Methanethiol-dependent dimethylsulfide production in soil environments

Dimethylsulfide (DMS) is an environmentally important trace gas with roles in sulfur cycling, signalling to higher organisms and in atmospheric chemistry. DMS is believed to be predominantly produced in marine environments via microbial degradation of the osmolyte dimethylsulfoniopropionate (DMSP). However, significant amounts of DMS are also generated from terrestrial environments, for example, peat bogs can emit ~6 μmol DMS m−2 per day, likely via the methylation of methanethiol (MeSH). A methyltransferase enzyme termed ‘MddA’, which catalyses the methylation of MeSH, generating DMS, in a wide range of bacteria and some cyanobacteria, may mediate this process, as the mddA gene is abundant in terrestrial metagenomes. This is the first study investigating the functionality of MeSH-dependent DMS production (Mdd) in a wide range of aerobic environments. All soils and marine sediment samples tested produced DMS when incubated with MeSH. Cultivation-dependent and cultivation-independent methods were used to assess microbial community changes in response to MeSH addition in a grassland soil where 35.9% of the bacteria were predicted to contain mddA. Bacteria of the genus Methylotenera were enriched in the presence of MeSH. Furthermore, many novel Mdd+ bacterial strains were isolated. Despite the abundance of mddA in the grassland soil, the Mdd pathway may not be a significant source of DMS in this environment as MeSH addition was required to detect DMS at only very low conversion rates

DddY, a periplasmic dimethylsulfoniopropionate lyase found in taxonomically diverse species of Proteobacteria

The abundant compatible solute dimethylsulfoniopropionate (DMSP) is made by many marine algae. Different marine bacteria catabolise DMSP by various mechanisms, some of which liberate the environmentally important gas dimethyl sulfide (DMS). We describe an enzyme, DddY, which cleaves DMSP into DMS plus acrylate and is located in the bacterial periplasm, unlike other DMSP lyases that catalyse this reaction. There are dddY-like genes in strains of Alcaligenes, Arcobacter and Shewanella, in the β-, ɛ- and γ-proteobacteria, respectively. In Alcaligenes, dddY is in a cluster of ddd and acu genes that resemble, but also have significant differences to, those in other bacteria that catabolise both DMSP and acrylate. Although production of DMS and transcription of Alcaligenes dddY are both apparently inducible by pre-growth of cells with DMSP, this substrate must be catabolised to form acrylate, the bona fide coinducer

First principles and integrated modelling achievements towards trustful fusion power predictions for JET and ITER

Predictability of burning plasmas is a key issue for designing and building credible future fusion devices. In this context, an important effort of physics understanding and guidance is being carried out in parallel to JET experimental campaigns in H and D by performing analyses and modelling towards an improvement of the understanding of DT physics for the optimization of the JET-DT neutron yield and fusion born alpha particle physics. Extrapolations to JET-DT from recent experiments using the maximum power available have been performed including some of the most sophisticated codes and a broad selection of models. There is a general agreement that 11-15 MW of fusion power can be expected in DT for the hybrid and baseline scenarios. On the other hand, in high beta, torque and fast ion fraction conditions, isotope effects could be favourable leading to higher fusion yield. It is shown that alpha particles related physics, such as TAE destabilization or fusion power electron heating, could be studied in ITER relevant JET-DT plasmas

Role of fast ion pressure in the isotope effect in JET L-mode plasmas

This paper presents results of JET ITER-like wall L-mode experiments in hydrogen and deuterium (D) plasmas, dedicated to the study of the isotope dependence of ion heat transport by determination of the ion critical gradient and stiffness by varying the ion cyclotron resonance heating power deposition. When no strong role of fast ions in the plasma core is expected, the main difference between the two isotope plasmas is determined by the plasma edge and the core behavior is consistent with a gyro-Bohm scaling. When the heating power (and the fast ion pressure) is increased, in addition to the difference in the edge region, also the plasma core shows substantial changes. The stabilization of ion heat transport by fast ions, clearly visible in D plasmas, appears to be weaker in H plasmas, resulting in a higher ion heat flux in H with apparent anti-gyro-Bohm mass scaling. The difference is found to be caused by the different fast ion pressure between H and D plasmas, related to the heating power settings and to the different fast ion slowing down time, and is completely accounted for in non-linear gyrokinetic simulations. The application of the TGLF quasi-linear model to this set of data is also discussed

Deep neural networks for plasma tomography with applications to JET and COMPASS

Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays

Ion cyclotron resonance heating scenarios for DEMO

The present paper offers an overview of the potential of ion cyclotron resonance heating (ICRH) or radio frequency heating for the DEMO machine. It is found that various suitable heating schemes are available. Similar to ITER and in view of the limited bandwidth of about 10 MHz that can be achieved to ensure optimal functioning of the launcher, it is proposed to make core second harmonic tritium heating the key ion heating scheme, assisted by fundamental cyclotron heating He-3 in the early phase of the discharge; for the present design of DEMO-with a static magnetic field strength of B-o = 5.855 T-that places the T and 3He layers in the core for f = 60 MHz and suggests centering the bandwidth around that main operating frequency. In line with earlier studies for hot, dense plasmas in large-size magnetic confinement machines, it is shown that good single pass absorption is achieved but that the size as well as the operating density and temperature of the machine cause the electrons to absorb a non-negligible fraction of the power away from the core when core ion heating is aimed at. Current drive and alternative heating options are briefly discussed and a dedicated computation is done for the traveling wave antenna, proposed for DEMO in view of its compatibility with substantial antenna-plasma distances. The various tasks that ICRH can fulfill are briefly listed. Finally, the impact of transport and the sensitivity of the obtained results to changes in the machine parameters is commented on