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15 results on '"Region Grand-Est"'

1. ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech

Author

Hirokazu Kameoka, Hsin-Te Hwang, Driss Matrouf, Markus Becker, Quan Wang, Sahidullah, Ye Jia, Yu Zhang, Lauri Juvela, Hsin-Min Wang, Wen-Chin Huang, Zhen-Hua Ling, Yuan Jiang, Yi-Chiao Wu, Héctor Delgado, Massimiliano Todisco, Yu Tsao, Li-Juan Liu, Junichi Yamagishi, Jean-François Bonastre, Tomoki Toda, Nicholas Evans, Robert A. J. Clark, Kai Onuma, Yu-Huai Peng, Sébastien Le Maguer, Avashna Govender, Takashi Kaneda, Andreas Nautsch, Kong Aik Lee, Xin Wang, Srikanth Ronanki, Ville Vestman, Koji Mushika, Ingmar Steiner, Tomi Kinnunen, Fergus Henderson, Jing-Xuan Zhang, Kou Tanaka, Paavo Alku, Hitotsubashi University, University of Edinburgh, Eurecom [Sophia Antipolis], Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), University of Eastern Finland, NEC Corporation, Aalto University, Academia Sinica, ADAPT Centre, Sigmedia Lab, EE Engineering, Trinity College Dublin, Google Inc [Mountain View], Research at Google, Hoya Corp., iFlytek Research, Nagoya City University [Nagoya, Japan], NTT Communication Science Laboratories, NTT Corporation, audEERING GmbH, Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, The Centre for Speech Technology Research [Edinburgh] (CSTR), Southern University of Science and Technology (SUSTech), The work was partially supported by JST CREST Grant No. JPMJCR18A6 (VoicePersonae project), Japan, MEXT KAKENHI Grant Nos. (16H06302, 16K16096, 17H04687, 18H04120, 18H04112, 18KT0051), Japan, the VoicePersonae and RESPECT projects funded by the French Agence Nationale de la Recherche (ANR), the Academy of Finland (NOTCH project no. 309629), and Region Grand Est, France. entitled 'NOTCH: NOn-cooperaTive speaker CHaracterization'). The authors at the University of Eastern Finland also gratefully acknowledge the use of the computational infrastructures at CSC – the IT Center for Science, and the support of the NVIDIA Corporation the donation of a Titan V GPU used in this research. The numerical calculations of some of the spoofed data were carried out on the TSUBAME3.0 supercomputer at the Tokyo Institute of Technology. The work is also partially supported by Region Grand Est, France. The ADAPT centre (13/RC/2106) is funded by the Science Foundation Ireland (SFI)., National Institute of Informatics, EURECOM, Université de Lorraine, Dept Signal Process and Acoust, Trinity College Dublin, Google, USA, HOYA Corporation, IFLYTEK Co., Ltd., Nagoya University, AudEERING GmbH, Avignon Université, University of Science and Technology of China, Aalto-yliopisto, and Southern University of Science and Technology of China (SUSTech)

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Sound (cs.SD), ASVspoof challenge, biometrics, Computer Science - Cryptography and Security, voice conversion, Computer science, Speech synthesis, 02 engineering and technology, computer.software_genre, 01 natural sciences, Computer Science - Sound, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], text-to-speech synthesis, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Audio and Speech Processing (eess.AS), 0202 electrical engineering, electronic engineering, information engineering, Replay, Use case, media forensics, 010301 acoustics, Protocol (object-oriented programming), Text-to-speech synthesis, Database, presentation attack, ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS, Automatic speaker verification, Cryptography and Security (cs.CR), [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Electrical Engineering and Systems Science - Audio and Speech Processing, automatic speaker verification, Voice conversion, Spoofing attack, Biometrics, anti-spoofing, Reliability (computer networking), Database design, Theoretical Computer Science, replay, presentation attack detection, 0103 physical sciences, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, [SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph], ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020206 networking & telecommunications, Human-Computer Interaction, Physical access, computer, countermeasure, Software
Abstract

Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is vulnerable to spoofing, also referred to as "presentation attacks." These vulnerabilities are generally unacceptable and call for spoofing countermeasures or "presentation attack detection" systems. In addition to impersonation, ASV systems are vulnerable to replay, speech synthesis, and voice conversion attacks. The ASVspoof 2019 edition is the first to consider all three spoofing attack types within a single challenge. While they originate from the same source database and same underlying protocol, they are explored in two specific use case scenarios. Spoofing attacks within a logical access (LA) scenario are generated with the latest speech synthesis and voice conversion technologies, including state-of-the-art neural acoustic and waveform model techniques. Replay spoofing attacks within a physical access (PA) scenario are generated through carefully controlled simulations that support much more revealing analysis than possible previously. Also new to the 2019 edition is the use of the tandem detection cost function metric, which reflects the impact of spoofing and countermeasures on the reliability of a fixed ASV system. This paper describes the database design, protocol, spoofing attack implementations, and baseline ASV and countermeasure results. It also describes a human assessment on spoofed data in logical access. It was demonstrated that the spoofing data in the ASVspoof 2019 database have varied degrees of perceived quality and similarity to the target speakers, including spoofed data that cannot be differentiated from bona-fide utterances even by human subjects., Accepted, Computer Speech and Language. This manuscript version is made available under the CC-BY-NC-ND 4.0. For the published version on Elsevier website, please visit https://doi.org/10.1016/j.csl.2020.101114

