Bromine-rich argyrodites compositions: Enhancing lithium-ion conductivity for improved solid-state battery performance

International audienceHalide-enriched lithium argyrodite superionic conductors are considered as promising candidates for all-solid-state batteries due to their soft structure and high ionic conductivity. Challenges remain, including chemical instability and incompatibility with anode materials, and in addition a deeper understanding of the fundamental aspects of ionic transport and performance is required. In this study, we investigated two argyrodite mixed-halide series of compositions, Li6−xPS5−xBrClx and Li5.5PS4.5Br1.5−xClx. By employing a range of techniques including X-ray diffraction (XRD), neutron diffraction, nuclear magnetic resonance (NMR) spectroscopy, electrochemical impedance spectroscopy and machine learning based molecular dynamics, we found that increasing the halide substitution enhances ionic conductivity. Notably, the Li5.4PS4.4BrCl0.6 composition achieves an ionic conductivity of 10 mS/cm, demonstrates superior air stability compared to conventional lithium argyrodites and allows for the fabrication of well-performing all solid-state batteries. Our results reveal that in lithium-poor compositions the lithium environments in the 4a and 4d cages become more alike, facilitating fast long-range lithium-ion transport. This work paves the way for the development of air-stable, high-conductivity sulfide electrolytes, advancing the practical implementation of solid-state batteries

Mechanism of the Effect of Micro-Water on the Thermal Decomposition Characteristics of C 4 F 7 N/CO 2 /O 2 Gas Mixture

Version acceptéeInternational audienceThe C4F7N/CO2/O2 ternary gas mixture, with its excellent environmental and insulating properties, has emerged as one of the most promising alternatives to SF6 and has seen initial applications in global power systems. Currently, there is limited research on the stability of C4F7N/CO2/O2 in equipment under long-term operation with micro-water content. This study uses reactive molecular dynamics simulations, using ReaxFF forcefield, for investigating the effect of water (up to 2%) on the thermal decomposition characteristics of C4F7N/CO2/O2 at the microscopic level. Additionally, thermal decomposition experiments of C4F7N/CO2/O2 under different micro-water concentrations were conducted to analyze the relationship between decomposition products and micro-water content. When the micro-water concentration is below 1.6%, H2O promotes the generation of O radicals, increasing the decomposition of C4F7N. However, as the H2O concentration increases further, the large amount of generated OH radicals consume O radicals, inhibiting the main decomposition reactions of C4F7N. Experimental results show that the main thermal decomposition products of the gas mixture are CF4, C3F8, C3F6, C2F6, and CHF3. The findings of this study provide theoretical support and technical foundation for enhancing the reliability of C4F7N/CO2/O2 insulation equipment in long-term engineering applications.</div

Identification, occurrence and prevention of aspartimide-related byproducts in chemical protein synthesis

International audienceFormation of a five-membered ring aspartimide through the attack of a backbone amide to the side chain of aspartate and asparagine residues is a long-known side-reaction in solid phase peptide synthesis, and is also associated with in vivo protein ageing and instability of purified proteins. Conversely, its possible occurrence during chemical ligation-based protein synthesis, in particular when using the gold-standard reaction NCL (native chemical ligation), is dubious. We herein report a systematic study which demonstrates that the prevalence of this side-reaction may have been overlooked, due to the difficulty to identify it through standard HPLC analytical methods, but also the in situ conversion of aspartimide into other byproducts, having the same molecular mass as the parent aspartate residue. We show that the formation of aspartimide and derived byproducts can be limited by adopting "good NCL practices", which involve restricting the ligation temperature and reaction times, as well as replacing the commonly used phosphate buffer with HEPES. However, the efficiency of such precautions is expected to vary considerably depending on the sequence of the target protein, and the amount of byproducts is expected to grow with the length of the target protein, as a result of the number of NCL reactions and potential aspartimide hotspots. To overcome such limitations, we developed a novel straightforward and potentially generally applicable methodology based on the temporary protection of the backbone nitrogen by a 2-(4-aminobutanoyloxy)-4-methoxybenzyl (GABA-Hmb) group. This strategy was validated by the byproduct-free synthesis of SUMO-2 and a SUMOylated peptide mimic.Scheme 1 Native Chemical Ligation (NCL).</div

Potential impacts of ammonia/hydrogen on engine lubricants: A review

As intrinsically carbon-free molecules, ammonia and hydrogen are considered as fuels for internal combustion engines, mainly for long-distance or off-road applications. These alternative fuels have different combustion characteristics, reactivity, and exhaust gas compositions compared to conventional fuels, raising questions about the suitability of lubricants in engines operating with them. The impact of ammonia, hydrogen, and their blends on lubricants in internal combustion engines is a relatively new topic, with few reference studies available. However, degradation processes of lubricants have been studied in the context of hydrocarbon fuels, and in compressors using ammonia as a refrigerant, for example. This work presents a review of the literature on engine oil degradation phenomena in relation to ammonia and hydrogen combustion characteristics. In particular, it highlights the current state of knowledge regarding compatibility with unburnt gases, elevated nitrogen oxide levels, and water. Additionally, it summarizes the latest insights into the contribution of lubricants to pollutant emissions

