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Impact and Interaction of Additives on the Formation of Non Intentionally Added Substances (NIAS) and Polystyrene Rheology
No full textInternational audienceRecycling polystyrene on an industrial scale remains challenging. One of the key challenges lies in the formation of nonintentionally added substances (NIAS) arising from polymer manufacturing, polymer or additive degradation, and contaminants. This study aims at investigating the interactions between the polystyrene matrix and five common additives (antioxidants, UV stabilizer, brominated flame retardant, inorganic flame retardant). The main objective is to evaluate the impact of these interactions on NIAS formation and polymer rheological behavior. Our previously developed simple and efficient extraction was used to recover additives, and NIAS and was adapted for the low solubility additive decabromodiphenyl ether, to reach combined extraction efficiency (considering additives and their degradation products) between 81.3 and 100 wt %. Extracts were identified by 1H, 31P nuclear magnetic resonance (NMR), and LC–MS and quantified by LC–MS with limits of quantification (LOQ) as low as 0.21 ng/L. Extended investigation of the rheological behavior showed the impact of processing parameters and presence of additives. Chemical interaction between additives also highly impacted NIAS production, leading to either a decrease (up to 8.5-fold) or an increase (up to 3.5-fold) formation of NIAS. The present work contributes to the better understanding of interactions present during PS processing or recycling, highlighting the challenges linked to polystyrene mechanical recycling and the production of potentially toxic species
An Augmented Lagrangian Method on GPU for Security-Constrained AC Optimal Power Flow
No full textWe present a new algorithm for solving large-scale security-constrained optimal power flow in polar form (AC-SCOPF). The method builds on Nonlinearly Constrained augmented Lagrangian (NCL), an augmented Lagrangian method in which the subproblems are solved using an interior-point method. NCL has two key advantages for large-scale SC-OPF. First, NCL handles difficult problems such as infeasible ones or models with complementarity constraints. Second, the augmented Lagrangian term naturally regularizes the Newton linear systems within the interior-point method, enabling to solve the Newton systems with a pivoting-free factorization that can be efficiently parallelized on GPUs. We assess the performance of our implementation, called MadNCL, on large-scale corrective AC-SCOPFs, with complementarity constraints modeling the corrective actions. Numerical results show that MadNCL can solve AC-SCOPF with 500 buses and 256 contingencies fully on the GPU in less than 3 minutes, whereas Knitro takes more than 3 hours to find an equivalent solution
Efficacy of pembrolizumab and vorinostat combination in patients with recurrent and/or metastatic squamous cell carcinomas: a phase 2 basket trial
No full textInternational audienceAbstract Immune checkpoint inhibitors improve the treatment of many solid tumors and have shown encouraging results in advanced squamous cell carcinoma (SCC), yet only a minority of patients respond to immune checkpoint inhibitor monotherapy. We conducted the PEVOsq trial, an open-label, nonrandomized, multicenter, basket phase 2 trial to evaluate the combination of pembrolizumab and vorinostat in recurrent/metastatic SCC of various origins. The primary endpoint was the objective response rate (ORR) in each tumor cohort during treatment as per the investigators’ assessment. Secondary endpoints included safety and antitumor activity evaluation in terms of centrally confirmed ORR, progression-free survival, overall survival and duration of response. In the efficacy population ( n = 107), the ORR was met in cervical (39%), anal (31%) and vulvar/vaginal (19%) cancer cohorts, but not in head and neck SCC (19%) or penile (18%) cancer cohorts (overall ORR = 26%). Median progression-free survival was 4.0 months (95% confidence interval: 2.6–4.3), and median overall survival was 11.1 months (95% confidence interval: 9.2–17.4). In the safety population, 101 (91%) of 111 patients developed at least one treatment-related adverse event, with 39% and 5.4% of patients experiencing at least one grade 3 and grade 4 treatment-related adverse event, respectively. Vorinostat-related toxicity prompted a dose reduction/interruption in 66% of patients. Whole-exome sequencing analyses revealed several potential predictive biomarkers of response to treatment. Further studies in a larger number of patients are required to validate these findings. ClinicalTrials.gov identifier: NCT04357873
RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning
No full textInternational audienceAbstract RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. However, docking struggles to scale with large compound libraries and RNA targets. Machine learning offers a solution but remains underdeveloped for RNA due to limited data and practical evaluations. We introduce a data-driven VS pipeline tailored for RNA, utilizing coarse-grained 3D modeling, synthetic data augmentation, and RNA-specific self-supervision. Our model achieves a 10,000x speedup over docking while ranking active compounds in the top 2.8% on structurally distinct test sets. It is robust to binding site variations and successfully screens unseen RNA riboswitches in a 20,000-compound in-vitro microarray, with a mean enrichment factor of 2.93 at 1%. This marks the first experimentally validated success of structure-based deep learning for RNA VS