Published
2020
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2. Detection of minor compounds in complex mineral samples from millions of spectra: A new data analysis strategy in LIBS imaging

Author

Ludovic Duponchel, Frédéric Pelascini, Cécile Fabre, Jean Cauzid, Vincent Motto-Ros, Alessandro Nardecchia, Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 (LASIRE), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), GeoRessources, Institut national des sciences de l'Univers (INSU - CNRS)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Cetim Grand Est, Spectrométrie des biomolécules et agrégats (SPECTROBIO), Institut Lumière Matière [Villeurbanne] (ILM), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Pulsalys, French region Grand Est, French region Rhones Alpes Auvergne (Optolyse, CPER2016), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille Institut (CLIL), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Institut national des sciences de l'Univers (INSU - CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon

Subjects
Chemical imaging, Hyperspectral imaging, Field of view, 02 engineering and technology, 01 natural sciences, Biochemistry, Clustering, Spectral line, Analytical Chemistry, Big data, [SPI]Engineering Sciences [physics], [CHIM]Chemical Sciences, Environmental Chemistry, Spectroscopy, Cluster analysis, [PHYS]Physics [physics], Detection limit, business.industry, Chemistry, 010401 analytical chemistry, Pattern recognition, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Characterization (materials science), Laser-induced breakdown spectroscopy (LIBS), Artificial intelligence, 0210 nano-technology, business
Abstract

International audience; Today, Laser-Induced Breakdown Spectroscopy (LIBS) imaging is in full change. Indeed, always more stable instrumentations are developed, which significantly increases the signal quality and naturally the analytical potential of the technique for the characterization of complex and heterogeneous samples at the micro-scale level. Obviously, other intrinsic features such as a limit of detection in the order of ppm, a high field of view and high acquisition rate make it one of the most complete chemical imaging techniques to date. It is thus possible in these conditions to acquire several million spectra from one single sample in just hours. Managing big data in LIBS imaging is the challenge ahead. In this paper, we put forward a new spectral analysis strategy, called embedded k-means clustering, for simultaneous detection of major and minor compounds and the generation of associated localization maps. A complex rock section with different phases and traces will be explored to demonstrate the value of this approach.

Published
2020
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3. Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing

Author

Xin Wang, Kong Aik Lee, Massimiliano Todisco, Junichi Yamagishi, Andreas Nautsch, Md. Sahidullah, Héctor Delgado, Tomi Kinnunen, Nicholas Evans, University of Eastern Finland, Eurecom [Sophia Antipolis], Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), National Institute of Informatics (NII), Nuance Communications [Spain], Institute for Infocomm Research (I2R), This work was supported by a number of projects and funding sources: VoicePersonae, supported by the French Agence Nationale de la Recherche (ANR) and the Japan Science and Technology Agency (JST) with grant No. JPMJCR18A6, Academy of Finland (proj. 309629), Region Grand Est, France., Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Sound (cs.SD), Computer science, multi-dimensional scaling, 02 engineering and technology, Classifier, Statistics - Applications, Computer Science - Sound, Machine Learning (cs.LG), Set (abstract data type), 030507 speech-language pathology & audiology, 03 medical and health sciences, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Audio and Speech Processing (eess.AS), Classifier (linguistics), 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Applications (stat.AP), Representation (mathematics), [STAT.AP]Statistics [stat]/Applications [stat.AP], Receiver operating characteristic, business.industry, Visual comparison, 020206 networking & telecommunications, Pattern recognition, Mixture model, Automatic summarization, Adjacency list, Artificial intelligence, 0305 other medical science, business, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Whether it be for results summarization, or the analysis of classifier fusion, some means to compare different classifiers can often provide illuminating insight into their behaviour, (dis)similarity or complementarity. We propose a simple method to derive 2D representation from detection scores produced by an arbitrary set of binary classifiers in response to a common dataset. Based upon rank correlations, our method facilitates a visual comparison of classifiers with arbitrary scores and with close relation to receiver operating characteristic (ROC) and detection error trade-off (DET) analyses. While the approach is fully versatile and can be applied to any detection task, we demonstrate the method using scores produced by automatic speaker verification and voice anti-spoofing systems. The former are produced by a Gaussian mixture model system trained with VoxCeleb data whereas the latter stem from submissions to the ASVspoof 2019 challenge., Comment: Accepted to Interspeech 2021. Example code available at https://github.com/asvspoof-challenge/classifier-adjacency

