Soil core study indicates limited CO2 removal by enhanced weathering in dry croplands in the UK

The application of crushed silicate minerals to agricultural soils has been suggested as a route to enhance weathering rates and increase CO2 drawdown. Laboratory studies have attempted to evaluate the potential of enhanced weathering as a CO2 removal technique but do not simulate the geochemical complexity of soil environments, and studies in the field are limited in the nature of data they can collect. To overcome these limitations, this study uses an experimental set-up which fully encapsulates field conditions in a controlled setting using soil cores removed from UK cropland and treated with crushed basalt. Cores were exposed to natural weather conditions throughout a 14-month time series, and soil solution was sampled in 10–20 cm intervals in the core to provide insight into the fate of dissolution products with soil depth. This study assessed the rate and chemistry of basalt dissolution 8 months after addition at a high application rate (100t basalt ha−1) using direct measurements from a UK soil. Assuming conclusions drawn from this study are representative of field-scale enhanced weathering, findings indicate that a set application of basalt to lime-rich, unirrigated UK soils releases alkalinity at a rate of 310 ± 30 eq ha−1 yr−1 and could remove 10.2 ± 0.8 kgCO2 ha−1 yr−1. Accumulation of undissolved basalt may also lead to large and irreversible changes to soil compositions following repeated application. When considering variation in hydrology around the UK, we assess the drawdown potential of application of basalt to all UK arable land as 1.3 ± 0.1 MtCO2 yr−1 which is equivalent to 3% of current UK agricultural CO2 emissions. This is 5- to 25- fold slower than previous modelled assessments, likely due to complexities of soil systems and to water limitation on alkalinity release. Further research is needed to fully assess controls on the potential of enhanced weathering in the real-world environment, across a range of hydrological and soil environments, before the approach is substantively scaled-up for CO2 removal

Lithium Intercalation into the Excitonic Insulator Candidate Ta2NiSe5

A new reduced phase derived from the excitonic insulator candidate Ta2NiSe5 has been synthesized via the intercalation of lithium. LiTa2NiSe5 crystallizes in the orthorhombic space group Pmnb (no. 62) with lattice parameters a = 3.50247(3) Å, b = 13.4053(4) Å, c = 15.7396(2) Å, and Z = 4, with an increase of the unit cell volume by 5.44(1)% compared with Ta2NiSe5. Significant rearrangement of the Ta-Ni-Se layers is observed, in particular a very significant relative displacement of the layers compared to the parent phase, similar to that which occurs under hydrostatic pressure. Neutron powder diffraction experiments and computational analysis confirm that Li occupies a distorted triangular prismatic site formed by Se atoms of adjacent Ta2NiSe5 layers with an average Li-Se bond length of 2.724(2) Å. Li-NMR experiments show a single Li environment at ambient temperature. Intercalation suppresses the distortion to monoclinic symmetry that occurs in Ta2NiSe5 at 328 K and that is believed to be driven by the formation of an excitonic insulating state. Magnetometry data show that the reduced phase has a smaller net diamagnetic susceptibility than Ta2NiSe5 due to the enhancement of the temperature-independent Pauli paramagnetism caused by the increased density of states at the Fermi level evident also from the calculations, consistent with the injection of electrons during intercalation and formation of a metallic phase

Cell-permeable lanthanide-platinum(iv) anti-cancer prodrugs

Platinum compounds are a vital part of our anti-cancer arsenal, and determining the location and speciation of platinum compounds is crucial. We have synthesised a lanthanide complex bearing a salicylic group (Ln = Gd, Eu) which demonstrates excellent cellular accumulation and minimal cytotoxicity. Derivatisation enabled access to bimetallic lanthanide–platinum(II) and lanthanide–platinum(IV) complexes. Luminescence from the europium–platinum(IV) system was quenched, and reduction to platinum(II) with ascorbic acid resulted in a “switch-on” luminescence enhancement. We used diffusion-based 1H NMR spectroscopic methods to quantify cellular accumulation. The gadolinium–platinum(II) and gadolinium–platinum(IV) complexes demonstrated appreciable cytotoxicity. A longer delay following incubation before cytotoxicity was observed for the gadolinium–platinum(IV) compared to the gadolinium–platinum(II) complex. Functionalisation with octanoate ligands resulted in enhanced cellular accumulation and an even greater latency in cytotoxicity

