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Unprecedented homoleptic octathioether macrocyclic coordination to Na(+) in [Na([24]aneS8)](+) has been achieved by using Na[B{3,5-(CF3)2-C6H3}4] as a source of "naked" Na(+) ions and confirmed crystallographically, with d(Na-S) = 2.9561(15)-3.0524(15) Å. Density functional theory calculations show that there is electron transfer from the S 3p and C 2p valence orbitals of the ligand to the 3s and 3p orbitals of the Na(+) ion upon complexation.

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are increasingly used to reconstruct mean annual air temperature (MAAT) during the early Paleogene. However, the application of this proxy in coal deposits is limited and brGDGTs have only been detected in immature coals (i.e. lignites). Using samples recovered from Schöningen, Germany (∼48°N palaeolatitude), we provide the first detailed study into the occurrence and distribution of brGDGTs through a sequence of early Eocene lignites and associated interbeds. BrGDGTs are abundant and present in every sample. In comparison to modern studies, changes in vegetation type do not appear to significantly impact brGDGT distributions; however, there are subtle differences between lignites – representing peat-forming environments – and siliciclastic nearshore marine interbed depositional environments. Using the most recent brGDGT temperature calibration (MATmr) developed for soils, we generate the first continental temperature record from central-western continental Europe through the early Eocene. Lignite-derived MAAT estimates range from 23 to 26 °C while those derived from the nearshore marine interbeds exceed 20 °C. These estimates are consistent with other mid-latitude environments and model simulations, indicating enhanced mid-latitude, early Eocene warmth. In the basal part of the section studied, warming is recorded in both the lignites (∼2 °C) and nearshore marine interbeds (∼2–3 °C). This culminates in a long-term temperature maximum, likely including the Early Eocene Climatic Optimum (EECO). Although this long-term warming trend is relatively well established in the marine realm, it has rarely been shown in terrestrial settings. Using a suite of model simulations we show that the magnitude of warming at Schöningen is broadly consistent with a doubling of CO2, in agreement with late Paleocene and early Eocene pCO2 estimates.

Current advances in emerging memory technologies enable novel and unconventional computing architectures for high-performance and low-power electronic systems, capable of carrying out massively parallel operations at the edge. One emerging technology, ReRAM, also known to belong in the family of memristors (memory resistors), is gathering attention due to its attractive features for logic and in-memory computing; benefits which follow from its technological attributes, such as nanoscale dimensions, low power operation and multi-state programming. At the same time, design with CMOS is quickly reaching its physical and functional limitations, and further research towards novel logic families, such as Threshold Logic Gates (TLGs) is scoped. TLGs constitute a logic family known for its high-speed and low power consumption, yet rely on conventional transistor technology. Introducing memristors enables a more affordable reconfiguration capability of TLGs. Through this work, we are introducing a physical implementation of a memristor-based current-mode TLG (MCMTLG) circuit and validate its design and operation through multiple experimental setups. We demonstrate 2-input and 3-input MCMTLG configurations and showcase their reconfiguration capability. This is achieved by varying memristive weights arbitrarily for shaping the classification decision boundary, thus showing promise as an alternative hardware-friendly implementation of Artificial Neural Networks (ANNs). Through the employment of real memristor devices as the equivalent of synaptic weights in TLGs, we are realizing components that can be used towards an in-silico classifier.

Accurate prediction of alkane phase transitions involving solids is needed to prevent catastrophic pipeline blockages, improve lubrication formulations, smart insulation, and energy storage, as well as bring fundamental understanding to processes such as artificial morphogenesis. However, simulation of these transitions is challenging and therefore often omitted in force field development. Here, we perform a series of benchmarks on seven representative molecular dynamics models (TraPPE, PYS, CHARMM36, L-OPLS, COMPASS, Williams, and the newly optimized Williams 7B), comparing with experimental data for liquid properties, liquid-solid, and solid-solid phase transitions of two prototypical alkanes, n-pentadecane (C15) and n-hexadecane (C16). We find that existing models overestimate the melting points by up to 34 K, with PYS and Williams 7B yielding the most accurate results deviating only 2 and 3 K from the experiment. We specially design order parameters to identify crystal-rotator phase transitions in alkanes. United-atom models could only produce a rotator phase with complete rotational disorder, whereas all-atom models using a 12-6 Lennard-Jones potential show no rotator phase even when superheated above the melting point. In contrast, Williams (Buckingham potential) and COMPASS (9-6 Lennard-Jones) reproduce the crystal-to-rotator phase transition, with the optimized Williams 7B model having the most accurate crystal-rotator transition temperature of C15.

Detailed spectroscopic characterisation of the $$^4I_{9/2}\ \rightarrow ^4F_{3/2}$$ absorption cross section of Nd:YAG at temperatures ranging from room temperature to liquid nitrogen temperature is reported. Exploiting this in-band pumping scheme, a novel volume-Bragg-grating-locked diode-laser array (DLA) operating at 869 nm was developed to end-pump a cryogenically cooled Nd:YAG crystal. As a result, the first 60-W cryogenically-cooled Nd:YAG laser operating at 946 nm is demonstrated with a slope, and optical-to-optical, efficiency of $$52\%$$ .