Published
2021
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4. Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes

Author

Romain Serizel, Hakan Erdogan, Justin Salamon, Nicolas Turpault, John R. Hershey, Scott Wisdom, Eduardo Fonseca, Prem Seetharaman, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Google Inc, Research at Google, Universitat Pompeu Fabra [Barcelona] (UPF), Descript, Inc., Adobe Research, Part of this work was made with the support of the French National Research Agency, in the framework of the project LEAUDS 'Learning to understand audio scenes' (ANR-18-CE23-0020) and the French region Grand-Est. High Performance Computing resources were partially provided by the EXPLOR centre hosted by the University de Lorraine., Grid'5000, ANR-18-CE23-0020,LEAUDS,Apprentissage statistique pour la compréhension de scènes audio(2018), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
FOS: Computer and information sciences, Sound localization, Sound (cs.SD), Reverberation, Soundscape, Computer science, Speech recognition, 02 engineering and technology, Computer Science - Sound, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Audio and Speech Processing (eess.AS), Robustness (computer science), FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Sound (geography), synthetic soundscapes, geography, Signal processing, geography.geographical_feature_category, Event (computing), Sound event detection, [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD], Benchmark (computing), sound separation, 020201 artificial intelligence & image processing, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

International audience; We propose a benchmark of state-of-the-art sound event detection systems (SED). We designed synthetic evaluation sets to focus on specific sound event detection challenges. We analyze the performance of the submissions to DCASE 2021 task 4 depending on time related modifications (time position of an event and length of clips) and we study the impact of non-target sound events and reverberation. We show that the localization in time of sound events is still a problem for SED systems. We also show that reverberation and non-target sound events are severely degrading the performance of the SED systems. In the latter case, sound separation seems like a promising solution.

Published
2020
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5. Improving Sound Event Detection Metrics: Insights from DCASE 2020

Author

Francesco Tuveri, Sacha Krstulovic, Cagdas Bilen, Romain Serizel, Juan Azcarreta, Giacomo Ferroni, Nicolas Turpault, Audio Analytic, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), UL/INRIA’s work for this article was partly supported by the French National Research Agency (project LEAUDS 'Learning to under-stand audioscenes' ANR-18-CE23-0020) and by the French region Grand-Est., Grid'5000, and ANR-18-CE23-0020,LEAUDS,Apprentissage statistique pour la compréhension de scènes audio(2018)

Subjects
FOS: Computer and information sciences, Sound (cs.SD), Dependency (UML), Computer science, 02 engineering and technology, computer.software_genre, Computer Science - Sound, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Audio and Speech Processing (eess.AS), Robustness (computer science), FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Event (probability theory), Operating point, Signal processing, Intersection (set theory), Sound detection, segment vs event criteria, sound event detection, evaluation metrics, Ranking, [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD], 020201 artificial intelligence & image processing, Data mining, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, computer, polyphonic sound detection score, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

International audience; The ranking of sound event detection (SED) systems may be biased by assumptions inherent to evaluation criteria and to the choice of an operating point. This paper compares conventional event-based and segment-based criteria against the Polyphonic Sound Detection Score (PSDS)'s intersection-based criterion, over a selection of systems from DCASE 2020 Challenge Task 4. It shows that, by relying on collars , the conventional event-based criterion introduces different strictness levels depending on the length of the sound events, and that the segment-based criterion may lack precision and be application dependent. Alternatively, PSDS's intersection-based criterion overcomes the dependency of the evaluation on sound event duration and provides robustness to labelling subjectivity, by allowing valid detections of interrupted events. Furthermore, PSDS enhances the comparison of SED systems by measuring sound event modelling performance independently from the systems' operating points.