Modelling the effect of volcanic outgassing of sulphur on early Martian surface temperatures using a 3-D Global Climate Model
No full textInternational audienceAround the time of the transition from the Late Noachian to the Early Hesperian eras (~3.6 Gya), Mars was predicted to have been both volcanically active, and have sustained a climate warm enough to melt liquid water on its surface episodically despite a faint young sun. The effect of volcanic outgassing on the climate of early Mars and its ability to raise temperatures above the melting point of water has, however, been disputed, with a major uncertainty being the timescales over which the greenhouse effect of outgassed sulphur dioxide (SO 2 ) and hydrogen sulphide (H 2 S) can warm the atmosphere of Mars before they react to form H 2 SO 4 and S 8 aerosols which act to cool the surface of Mars. We have developed the first 3-D model of the Martian sulphur cycle from source to sink that includes outgassing of SO 2 , H 2 S and S 2 from the surface, the formation of H 2 SO 4 and S 8 through atmospheric chemistry, and the condensation and deposition of H 2 SO 4 and S 8 to the surface. We confirm the results of Tian et al.</div
Multi-Field Relativistic Continuous Matrix Product States
No full textInternational audienceRelativistic continuous matrix product states (RCMPS) are a powerful variational ansatz for quantum field theories of a single field. However, they inherit a property of their non-relativistic counterpart that makes them divergent for models with multiple fields, unless a regularity condition is satisfied. This has so far restricted the use of RCMPS to toy models with a single self-interacting field. We address this long standing problem by introducing a Riemannian optimization framework, that allows to minimize the energy density over the regular submanifold of multi-field RCMPS, and thus to retain purely variational results. We demonstrate its power on a model of two interacting scalar fields in dimensions. The method captures distinct symmetry-breaking phases, and the signature of a Berezinskii-Kosterlitz-Thouless (BKT) transition along an -symmetric parameter line. This makes RCMPS usable for a far larger class of problems than before
Caractérisation du comportement en rupture de la pile d'éponge de Zr en fonction de sa microstructure
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Influence of initial microstructure and niobium content on recrystallization and grain growth during hot forming of Zr-Nb alloy
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Efficient and accurate simulation of the Smith–Zener pinning mechanism during grain growth using a front-tracking numerical framework
No full textInternational audienceThis study proposes a new full-field approach for modeling grain boundary pinning by second phase particles in two-dimensional polycrystals. These particles are of great importance during thermomechanical treatments, as they produce deviations from the microstructural evolution occurring in the alloy in the absence of particles. This phenomenon, well-known as Smith–Zener pinning, is widely used by metallurgists to control the grain size during the metal forming process of many alloys. Predictive tools are then needed to accurately model this phenomenon. This article introduces a new methodology for the simulation of microstructural evolutions subjected to the presence of second phase particles. The methodology employs a Lagrangian 2D front-tracking methodology, while the particles are modeled using discretized circular shapes or pinning nodes. The evolution of the particles can be considered and modeled using a constant velocity of particle shrinking. This approach has the advantages of improving the limited description made of the phenomenon in vertex approaches, to be usable for a wide range of second-phase particle sizes and to improve calculation times compared to front-capturing type approaches
Mechanical modeling of GaN pillars coalescence for growth parameter optimization
No full textInternational audienceThis work focuses on optimizing various growth parameters related to a novel pendeo-epitaxy manufacturing approach aimed at producing high quality gallium nitride (GaN) for optoelectronic applications. The proposed approach consists of growing GaN pyramids on top of GaN/AlN/Si(111)/SiO 2 etched nanopillars on silicon-on-insulator substrates. It is expected that the excess of energy on the vertical edge of the GaN pyramids will allow the pillars to rotate so that the GaN on the top can align crystallographically. This should result in the formation of well-oriented GaN layer with low dislocation density. Finite element simulations using Abaqus software are performed to determine the optimal pillar parameters (e.g. radius ( r ), length, center-to-center distance between two pillars (pitch)) that would reduce the required rotation energy for it to be lower than the available energy, thus making the rotation of the pillars energetically feasible. The results showed that the pitch and the length of the pillars have the least effect on the required rotation energy while the latter is proportional to the square of the rotation angle. These numerical results allowed the development and validation of a simplified analytical model that accounts for the mechanics of the nanopillar in both tilt and twist case. The analytical formulation demonstrated that the most critical parameter is the radius as the required rotation energy is proportional to r 4 . Finally, this work allowed us to predict the optimal strategy for designing samples to enable the growth of high quality GaN layers suitable for micro light-emitting diodes