Camera equipped Autonomous Underwater Vehicles (AUVs) are now routinely used in seafloor surveys. Obtaining effective representations from the images they collect can enable perception-aware robotic exploration such as information-gain-guided path planning and target-driven visual navigation. This letter develops a novel self-supervised representation learning method for seafloor images collected by AUVs. The method allows deep-learning convolutional autoencoders to leverage multiple sources of metadata to regularise their learning, prioritising features observed in images that can be correlated with patterns in their metadata. The impact of the proposed regularisation is examined on a dataset consisting of more than 30 k colour seafloor images gathered by an AUV off the coast of Tasmania. The metadata used to regularise learning in this dataset consists of the horizontal location and depth of the observed seafloor. The results show that including metadata in self-supervised representation learning can increase image classification accuracy by up to 15% and never degrades learning performance. We show how effective representation learning can be applied to achieve class balanced representative image identification for summarised understanding of imbalanced class distributions in an unsupervised way.

Pt and PtSn catalysts were studied for n-butanol electro-oxidation at various temperatures. PtSn showed a higher activity towards butanol electro-oxidation compared to Pt in acidic media. The onset potential for n-butanol oxidation on PtSn is similar to 520 mV lower than that found on Pt, and significantly lower activation energy was found for PtSn compared with that for Pt.

Abstract\ud Aims Rhizodeposits collected from hydroponic solutions with roots of maize and barley, and seed mucilage washed from chia, were added to soil to measure their impact on water retention and hysteresis in a sandy loam soil at a range of concentrations. We test the hypothesis that the effect of plant exudates and mucilages on hydraulic properties of soils depend on their physicochemical characteristics and origin.\ud Methods Surface tension and viscosity of the exudate solutions were measured using the Du Noüy ring method and a cone-plate rheometer, respectively. The contact angle of water on exudate treated soil was measured with the sessile drop method. Water retention and hysteresis were measured by equilibrating soil samples, treated with exudates and mucilages at 0.46 and 4.6 mg g−1 concentration, on dialysis tubing filled with polyethylene glycol (PEG) solution of known osmotic potential.\ud Results Surface tension decreased and viscosity increased with increasing concentration of the exudates and mucilage in solutions. Change in surface tension and viscosity was greatest for chia seed exudate and least for barley root exudate. Contact angle increased with increasing maize root and chia seed exudate concentration in soil, but not barley root. Chia seed mucilage and maize root rhizodeposits enhanced soil water retention and increased hysteresis index, whereas barley root rhizodeposits decreased soil water retention and the hysteresis effect. The impact of exudates and mucilages on soil water retention almost ceased when approaching the wilting point at −1500 kPa matric potential.\ud Conclusions Barley rhizodeposits behaved as surfactants, drying the rhizosphere at smaller suctions. Chia seed mucilage and maize root rhizodeposits behaved as hydrogels that hold more water in the rhizosphere, but with slower rewetting and greater hysteresis.

The stable carbon isotope composition of dissolved inorganic carbon (δ13CDIC) in seawater was measured in a batch process for 552 samples collected during two cruises in the northeastern Atlantic and Nordic Seas from June to August 2012. One cruise was part of the UK Ocean Acidification research programme, and the other was a repeat hydrographic transect of the Extended Ellett Line. In combination with measurements made of other variables on these and other cruises, these data can be used to constrain the anthropogenic component of dissolved inorganic carbon (DIC) in the interior ocean, and to help to determine the influence of biological carbon uptake on surface ocean carbonate chemistry. The measurements have been processed, quality-controlled and submitted to an in-preparation global compilation of seawater δ13CDIC data, and are available from the British Oceanographic Data Centre. The observed δ13CDIC values fall in a range from −0.58 to +2.37 ‰, relative to the Vienna Pee Dee Belemnite standard. The mean of the absolute differences between samples collected in duplicate in the same container type during both cruises and measured consecutively is 0.10 ‰, which corresponds to a 1σ uncertainty of 0.09 ‰, and which is within the range reported by other published studies of this kind. A crossover analysis was performed with nearby historical δ13CDIC data, indicating that any systematic offsets between our measurements and previously published results are negligible. Data doi:10.5285/09760a3a-c2b5-250b-e053-6c86abc037c0 (northeastern Atlantic), doi:10.5285/09511dd0-51db-0e21-e053-6c86abc09b95 (Nordic Seas).

ISOX-DUAL is a dual inhibitor of CBP/p300 (IC50 = 0.65 μM) and BRD4 (IC50 = 1.5 μM) bromodomains, and a useful chemical probe for epigenetic research. Aspects of the published synthetic route to this compound and its analogues are small-scale, poor-yielding or simply unamenable to scale-up without optimization. Herein we describe the development of a refined synthesis that circumvents the challenges of the original report, with notable improvements to several of the key synthetic transformations. Moreover, a general Suzuki Miyaura protocol for the late stage installation of alternative dimethyl-isoxazole acetyl-lysine (KAc) binding motifs is presented.