Published
2020
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6. Carbon heterogeneities in austenite during Quenching & Partitioning (Q&P) process revealed by in situ High Energy X-Ray Diffraction (HEXRD) experiments

Author

Steve Gaudez, Michel Soler, Frédéric Danoix, Guillaume Geandier, Sébastien Allain, Mohamed Gouné, Institut Jean Lamour (IJL), Université de Lorraine (UL)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Labex DAMAS, Université de Lorraine (UL), Groupe de physique des matériaux (GPM), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), ArcelorMittal Maizières Research SA, ArcelorMittal, Institut de Chimie de la Matière Condensée de Bordeaux (ICMCB), Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), This work was supported by the National Research Agency (ANR). The synchrotron experiments were realized in December 2016, under the P160 grant at DESY PETRA P-07 in Hamburg, which is fully acknowledged. The authors want to thank Jean-Christophe Hell for his support during the experiments. The authors would like also to thank MATERALIA cluster (Region Grand Est) for their support., ANR-14-CE07-0029,CAP NANO,Partition du carbone dans les phases ferritiques nanostructurées: cinétiques et microstructures(2014), ANR-11-LABX-0008,DAMAS,Design des Alliages Métalliques pour Allègement des Structures(2011), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Université de Rouen Normandie (UNIROUEN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), and Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)

Subjects
Diffraction, Materials science, Analytical chemistry, chemistry.chemical_element, 02 engineering and technology, Atom probe, 01 natural sciences, law.invention, [SPI.MAT]Engineering Sciences [physics]/Materials, law, Phase (matter), partitioning, 0103 physical sciences, General Materials Science, steel, X-Ray diffraction, austenite, 010302 applied physics, Quenching, Austenite, Mechanical Engineering, Metals and Alloys, martensite, 021001 nanoscience & nanotechnology, Condensed Matter Physics, chemistry, Mechanics of Materials, Martensite, X-ray crystallography, 0210 nano-technology, Carbon
Abstract

Based on the evolution of the positions and intensities of the diffraction peaks, high energy X-ray diffraction (HEXRD) is recognized as the ultimate method to follow quantitatively in situ phase transformations in steels. However, the possible asymmetricity of diffraction peaks is seldom considered, and is known to bear information. A procedure for quantifying their skewness is proposed. In the case of a third generation high strength steel obtained by quench and partitioning (Q&P), the skewness is shown to be due to carbon heterogeneities at austenite/martensite interfaces developed at nanoscale, in agreement with prior post mortem atom probe tomography (APT) investigations.

Published
2020
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7. Microstructure Evolution and Competitive Reactions during Quenching and Partitioning of a Model Fe–C–Mn–Si Alloy

Author

Guillaume Geandier, Samy Aoued, Steve Gaudez, Mohamed Gouné, Frédéric Danoix, Jean-Christophe Hell, Michel Soler, Sébastien Allain, Institut de Chimie de la Matière Condensée de Bordeaux (ICMCB), Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Groupe de physique des matériaux (GPM), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), Institut Jean Lamour (IJL), Université de Lorraine (UL)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), ArcelorMittal Maizières Research SA, ArcelorMittal, This work was partly carried out owing the experimental GENESIS platform. GENESIS is supported by the region Haute-Normandie, the Metropole Rouen Normandie, the CNRS via LABEX EMC, and the French National Research Agency as part of the program 'Investissement d’Avenir' ANR 11-EQPX-002. The synchrotron experiments were realized in December 2016 under the P160 grant at DESY PETRA P-07 in Hamburg, which is fully acknowledged. The authors would like also to thank MATERALIA cluster (Region Grand Est) for their support., ANR-14-CE07-0029,CAP NANO,Partition du carbone dans les phases ferritiques nanostructurées: cinétiques et microstructures(2014), ANR-11-LABX-0008,DAMAS,Design des Alliages Métalliques pour Allègement des Structures(2011), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Labex DAMAS, Université de Lorraine (UL), and ANR-11-EQPX-0020,GENESIS,Groupe d'Etudes et de Nanoanalyses des Effets d'IrradiationS(2011)

Subjects
lcsh:TN1-997, Materials science, Bainite, Alloy, chemistry.chemical_element, Thermodynamics, 02 engineering and technology, Atom probe, engineering.material, Lath, 01 natural sciences, [SPI.MAT]Engineering Sciences [physics]/Materials, law.invention, [SPI]Engineering Sciences [physics], law, partitioning, 0103 physical sciences, General Materials Science, ddc:530, high-energy X-ray diffraction, lcsh:Mining engineering. Metallurgy, 010302 applied physics, Quenching, Austenite, Metals and Alloys, 021001 nanoscience & nanotechnology, atom probe tomography, chemistry, Martensite, steels, engineering, quenching and partitioning, 0210 nano-technology, Carbon
Abstract

The mechanisms behind the carbon enrichment of austenite during quenching and partitioning are still a matter of debate. This work investigates the microstructural evolution during the quenching and partitioning of a model Fe&ndash, C&ndash, Mn&ndash, Si alloy by means of in situ high energy X-ray diffraction (HEXRD) atom probe tomography, and image analysis. The ultra-fast time-resolved quantitative information about phase transformations coupled with image analysis highlights the formation of carbide-free BCT bainite, which is formed within a very short range during the reheating and partitioning step. Its transformation rate, which is a better indicator than the intrinsic volume fraction, depends on the quenching temperature (QT). It is shown to decrease with decreasing QT, from 45% at QT = 260 &deg, C to 20% at QT = 200 &deg, C. As a consequence, a significant part of the carbon enrichment observed in austenite can be attributed to bainite transformation. Furthermore, a large part of carbon was shown to be trapped into martensite. Both the formation of Fe2.6C iron carbides and the segregation of carbon on lath boundaries in martensite were highlighted by atom probe tomography. The energy for carbon segregation was determined to be 0.20 eV, and the carbon concentration on the lath boundaries was obtained to be around 25 at %. Therefore, the carbon enrichment of austenite is the result of competitive reactions such as carbon partitioning from martensite, bainite transformation, and carbon trapping in martensite.