Anion redox as a means to ferive layered manganese oxychalcogenides with exotic intergrowth structures

Topochemistry enables step-by-step conversions of solid-state materials often leading to metastable structures that retain initial structural motifs. Recent advances in this field revealed many examples where relatively bulky anionic constituents were actively involved in redox reactions during (de)intercalation processes. Such reactions are often accompanied by anion-anion bond formation, which heralds possibilities to design novel structure types disparate from known precursors, in a controlled manner. Here we present the multistep conversion of layered oxychalcogenides Sr2MnO2Cu1.5Ch2 (Ch = S, Se) into Cu-deintercalated phases where antifluorite type [Cu1.5Ch2]2.5- slabs collapsed into two-dimensional arrays of chalcogen dimers. The collapse of the chalcogenide layers on deintercalation led to various stacking types of Sr2MnO2Ch2 slabs, which formed polychalcogenide structures unattainable by conventional high-temperature syntheses. Anion-redox topochemistry is demonstrated to be of interest not only for electrochemical applications but also as a means to design complex layered architectures

H-ATLAS: a candidate high redshift cluster/protocluster of star-forming galaxies

We investigate the region around the Planck-detected z=3.26 gravitationally lensed galaxy HATLAS J114637.9-001132 (hereinafter HATLAS12-00) using both archival Herschel data from the H-ATLAS survey and using submm data obtained with both LABOCA and SCUBA2. The lensed source is found to be surrounded by a strong overdensity of both Herschel-SPIRE sources and submm sources. We detect 17 bright (S870 >~7 mJy) sources at >4sigma closer than 5 arcmin to the lensed object at 850/870 microns. Ten of these sources have good cross-identifications with objects detected by Herschel-SPIRE which have redder colours than other sources in the field, with 350 micron flux > 250 micron flux, suggesting that they lie at high redshift. Submillimeter Array (SMA) observations localise one of these companions to ~1 arcsecond, allowing unambiguous cross identification with a 3.6 and 4.5 micron Spitzer source. The optical/near-IR spectral energy distribution (SED) of this source is measured by further observations and found to be consistent with z>2, but incompatible with lower redshifts. We conclude that this system may be a galaxy cluster/protocluster or larger scale structure that contains a number of galaxies undergoing starbursts at the same time

Towards the prediction of molecular parameters from astronomical emission lines using Neural Networks

Molecular astronomy is a field that is blooming in the era of large observatories such as the Atacama Large Millimeter/Submillimeter Array (ALMA). With modern, sensitive, and high spectral resolution radio telescopes like ALMA and the Square Kilometer Array, the size of the data cubes is rapidly escalating, generating a need for powerful automatic analysis tools. This work introduces MolPred, a pilot study to perform predictions of molecular parameters such as excitation temperature (Tex) and column density (log(N)) from input spectra by the use of neural networks. We used as test cases the spectra of CO, HCO+, SiO and CH3CN between 80 and 400 GHz. Training spectra were generated with MADCUBA, a state-of-the-art spectral analysis tool. Our algorithm was designed to allow the generation of predictions for multiple molecules in parallel. Using neural networks, we can predict the column density and excitation temperature of these molecules with a mean absolute error of 8.5% for CO, 4.1% for HCO+, 1.5% for SiO and 1.6% for CH3CN. The prediction accuracy depends on the noise level, line saturation, and number of transitions. We performed predictions upon real ALMA data. The values predicted by our neural network for this real data differ by 13% from the MADCUBA values on average. Current limitations of our tool include not considering linewidth, source size, multiple velocity components, and line blending

Towards the prediction of molecular parameters from astronomical emission lines using Neural Networks

