a comprehensive overview of the current status of high-power facilities of ${>}200~\text{TW}$ was presented. This was largely based on facility specifications, with some description of their uses, for instance in fundamental ultra-high-intensity interactions, secondary source generation, and inertial confinement fusion (ICF). With the 2018 Nobel Prize in Physics being awarded to Professors Donna Strickland and Gerard Mourou for the development of the technique of chirped pulse amplification (CPA), which made these lasers possible, we celebrate by providing a comprehensive update of the current status of ultra-high-power lasers and demonstrate how the technology has developed. We are now in the era of multi-petawatt facilities coming online, with 100 PW lasers being proposed and even under construction. In addition to this there is a pull towards development of industrial and multi-disciplinary applications, which demands much higher repetition rates, delivering high-average powers with higher efficiencies and the use of alternative wavelengths: mid-IR facilities. So apart from a comprehensive update of the current global status, we want to look at what technologies are to be deployed to get to these new regimes, and some of the critical issues facing their development.

Accurate modelling of the interaction between fast electrons and partially ionized atoms is important for evaluating tokamak disruption mitigation schemes based on material injection. This requires accounting for the effect of screening of the impurity nuclei by the cloud of bound electrons. In this paper, we generalize the Fokker–Planck operator in a fully ionized plasma by accounting for the effect of screening. We detail the derivation of this generalized operator, and calculate the effective ion length scales, needed in the components of the collision operator, for a number of ion species commonly appearing in fusion experiments. We show that for high electric fields, the secondary runaway growth rate can be substantially larger than in a fully ionized plasma with the same effective charge, although the growth rate is significantly reduced at near-critical electric fields. Furthermore, by comparison with the Boltzmann collision operator, we show that the Fokker–Planck formalism is accurate even for large impurity content.

Sufficiently strong electric fields in plasmas can accelerate charged particles to relativistic energies. In this paper we describe the dynamics of positrons accelerated in such electric fields, and calculate the fraction of created positrons that become runaway accelerated, along with the amount of radiation that they emit. We derive an analytical formula that shows the relative importance of the different positron production processes, and show that, above a certain threshold electric field, the pair production by photons is lower than that by collisions. We furthermore present analytical and numerical solutions to the positron kinetic equation; these are applied to calculate the fraction of positrons that become accelerated or thermalized, which enters into rate equations that describe the evolution of the density of the slow and fast positron populations. Finally, to indicate operational parameters required for positron detection during runaway in tokamak discharges, we give expressions for the parameter dependencies of detected annihilation radiation compared to bremsstrahlung detected at an angle perpendicular to the direction of runaway acceleration. Using the full leading-order pair-production cross-section, we demonstrate that previous related work has overestimated the collisional pair production by at least a factor of four.

This work is part of the interlaboratory collaboration to study the stability of organic solar cells containing PCDTBT polymer as a donor material. The varieties of the OPV devices with different device architectures, electrode materials, encapsulation, and device dimensions were prepared by seven research laboratories. Sets of identical devices were aged according to four different protocols: shelf lifetime, laboratory weathering under simulated illumination at ambient temperature, laboratory weathering under simulated illumination, and elevated temperature (65 °C) and daylight outdoor weathering under sunlight. The results generated in this study allow us to outline several general conclusions related to PCDTBT-based bulk heterojunction (BHJ) solar cells. The results herein reported can be considered as practical guidance for the realization of stabilization approaches in BHJ solar cells containing PCDTBT.

The order Chiroptera is considered the second largest group of mammals in the world, hosting important zoonotic virus and bacteria. Bartonella and hemotropic mycoplasmas are bacteria that parasite different mammals’ species, including humans, causing different clinical manifestations. The present work aimed investigating the occurrence and assessing the phylogenetic positioning of Bartonella spp. and Mycoplasma spp. in neotropical bats sampled from Brazil. Between December 2015 and April 2016, 325 blood and/or tissues samples were collected from 162 bats comprising 19 different species sampled in five states of Brazil. Out of 322 bat samples collected, while 17 (5·28%) were positive to quantitative PCR for Bartonella spp. based on nuoG gene, 45 samples (13·97%) were positive to cPCR assays for hemoplasmas based on 16S rRNA gene. While seven sequences were obtained for Bartonella (nuoG) (n = 3), gltA (n = 2), rpoB (n = 1), ftsZ (n = 1), five 16S rRNA sequences were obtained for hemoplasmas. In the phylogenetic analysis, the Bartonella sequences clustered with Bartonella genotypes detected in bats sampled in Latin America countries. All five hemoplasmas sequences clustered together as a monophyletic group by Maximum Likelihood and Bayesian Inference analyses. The present work showed the first evidence of circulation of Bartonella spp. and hemoplasmas among bats in Brazil.

Millisecond pulsars (MSPs) are a class of radio pulsars with extremely stable rotation. Their excellent timing stability can be used to study a wide variety of astrophysical phenomena. In particular, a large sample of these pulsars can be used to detect low-frequency gravitational waves. We have developed a precision pulsar timing backend for the NASA Deep Space Network (DSN), which will allow the use of short gaps in tracking schedules to time pulses from an ensemble of MSPs. The DSN operates clusters of large dish antennas (up to 70-m in diameter), located roughly equidistant around the Earth, for communication and tracking of deep-space spacecraft. The backend system will be capable of removing entirely the dispersive effects of propagation of radio waves through the interstellar medium in real-time. We will describe our development work, initial results, and prospects for future observations over the next few years.