Published
2020
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8. Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs

Author

Miguel Couceiro, Kevin Dalleau, Malika Smaïl-Tabbone, Computational Algorithms for Protein Structures and Interactions (CAPSID), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Knowledge representation, reasonning (ORPAILLEUR), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), ANR-15-RHUS-0004,FIGHT-HF,Combattre l'insuffisance cardiaque(2015), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Funded by the RHU FIGHT-HF (ANR-15-RHUS-0004) and the Region Grand Est (France).

Subjects
Theoretical computer science, Computer science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Random tree, Decision tree, 02 engineering and technology, Complex network, Vertex (geometry), Dissimilarity, Graph clustering, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], 020204 information systems, Heterogeneous data, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Pairwise comparison, [INFO]Computer Science [cs], Cluster analysis, Categorical variable, Attributed graph, Clustering coefficient, MathematicsofComputing_DISCRETEMATHEMATICS
Abstract

International audience; A current challenge in graph clustering is to tackle the issue of complex networks, i.e, graphs with attributed vertices and/or edges. In this paper, we present GraphTrees, a novel method that relies on random decision trees to compute pairwise dissimilarities between vertices in a graph. We show that using different types of trees, it is possible to extend this framework to graphs where the vertices have attributes. While many existing methods that tackle the problem of clustering vertices in an attributed graph are limited to categorical attributes, GraphTrees can handle heterogeneous types of vertex attributes. Moreover, unlike other approaches, the attributes do not need to be preprocessed. We also show that our approach is competitive with well-known methods in the case of non-attributed graphs in terms of quality of clustering, and provides promising results in the case of vertex-attributed graphs. By extending the use of an already well established approach-the random trees-to graphs, our proposed approach opens new research directions, by lever-aging decades of research on this topic.

Published
2019
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9. High dynamic range reflectance transformation imaging: an adaptive multi-light approach for visual surface quality assessment

Author

Yuly Castro, Hugues Favreliere, Abir Zendagui, Marvin Nurit, G. Le Goïc, Alamin Mansouri, Imagerie et Vision Artificielle [Dijon] (ImViA), Université de Bourgogne (UB), Laboratoire SYstèmes et Matériaux pour la MEcatronique (SYMME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), French National Research Agency (ANR) ANR, Univ Haute Alsace, Mulhouse Alsace Agglomerat, Region Grand Est, IDS GmbH, Fac Sci Mulhouse, Cudel, Bazeille, and Verrier

Subjects
Visual saliency, 0209 industrial biotechnology, Observer (quantum physics), Computer science, 02 engineering and technology, 01 natural sciences, HDR Imaging, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 010309 optics, 020901 industrial engineering & automation, Robustness (computer science), 0103 physical sciences, Computer vision, [INFO]Computer Science [cs], Entropy (energy dispersal), High dynamic range, [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics], Pixel, business.industry, Visual appearance, Quality inspection, Kurtosis, RTI imaging, Artificial intelligence, business, Polynomial texture mapping
Abstract

International audience; Visual inspection of surfaces is a complex sensory process that depends on several factors related to the observer [1]-[3] (his knowledge, experience, tiredness or the purpose of observation), the object observed and the light environment. In order to reduce the subjectivity and to improve the robustness of the analysis of the appearance quality of the inspected surfaces, multi-lighting imaging techniques like RTI (Reflectance Transformation Imaging) are being used more and more. However, and to make the most of this technique, it is necessary to control the acquisition and processing, especially for highly reflective surfaces and / or having particular surface topographies. Thus, we propose an innovative implementation based on the RTI technique by increasing it with an acquisition and a processing in high dynamic range (HDR), adapted and adaptive. This coupling makes it possible to avoid the low dynamic range (LDR) of the cameras and therefore ensures a faithful estimate, for each pixel, of the angular component of the reflectance of the surface inspected, in particular in the case of non-Lambertian surfaces, and heterogeneous surfaces in terms of material and / or geometric texturing. Beyond appearance reconstruction, maps associated with geometric and statistical indicator maps (local slope/kurtosis/skewness/entropy) are used to show the relevance and performance of the proposed HDR-RTI methodology.