Molecular astronomy is a field that is blooming in the era of large observatories such as the Atacama Large Millimeter/Submillimeter Array (ALMA). With modern, sensitive, and high spectral resolution radio telescopes like ALMA and the Square Kilometer Array, the size of the data cubes is rapidly escalating, generating a need for powerful automatic analysis tools. This work introduces MolPred, a pilot study to perform predictions of molecular parameters such as excitation temperature (T) and column density (log(N)) from input spectra by the use of neural networks. We used as test cases the spectra of CO, HCO, SiO and CHCN between 80 and 400 GHz. Training spectra were generated with MADCUBA, a state-of-the-art spectral analysis tool. Our algorithm was designed to allow the generation of predictions for multiple molecules in parallel. Using neural networks, we can predict the column density and excitation temperature of these molecules with a mean absolute error of 8.5% for CO, 4.1% for HCO, 1.5% for SiO and 1.6% for CHCN. The prediction accuracy depends on the noise level, line saturation, and number of transitions. We performed predictions upon real ALMA data. The values predicted by our neural network for this real data differ by 13% from the MADCUBA values on average. Current limitations of our tool include not considering linewidth, source size, multiple velocity components, and line blending.A.B. wishes to thank Dr. Diego Mardones for his contribution to the early stages of this work. Also, to acknowledge support from the Federico Santa María Technical University General Directorate for Research and Postgraduate Studies (DGIP). JH and SV are funded by the European Research Council (ERC) Advanced Grant MOPPEX 833460. V.M.R. acknowledges support from the Comunidad de Madrid through the Atracción de Talento Investigador Modalidad 1 (Doctores con experiencia) Grant (COOL: Cosmic Origins Of Life; 2019-T1/TIC-15379; PI: V.M. Rivilla)

The distribution and origin of C₂H in NGC 253 from ALCHEMI

Context. Observations of chemical species can provide insights into the physical conditions of the emitting gas however it is important to understand how their abundances and excitation vary within different heating environments. C2H is a molecule typically found in PDR regions of our own Galaxy but there is evidence to suggest it also traces other regions undergoing energetic processing in extragalactic environments. / Aims. As part of the ALCHEMI ALMA large program, we map the emission of C2H in the central molecular zone of the nearby starburst galaxy NGC 253 at 1.6″ (28 pc) resolution and characterize it to understand its chemical origins. / Methods. We used spectral modeling of the N = 1−0 through N = 4−3 rotational transitions of C2H to derive the C2H column densities towards the dense clouds in NGC 253. We then use chemical modeling, including photodissociation region (PDR), dense cloud, and shock models to investigate the chemical processes and physical conditions that are producing the molecular emission. / Results. We find high C2H column densities of ∼1015 cm−2 detected towards the dense regions of NGC 253. We further find that these column densities cannot be reproduced if it is assumed that the emission arises from the PDR regions at the edge of the clouds. Instead, we find that the C2H abundance remains high even in the high visual extinction interior of these clouds and that this is most likely caused by a high cosmic-ray ionization rate

Reconstructing the shock history in the CMZ of NGC 253 with ALCHEMI

HNCO and SiO are well known shock tracers and have been observed in nearby galaxies, including the nearby (D=3.5 Mpc) starburst galaxy NGC 253. The simultaneous detection of these two species in regions where the star formation rate is high may be used to study the shock history of the gas. We perform a multi-line molecular study using these two shock tracers (SiO and HNCO) with the aim of characterizing the gas properties. We also explore the possibility of reconstructing the shock history in NGC 253's Central Molecular Zone (CMZ). Six SiO transitions and eleven HNCO transitions were imaged at high resolution $1''.6$ (28 pc) with the Atacama Large Millimeter/submillimeter Array (ALMA) as part of the ALCHEMI Large Programme. Both non-LTE radiative transfer analysis and chemical modelling were performed in order to characterize the gas properties, and to investigate the chemical origin of the emission. The non-LTE radiative transfer analysis coupled with Bayesian inference shows clear evidence that the gas traced by SiO has different densities and temperatures than that traced by HNCO, with an indication that shocks are needed to produce both species. Chemical modelling further confirms such a scenario and suggests that fast and slow shocks are responsible for SiO and HNCO production, respectively, in most GMCs. We are also able to infer the physical characteristics of the shocks traced by SiO and HNCO for each GMC. Radiative transfer and chemical analysis of the SiO and HNCO in the CMZ of NGC 253 reveal a complex picture whereby most of the GMCs are subjected to shocks. We speculate on the possible shock scenarios responsible for the observed emission and provide potential history and timescales for each shock scenario. Higher spatial resolution observations of these two species are required in order to quantitatively differentiate between scenarios