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Enregistrement W2997009312 · doi:10.1002/ejoc.201901718

European Research in Focus: Mechanochemistry for Sustainable Industry (COST Action <i>MechSustInd</i>)

2020· article· en· W2997009312 sur OpenAlexaboutno aff
José G. Hernández, Iván Halász, Deborah E. Crawford, Martin Krupička, Matěj Baláž, Vânia André, Liana Vella‐Żarb, Allan Niidu, Felipe Garcı́a, Lucia Maini, Evelina Colacino

Notice bibliographique

RevueEuropean Journal of Organic Chemistry · 2020
Typearticle
Langueen
DomaineEngineering
Thématique3D Printing in Biomedical Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMechanochemistryEuropean unionSustainable developmentEngineeringAction (physics)NanotechnologyChemistryPolitical scienceEngineering ethicsBusinessPhysicsChemical engineeringInternational tradeMaterials science

Résumé

récupéré en direct d'OpenAlex

In this Guest Editorial the recently funded COST Action: CA18112 – Mechanochemistry for Sustainable Industry (MechSustInd) is introduced to the scientific community. The use of mechanical energy to facilitate chemical transformations (mechanochemistry) has been rapidly gaining momentum across diverse areas of science. Experimentally, the strategies to mechanically promote physico-chemical changes in matter are varied and include the use of mechanical milling, extrusion techniques, pulsed ultrasonication, and single-molecule force-spectroscopy approaches, among others. Altogether, the implementation of these experimental techniques has resulted in the discovery of new chemical reactions and in the development of more sustainable alternatives to classical synthetic protocols. Collectively, the renaissance and thriving growth of mechanochemistry with its potential to enhance chemical synthesis have been recently acknowledged by the International Union of Pure and Applied Chemistry (IUPAC).1 Simultaneously, in 2019, one of the most prestigious and influential funding organizations for research and innovation networks in Europe, the European Cooperation in Science and Technology (COST),2 funded the COST Action: CA18112 – Mechanochemistry for Sustainable Industry (MechSustInd).3 This will provide a unique opportunity for scientific and technological growth in the area of mechanochemistry across Europe. As such, we are pleased to celebrate as well as to introduce the MechSustInd COST Action in this Editorial. The first steps towards a successful COST Action have already begun. To date, MechSustInd encompasses partners from 33 COST Member Countries, including 18 Inclusiveness Target Countries and partners, nine companies, one European intergovernmental scientific research organization (European Synchrotron Radiation Facility, ESRF), as well as partners from Canada, China, Mexico, Russia, Singapore, and USA. In total, represented by 72 Academic Institutions across Europe and around the world (Figure 1). During its lifespan, the COST Action CA18112 MechSustInd will enhance the cooperation of scientists already working in the field, but more importantly it will promote the translation of mechanochemistry into alternative niche sectors. For instance, efforts will be devoted to disseminate and train fundamental aspects of mechanochemistry and mechanochemical techniques within higher education and vocational training settings. Additionally, all members of this COST Action CA18112 will aim to develop mechanochemical synthetic routes of value-added products from laboratory-scale set-ups to large-scale production. This quest will be closely accompanied by physico-chemical and computational studies to better understand the mechanistic aspects prevailing in such mechanochemical transformations. Important to the success of implementing mechanochemical protocols in industry is the development of new mechanochemical techniques to complement existing strategies for the activation of reactants by mechanical treatment. More ambitious targets for MechSustInd also lie ahead, namely, the establishment of fruitful multi-disciplinary collaborative networks involving researchers from a myriad of academic institutions and industries. These networks will share the common objective of harmonizing both fundamental and applied research for industrial needs and fostering technological transfer from research laboratories to industrial value chains. Furthermore, to increase the potential impact of this COST Action, we will engage with key stakeholders to gain awareness of the current developments in policy making, business strategies, and societal needs. Moreover, we wish to use this Editorial to encourage proactive participation of all scientists, educators (schools and universities), engineers, industrial partners, policy- and decision-makers, and funding bodies alike to successfully achieve the objectives of COST Action CA18112 MechSustInd. Undoubtedly, vital for the achievement of this COST Action's objectives will be the use of more focused networking programs such as Short-Term Scientific Missions aimed at fostering collaboration via excellent research infrastructures and sharing techniques amongst the members of MechSustInd. Equally important will be the organization of Training Schools to standardize, propagate, and encourage the adoption of good experimental practices across the current and future mechanochemistry scientific community. Hence, established scientists will work together with Early Career Investigators to promote the scientific excellence within the field whilst maintaining gender balance within the network. Overall, we hope that in the upcoming years, the COST Action MechSustInd will become an inflexion point in the expansion, diversification, and establishment of mechanochemistry in a wide range of fields such as organic chemistry, organometallic synthesis, solid-state chemistry, spectroscopy, molecular modeling, process engineering, and crystal engineering, to name a few. Let the coming chemistry years be mechanical! This article is based upon work from COST Action CA18112, supported by COST (European Cooperation in Science and Technology).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesIntégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,113
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,003
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,087
Tête enseignante GPT0,323
Écart entre enseignants0,236 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations57
Publié2020
Routes d'admission1
Résumé présentoui

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