Published
2019
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10. Chalcogenide glasses as a playground for the application of first-principles molecular dynamics to disordered materials

Author

Mauro Boero, Evelyne Martin, Guido Ori, Assil Bouzid, Sébastien Le Roux, Carlo Massobrio, Ori, Guido, Institut de Physique et Chimie des Matériaux de Strasbourg (IPCMS), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), IRCER - Axe 3 : organisation structurale multiéchelle des matériaux (IRCER-AXE3), Institut de Recherche sur les CERamiques (IRCER), Institut des Procédés Appliqués aux Matériaux (IPAM), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut des Procédés Appliqués aux Matériaux (IPAM), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF), Physique - IEMN (PHYSIQUE - IEMN), Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF), Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS), Institut Charles Gerhardt Montpellier - Institut de Chimie Moléculaire et des Matériaux de Montpellier (ICGM), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Institut de Chimie du CNRS (INC)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Université de Strasbourg (UNISTRA)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Physique-IEMN (PHYSIQUE-IEMN), Institut Charles Gerhardt Montpellier - Institut de Chimie Moléculaire et des Matériaux de Montpellier (ICGM ICMMM), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut de Chimie du CNRS (INC), and AcknowledgementsM.B. thanks Pôle HPC, Equipex Equip@Meso/CPER Alsacalcul atthe University of Saskatchewan, and Grand Equipement National deCalcul Intensif (GENCI) under allocation DARI-A2 A0060906092. G.O.acknowledges the Fédération de Recherche en Matériaux etNanosciences Region Grand-Est (project HARWEST) and the SeedMoney program of Eucor - The European Campus (project MEDIA) forfinancial support

Subjects
Glass structure, Computer science, Chalcogenide, 02 engineering and technology, [SPI.MAT] Engineering Sciences [physics]/Materials, 010402 general chemistry, 01 natural sciences, London dispersion force, amorphous materials, [SPI.MAT]Engineering Sciences [physics]/Materials, Molecular dynamics, symbols.namesake, chemistry.chemical_compound, [CHIM] Chemical Sciences, [CHIM]Chemical Sciences, General Materials Science, Statistical physics, glass structure, General Chemistry, 021001 nanoscience & nanotechnology, Condensed Matter Physics, electronic structure, molecular dynamics, [PHYS.COND.CM-MS] Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], 0104 chemical sciences, [CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry, [CHIM.THEO] Chemical Sciences/Theoretical and/or physical chemistry, chemistry, symbols, [PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], chalcogenides, Computational material science, van der Waals force, 0210 nano-technology
Abstract

International audience; An overview of the major first-principles methods used to simulate condensed phases is presented, with special emphasis on chalcogenide glasses. The scope of this review article is to offer a survey of fundamental algorithms and techniques, accompanied by a few recent examples particularly representative of computational materials science applied to disordered chalcogenide phases. Special attention is devoted to the inclusion of long-range van der Waals dispersion forces, treatment of the exact exchange, dynamical simulations and extraction of optical and dielectric properties. Machine learning techniques are introduced as recent forefront applications of first-principle methods. In this latter case, accurate quantum-mechanics based simulations are crucial to generate a data base exploited by neuronal-network type algorithms to create accurate interatomic potentials (force fields) allowing for large and long-lasting simulations of realistic disordered materials. The atomic-level knowledge provided by the combination of high-performance computing and advanced computational methods pave the route for a rational approach to the design of novel chalcogenides possessing tuned properties for specific applications in next-generation devices.

Published
2019
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11. Recovery of 3-hydroxypropionic acid from organic phases after reactive extraction with amines in an alcohol-type solvent

Author

Ioan-Cristian Trelea, Florian Chemarin, Marwen Moussa, Florent Allais, Violaine Athès, Centre Européen de Biotechnologies et Bioéconomie (CEBB), Agro-Biotechnologies Industrielles (ABI), AgroParisTech, Génie et Microbiologie des Procédés Alimentaires (GMPA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Region Grand-Est, Conseil Departemental de la Marne, and Grand Reims

Subjects
Standard enthalpy of reaction, diluent swing, Inorganic chemistry, back-extraction, temperature swing, Salt (chemistry), Filtration and Separation, Alcohol, 02 engineering and technology, 3-Hydroxypropionic acid, Diluent, Analytical Chemistry, chemistry.chemical_compound, [CHIM.GENI]Chemical Sciences/Chemical engineering, 020401 chemical engineering, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, 0204 chemical engineering, chemistry.chemical_classification, pH swing, Extraction (chemistry), 021001 nanoscience & nanotechnology, 6. Clean water, Solvent, chemistry, Amine gas treating, 0210 nano-technology
Abstract