Suppression of long-range weberite-type ordering in high temperatureGd Nb O (x=0 and 0.25) elaborated by direct crystallisation from melt

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Bioluminescence Resonance Energy Transfer: A Powerful Technique in Neuropharmacology for Discovering New Ligands of G Protein-Coupled Receptors

MasterThe Bioluminescence Resonance Energy Transfer (BRET) is a proximity-based assay used to study protein-protein interactions in living cells. The principle behind BRET involves resonance transfer of energy between bioluminescent enzymes and a fluorescent acceptors, resulting in measurable signals that indicate specific molecular interactions. BRET has been widely adopted in drug discovery as a high-throughput screening method to investigate the behavior of signaling proteins, such as G protein-coupled receptors (GPCRs). Due to its ability to operate under physiological conditions, BRET is a highly sensitive and well-suited tool for real-time, dynamic studies regarding diverse signaling pathways, their downstream messengers, receptor internalization and more

RoBraTS : Segmentation automatique de tumeur cérébrale chez le rongeur àpartir d’IRM multi-paramétrique

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Anticipation training for expert tennis players when facing a specific player

International audienceIntroduction: In fast ball sports, such as tennis, when spatiotemporal constraintsare high, players have to anticipate the opponent action. Not much is knownabout how players acquire and improve this ability. The aim of this study wasto use an implicit training protocol (no information was given to participants)based on the knowledge of one particular opponent to analyse how expertscould improve their anticipation ability.Method: Professional tennis players were tested and trained in a protocolconsisted of watching videos with temporal occlusions before the opponentstroke and guessing the direction of the stroke. Three groups took part in theexperiment: one with a specific training with the same opponent as in pre- andpost-tests; one with a various training with players other than the one used inpre- and post-tests (to control that the improvement is link with the knowledgeof one specific opponent and not to an adaptation to the task) and one controlgroup without practice.Results: Only the group trained with the same opponent increased itsresponse accuracy.Discussion: Our results suggest that anticipation can be improved in professionaltennis players with a very specific training providing information aboutthe opponent

Strict inequality between the time constants of first-passage percolation and directed first-passage percolation

In the models of first-passage percolation and directed first-passage percolation on Z^d, we consider a family of i.i.d random variables indexed by the set of edges of the graph, called passage times. For every vertex x ∈ Z^d with nonnegative coordinates, we denote by t(0, x) the shortest passage time to go from 0 to x and by \vec{t}(0, x) the shortest passage time to go from 0 to x following a directed path. Under some assumptions, it is known that for every x ∈ R^d with nonnegative coordinates, t(0, ⌊nx⌋)/n converges to a constant µ(x) and that \vec{t}(0, ⌊nx⌋)/n converges to a constant \vec{µ}(x). With these definitions, we immediately get that µ(x) ≤ \vec{µ}(x). In this paper, we get the strict inequality µ(x) &lt; \vec{µ}(x) as a consequence of a new exponential bound for the comparison of t(0,x) and \vec{t}(0,x) when ||x|| goes to \infty. This exponential bound is itself based on a lower bound on the number of edges of geodesics in first-passage percolation (where geodesics are paths with minimal passage time)

LUMIA: linear probing for unimodal and multiModal membership inference attacks leveraging internal LLM states

International audienceLarge Language Models (LLMs) are increasingly used in a variety of applications, but concerns around membership inference have grown in parallel. Previous efforts focus on black-to-grey-box models, thus neglecting the potential benefit from internal LLM information. To address this, we propose the use of Linear Probes (LPs) as a method to detect Membership Inference Attacks (MIAs) by examining internal activations of LLMs. Our approach, dubbed LUMIA, applies LPs layer-by-layer to get fine-grained data on the model inner workings. We test this method across several model architectures, sizes and datasets, including unimodal and multimodal tasks. In unimodal MIA, LUMIA achieves an average gain of 15.71 % in Area Under the Curve (AUC) over previous techniques. Remarkably, LUMIA reaches AUC&gt;60% in 65.33% of cases -- an increment of 46.80% against the state of the art. Furthermore, our approach reveals key insights, such as the model layers where MIAs are most detectable. In multimodal models, LPs indicate that visual inputs can significantly contribute to detect MIAs -- AUC&gt;60% is reached in 85.90% of experiments