Multiscale Mechanistic Insights of Shaped Catalyst Body Formulations and Their Impact on Catalytic Properties

International audienceZeolite-based catalysts are globally employed in many industrial processes, such as in crude-oil refining and in the production of bulk chemicals. However, to be implemented in industrial reactors efficiently, zeolite powders are required to be shaped in catalyst bodies. Scale-up of zeolite catalysts into such forms comes with side effects to its overall physicochem-ical properties and to those of its constituting components. Although fundamental research into "technical" solid catalysts is scarce, binder effects have been reported to significantly impact their catalytic properties and lifetime. Given the large number of additional (in)organic components added in the formulation, it is somehow surprising to see that there is a distinct lack of research into the unintentional impact organic additives can have on the properties of the zeolite and the catalyst bodies in general. Here, we systematically prepared a series of alumina-bound zeolite ZSM-5-based catalyst bodies, with organic additives such as peptizing, plasticizing, and lubricating agents, to rationalize their impacts on the physicochemical properties of the shaped catalyst bodies. By utilizing a carefully selected arsenal of bulk and high-spatial resolution multiscale characterization techniques, as well as specifically sized bioinspired fluorescent nanoprobes to study pore accessibility, we clearly show that, although the organic additives achieve their primary function of a mechanically robust material, uncontrolled processes are taking place in parallel. We reveal that the extrusion process can lead to zeolite dealumination (from acid peptizing treatment, and localized steaming upon calcination); meso-and macropore structural rearrangement (via burning-out of organic plasticizing and lubricating agents upon calcination); and abating of known alumina binder effects (via scavenging of Al species via chelating lubricating agents), which significantly impact catalytic performance. Understanding the mechanisms behind such effects in industrial-grade catalyst formulations can lead to enhanced design of these important materials, which can improve process efficiency in a vast range of industrial catalytic reactions

Effect of zeolite topology and reactor configuration on the direct conversion of CO2 to light olefins and aromatics

The direct transformation of CO2 into high-value-added hydrocarbons (i.e., olefins and aromatics) has the potential to make a decisive impact in our society. However, despite the efforts of the scientific community, no direct synthetic route exists today to synthesize olefins and aromatics from CO2 with high productivities and low undesired CO selectivity. Herein, we report the combination of a series of catalysts comprising potassium superoxide doped iron oxide and a highly acidic zeolite (ZSM-5 and MOR) that directly convert CO2 to either light olefins (in MOR) or aromatics (in ZSM-5) with high space–time yields (STYC2-C4= = 11.4 mmol·g–1·h–1; STYAROM = 9.2 mmol·g–1·h–1) at CO selectivities as low as 12.8% and a CO2 conversion of 49.8% (reaction conditions: T = 375 °C, P = 30 bar, H2/CO2 = 3, and 5000 mL·g–1·h–1). Comprehensive solid-state nuclear magnetic resonance characterization of the zeolite component reveals that the key for the low CO selectivity is the formation of surface formate species on the zeolite framework. The remarkable difference in selectivity between the two zeolites is further rationalized by first-principles simulations, which show a difference in reactivity for crucial carbenium ion intermediates in MOR and ZSM-5

Valence and spin situations in isomeric [(bpy)Ru(Q′)2]n (Q′ = 3,5-di-tert- butyl-N-aryl-1,2-benzoquinonemonoimine). An experimental and DFT analysis