International audience; Reactive extraction is a well-known method for the recovery of organic acids from dilute streams. The extraction through complex formation with amines is followed by its back-extraction. Their affinity for amine extractants makes their back-extraction a limiting step. The case of 3-hydroxypropionic acid is addressed here. Three methods were compared: salts additions, diluent swing and temperature swing. Mineral bases led to complete 3-HP recovery but as a salt. Diluent swing was tested using n-hexane as the anti-solvent. Results showed that increasing the n-hexane content led to a great increase of 3-HP recovery. However, high recovery yields are associated with high dilutions. The temperature was varied from 4 to 140 °C and it led to a high decrease of the acid-amine complex formation. Our thermochemical study showed an apparent heat of reaction of-25.3 kJ/mol and, at 140 °C, 78% of 3-HP can be recovered in a single step.

Published
2019
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12. Ferulic acid derivatives used as biobased powders for a convenient plasticization of polylactic acid in continuous hot-melt process

Author

Antoine Gallos, Samir Kasmi, Johnny Beaugrand, Gabriel Paës, Florent Allais, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA), Agro-Biotechnologies Industrielles (ABI), AgroParisTech, Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de la Recherche Agronomique (INRA), Region Grand Est, Conseil Departemental de la Marne, Fractionnement des AgroRessources et Environnement - UMR-A 614 (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA)-SFR Condorcet, and Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Materials science, Polymers and Plastics, MIGRATION, [SDV]Life Sciences [q-bio], General Physics and Astronomy, plastification, 02 engineering and technology, 010402 general chemistry, 01 natural sciences, Ferulic acid, chemistry.chemical_compound, Polylactic acid, Materials Chemistry, Thermal stability, acide polylactique, POLY(LACTIC ACID), PHOSPHITE, chemistry.chemical_classification, SOLUBILITY PARAMETERS, Organic Chemistry, Plasticizer, Polymer, MECHANICAL-PROPERTIES, CHAIN EXTENSION, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Hildebrand solubility parameter, extrusion, chemistry, Chemical engineering, acide férulique, STARCH, Extrusion, 0210 nano-technology, Glass transition, FIBERS, ferulic acid
Abstract

Plasticizers are additives used to soften polymers, but most of them are oily or waxy and are difficult to process in a continuous hot-melt process. The plasticizing effect of four functionalized ferulic acid derivatives designed with controlled solubility parameters was investigated upon the study of both the thermal stability and the mechanical properties of polylactic acid (PLA) blends. The synthesized powders were incorporated into PLA through a continuous hot-melt process (extrusion) allowing the derivatives to turn from crystalline to an amorphous state. Such phase transition permitted the derivatives to act as plasticizers, reaching a reduction of the Young's modulus of PLA by 40% for one of the derivatives blended at 20 wt%. Another derivative decreased the glass transition of the PLA from 56.6 °C to 26.3 °C at the same content. These works demonstrate the interest of using phase transition additives to ease the mixing of efficient plasticizers by hot-melt processing.

Published
2019
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13. Output injection filtering redesign in high-gain observers

Author

Daniele Astolfi, Luca Zaccarian, Marc Jungers, Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Équipe Méthodes et Algorithmes en Commande (LAAS-MAC), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J), University of Trento [Trento], Region Grand-Est, CaRiTRo, grant PowerLyap, Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
0209 industrial biotechnology, High-gain antenna, Observer (quantum physics), Noise measurement, Computer science, 020208 electrical & electronic engineering, 02 engineering and technology, Filter (signal processing), Dynamical system, Term (time), Noise, 020901 industrial engineering & automation, Control theory, Convergence (routing), 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY]
Abstract

International audience; We propose a new paradigm to redesign high-gain observers in order to improve performances in the presence of measurement noise. In particular, instead of driving the observer by means of a standard output injection term, we filter it with a dynamical system having good filtering properties. In this first preliminary result we also select the filter in order to address numerical challenges.

Published
2018

14. Chemo-enzymatic synthesis of renewable sterically-hindered phenolic antioxidants with tunable polarity from lignocellulose and vegetal oil components

Author

Sandra Domenek, Florent Allais, Louis Hollande, Agro-Biotechnologies Industrielles (ABI), AgroParisTech, Ingénierie, Procédés, Aliments (GENIAL), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), Grand Reims, Conseil General de la Marne, Region Grand Est, and Allais, Florent

Subjects
Antioxidant, antioxidant, DPPH, medicine.medical_treatment, [SDV]Life Sciences [q-bio], CAL-B, 02 engineering and technology, Lignin, 7. Clean energy, 01 natural sciences, Antioxidants, lcsh:Chemistry, ferulic acid, fatty acid ethyl esters, Ferulic acid, chemistry.chemical_compound, [SDV.IDA]Life Sciences [q-bio]/Food engineering, Organic chemistry, lcsh:QH301-705.5, Spectroscopy, Candida, biology, General Medicine, 021001 nanoscience & nanotechnology, Computer Science Applications, 0210 nano-technology, Thermogravimetric analysis, Coumaric Acids, 010402 general chemistry, Article, Catalysis, Fungal Proteins, Inorganic Chemistry, Phenols, Glycerol, medicine, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Thermal stability, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Physical and Theoretical Chemistry, Molecular Biology, Esterification, Organic Chemistry, Lipase, Butylated Hydroxytoluene, biology.organism_classification, 0104 chemical sciences, lcsh:Biology (General), lcsh:QD1-999, chemistry, Candida antarctica, Oils
Abstract

Despite their great antioxidant activities, the use of natural phenols as antioxidant additives for polyolefins is limited owing to their weak thermal stability and hydrophilic character. Herein, we report a sustainable chemo-enzymatic synthesis of renewable lipophilic antioxidants specifically designed to overcome these restrictions using naturally occurring ferulic acid (found in lignocellulose) and vegetal oils (i.e., lauric, palmitic, stearic acids, and glycerol) as starting materials. A predictive Hansen and Hildebrand parameters-based approach was used to tailor the polarity of newly designed structures. A specific affinity of Candida antarctica lipase B (CAL-B) towards glycerol was demonstrated and exploited to efficiently synthesized the target compounds in yields ranging from 81 to 87%. Antiradical activity as well as radical scavenging behavior (H atom-donation, kinetics) of these new fully biobased additives were found superior to that of well-established, commercially available fossil-based antioxidants such as Irganox 1010&reg, and Irganox 1076&reg, Finally, their greater thermal stabilities (302 &lt, Td5% &lt, 311 &deg, C), established using thermal gravimetric analysis, combined with their high solubilities and antioxidant activities, make these novel sustainable phenolics a very attractive alternative to current fossil-based antioxidant additives in polyolefins.

Published
2018
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15. Detoxification of highly acidic hemicellulosic hydrolysate from wheat straw by diananofiltration with a focus on phenolic compounds

Author

Andreia R. S. Teixeira, Marie-Laure Lameloise, Marielle Bouix, Axel Fayet, Florent Allais, Agro-Biotechnologies Industrielles (ABI), AgroParisTech, Université Paris Saclay (COmUE), Génie et Microbiologie des Procédés Alimentaires (GMPA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Ingénierie, Procédés, Aliments (GENIAL), Region Grand Est, and Conseil Departemental de la Marne and Grand Reims

Subjects
[SDV]Life Sciences [q-bio], Filtration and Separation, 02 engineering and technology, 010501 environmental sciences, Furfural, 01 natural sciences, Biochemistry, Diafiltration, Hydrolysate, Acetic acid, chemistry.chemical_compound, Hemicellulosic hydrolysate, [SDV.IDA]Life Sciences [q-bio]/Food engineering, Osmotic pressure, General Materials Science, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Physical and Theoretical Chemistry, 0105 earth and related environmental sciences, Steam explosion, Chromatography, food and beverages, Sulfuric acid, Straw, 021001 nanoscience & nanotechnology, Nanofiltration, Phenolic compounds, chemistry, 0210 nano-technology, Detoxification
Abstract

International audience; Nanofiltration was studied for detoxification of lignocellulose hydrolysates obtained in harsh conditions. A hemicellulosic hydrolysate obtained from sulfuric acid steam explosion of wheat straw and presenting very low pH ( = 1) and high osmotic pressure (28 bar) was studied and 8 inhibitory compounds were followed, among which 4 phenolic compounds. Several polymeric nanofiltration membranes were compared for separation performances and permeabilities; DK membrane (GE Osmonics) proved suitable with high rejection of sugars ( > 99%) and lower rejections of inhibitors. Acetic acid and furfural were quasi-fully transmitted whereas the rejection of compounds ranked as follow: HMF (5-hydroxymethyl-furfural) < coumaric acid < levulinic acid < vanillin < ferulic acid < syringaldehyde with values of 40%, 50%, 60%, 80%, 90% and 98%, respectively, at a permeate flux of 14 L h(-1) m(-2). Diafiltration was carried out at a transmembrane pressure of 26 bar until 3 DV (Diafiltration Volume) to complete detoxification, and continuous and sequential-dilution modes were compared. Thanks to the permeability of the membrane to the monovalent form of sulfuric acid HSO4-, effective transmembrane pressure was increased and pH reached 2. At 3 DV, both modes showed removal performances between 92% (acetic acid and furfural) and 25% (syringaldehyde). Irreversible fouling was observed, leading to 30% permeability loss after diafiltration.

Published
2018
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