The article deals with the ruthenium complexes, [(bpy)Ru(Q′)2] (1–3) incorporating two unsymmetrical redox-noninnocent iminoquinone moieties [bpy = 2,2′-bipyridine; Q′ = 3,5-di-tert-butyl-N-aryl-1,2-benzoquinonemonoimine, aryl = C6H5 (Q′1), 1; m-Cl2C6H3 (Q′2), 2; m-(OCH3)2C6H3 (Q′3), 3]. 1 and 3 have been preferentially stabilised in the cc-isomeric form while both the ct- and cc-isomeric forms of 2 are isolated [ct: cis and trans and cc: cis and cis with respect to the mutual orientations of O and N donors of two Q′]. The isomeric identities of 1–3 have been authenticated by their single-crystal X-ray structures. The collective consideration of crystallographic and DFT data along with other analytical events reveals that 1–3 exhibit the valence configuration of [(bpy)RuII(Q′Sq)2]. The magnetization studies reveal a ferromagnetic response at 300 K and virtual diamagnetic behaviour at 2 K. DFT calculations on representative 2a and 2b predict that the excited triplet (S = 1) state is lying close to the singlet (S = 0) ground state with singlet–triplet separation of 0.038 eV and 0.075 eV, respectively. In corroboration with the paramagnetic features the complexes exhibit free radical EPR signals with g [similar]2 and 1HNMR spectra with broad aromatic proton signals associated with the Q′ at 300 K. Experimental results in conjunction with the DFT (for representative 2a and 2b) reveal iminoquinone based preferential electron-transfer processes leaving the ruthenium(II) ion mostly as a redox insensitive entity: [(bpy)RuII(Q′Q)2]2+ (12+–32+) [leftrightharpoons] [(bpy)RuII(Q′Sq)(Q′Q)]+ (1+–3+) [leftrightharpoons] [(bpy)RuII(Q′Sq)2] (1–3) [leftrightharpoons] [(bpy)RuII(Q′Sq)(Q′Cat)]−/[(bpy)RuIII(Q′Cat)2]− (1−–3−). The diamagnetic doubly oxidised state, [(bpy)RuII(Q′Q)2]2+ in 12+–32+ has been authenticated further by the crystal structure determination of the representative [(bpy)RuII(Q′3)2](ClO4)2 [3](ClO4)2 as well as by its sharp 1H NMR spectrum. The key electronic transitions in each redox state of 1n–3n have been assigned by TD–DFT calculations on representative 2a and 2b

A supramolecular view on the cooperative role of Brønsted and Lewis acid sites in zeolites for methanol conversion

A systematic molecular level and spectroscopic investigation is presented to show the cooperative role of Bronsted acid and Lewis acid sites in zeolites for the conversion of methanol. Extra-framework alkaline-earth metal containing species and aluminum species decrease the number of Bronsted acid sites, as protonated metal clusters are formed. A combined experimental and theoretical effort shows that postsynthetically modified ZSM-5 zeolites, by incorporation of extra-framework alkaline-earth metals or by demetalation with dealuminating agents, contain both mononuclear [MOH](+) and double protonated binuclear metal clusters [M(mu-OH)(2)M](2+) (M = Mg, Ca, Sr, Ba, and HOAl). The metal in the extra-framework clusters has a Lewis acid character, which is confirmed experimentally and theoretically by IR spectra of adsorbed pyridine. The strength of the Lewis acid sites (Mg > Ca > Sr > Ba) was characterized by a blue shift of characteristic IR peaks, thus offering a tool to sample Lewis acidity experimentally. The incorporation of extra-framework Lewis acid sites has a substantial influence on the reactivity of propene and benzene methylations. Alkaline-earth Lewis acid sites yield increased benzene methylation barriers and destabilization of typical aromatic intermediates, whereas propene methylation routes are less affected. The effect on the catalytic function is especially induced by the double protonated binuclear species. Overall, the extra-framework metal clusters have a dual effect on the catalytic function. By reducing the number of Bronsted acid sites and suppressing typical catalytic reactions in which aromatics are involved, an optimal propene selectivity and increased lifetime for methanol conversion over zeolites is obtained. The combined experimental and theoretical approach gives a unique insight into the nature of the supramolecular zeolite catalyst for methanol conversion which can be meticulously tuned by subtle interplay of Bronsted and Lewis acid sites

Federated Benchmarking of Medical Artificial Intelligence With MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform

MedPerf : Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation

Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving provider and patient experience. We argue that unlocking this potential requires a systematic way to measure the performance of medical AI models on large-scale heterogeneous data. To meet this need, we are building MedPerf, an open framework for benchmarking machine learning in the medical domain. MedPerf will enable federated evaluation in which models are securely distributed to different facilities for evaluation, thereby empowering healthcare organizations to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status, and our roadmap. We call for researchers and organizations to join us in creating the MedPerf open benchmarking platform

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. METHODS: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. FINDINGS: Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. INTERPRETATION: As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe