A study on the stability of carbon nanoforms–polyimidazolium network hybrids in the conversion of co2 into cyclic carbonates: Increase in catalytic activity after reuse

Three different carbon nanoforms (CNFs), single-walled and multi-walled carbon nanotubes (SWCNTs, MWCNTs) and carbon nanohorns (CNHs), have been used as supports for the direct polymerization of variable amounts of a bis-vinylimidazolium salt. Transmission electron microscopy confirmed that all CNFs act as templates on the growth of the polymeric network, which perfectly covers the nanocarbons forming a cylindrical (SWCNTs, MWCNTs) or spherical (CNHs) coating. The stability of these hybrid materials was investigated in the conversion of CO2 into cyclic carbonate under high temperature and CO2 pressure. Compared with the homopolymerized monomer, nanotube-based materials display an improved catalytic activity. Beside the low catalytic loading (0.05–0.09 mol%) and the absence of Lewis acid co-catalysts, all the materials showed high TON values (up to 1154 for epichlorohydrin with SW-1:2). Interestingly, despite the loss of part of the polymeric coating for crumbling or peeling, the activity increases upon recycling of the materials, and this behaviour was ascribed to their change in morphology, which led to materials with higher surface areas and with more accessible catalytic sites. Transmission electron microscopy analysis, along with different experiments, have been carried out in order to elucidate these findings

Iridium-Functionalized Cellulose Microcrystals as a Novel Luminescent Biomaterial for Biocomposites

Microcrystalline cellulose (MCC) is an emerging material with outstanding properties in many scientific and industrial fields, in particular as an additive in composite materials. Its surface modification allows for the fine-tuning of its properties and the exploitation of these materials in a plethora of applications. In this paper, we present the covalent linkage of a luminescent Ir-complex onto the surface of MCC, representing the first incorporation of an organometallic luminescent probe in this biomaterial. This goal has been achieved with an easy and sustainable procedure, which employs a Bronsted-acid ionic liquid as a catalyst for the esterification reaction of -OH cellulose surface groups. The obtained luminescent cellulose microcrystals display high and stable emissions with the incorporation of only a small amount of iridium (III). Incorporation of MCC-Ir in dry and wet matrices, such as films and gels, has been also demonstrated, showing the maintenance of the luminescent properties even in possible final manufacturers

Diastereoselective additions of organometallic reagents to (SFc)-2-p-tolylsulfanylferrocene carboxyaldehyde and to (SFc)-2-p-tolylsulfanyl ferrocenyl imines. Synthesis of new central and planar chiral ferrocenyl alcohols and amines

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Itaconic-Acid-Based Sustainable Poly(ester amide) Resin for Stereolithography

Material science is recognized as a frontrunner in achieving a sustainable future, owing to its primary reliance upon petroleum-based chemical raw materials. Several efforts are made to implement common renewable feedstocks as an alternative to common fossil resources. For this purpose, additive manufacturing (AM) represents promising and effective know-how for the replacement of high energy- and resource-demanding processes with more environmentally friendly practices. This work presents a novel biobased ink for stereolithography, which has been formulated by mixing a photocurable poly(ester amide) (PEA) obtained from renewable resources with citrate and itaconate cross-linkers and appropriate photopolymerization initiators, terminators, and dyes. The mechanical features and the relative biocompatibility of 3D-printed objects have been carefully studied to evaluate the possible resin implementation in the field of the textile fashion industry

Reduced salivary oxytocin after an empathic induction task in Intimate Partner Violence perpetrators: Importance of socio-affective functions and its impact on prosocial behavior

Intimate Partner Violence (IPV) has been linked to difficulties in socio-affective functions. Nevertheless, the underlying psychobiological mechanisms that might be responsible for them remain unclear. Oxytocin (OXT) stands out as an important hormone that may favor the salience of social information, due to its relevance in empathy and prosocial behavior. Thus, the study of salivary OXT (sOXT) may provide further information about potential impairments in social cognition in IPV perpetrators. This study analyzed the effects of an empathic induction task, performed through negative emotion-eliciting videos, on endogenous sOXT levels, mood state, and emotional perception in 30 IPV perpetrators compared to 32 controls. Additionally, we explored their performance on prosocial behavior after the empathic induction task, using Hare''s donation procedure. Lower sOXT levels were found in IPV perpetrators after the task compared to controls, along with a general decreasing tendency in their sOXT levels. Additionally, IPV perpetrators exhibited no change in their mood state and perceived others'' emotions as more positive and less intense. Moreover, the mood state response and alexithymia traits, respectively, positively and negatively predicted the sOXT levels after the empathic induction task in the entire sample. Finally, we did not observe a lower appearance of prosocial behaviors in IPV perpetrators; however, higher sOXT levels after the empathic induction task were found in subjects who donated when considering the whole sample. In sum, IPV perpetrators exhibited differences in their sOXT levels when empa-thizing, compared to controls, with alexithymia and the emotional response potentially explaining the sOXT levels after the task. Furthermore, prosocial behavior was more related to these sOXT levels than to IPV. As our knowledge about the emotional processing of IPV perpetrators increases, we will be better able to develop and include coadjutant treatments in current psychotherapeutic programs, in order to focus on their emotional needs, which, in turn, would reduce the future risk of recidivism

Deep-Manager: a versatile tool for optimal feature selection in live-cell imaging analysis

One of the major problems in bioimaging, often highly underestimated, is whether features extracted for a discrimination or regression task will remain valid for a broader set of similar experiments or in the presence of unpredictable perturbations during the image acquisition process. Such an issue is even more important when it is addressed in the context of deep learning features due to the lack of a priori known relationship between the black-box descriptors (deep features) and the phenotypic properties of the biological entities under study. In this regard, the widespread use of descriptors, such as those coming from pre-trained Convolutional Neural Networks (CNNs), is hindered by the fact that they are devoid of apparent physical meaning and strongly subjected to unspecific biases, i.e., features that do not depend on the cell phenotypes, but rather on acquisition artifacts, such as brightness or texture changes, focus shifts, autofluorescence or photobleaching. The proposed Deep-Manager software platform offers the possibility to efficiently select those features having lower sensitivity to unspecific disturbances and, at the same time, a high discriminating power. Deep-Manager can be used in the context of both handcrafted and deep features. The unprecedented performances of the method are proven using five different case studies, ranging from selecting handcrafted green fluorescence protein intensity features in chemotherapy-related breast cancer cell death investigation to addressing problems related to the context of Deep Transfer Learning. Deep-Manager, freely available at https://github.com/BEEuniroma2/Deep-Manager, is suitable for use in many fields of bioimaging and is conceived to be constantly upgraded with novel image acquisition perturbations and modalities

Comparison of the Electronic Structures and Energetics of Ferroelectric LiNbO3 and LiTaO3

This paper explains the origin of the ferroelectric instability in LiNbO3 and LiTaO3 and compares the electronic structures and energetics of the two materials.Comment: 31 pages, 11 Postscript figure

Interface properties and built-in potential profile of a LaCr O3/SrTi O3 superlattice determined by standing-wave excited photoemission spectroscopy

LaCrO3(LCO)/SrTiO3(STO) heterojunctions are intriguing due to a polar discontinuity along [001], exhibiting two distinct and controllable charged interface structures [(LaO)+/(TiO2)0 and (SrO)0/(CrO2)-] with induced polarization, and a resulting depth-dependent potential. In this study, we have used soft- and hard-x-ray standing-wave excited photoemission spectroscopy (SW-XPS) to quantitatively determine the elemental depth profile, interface properties, and depth distribution of the polarization-induced built-in potentials. We observe an alternating charged interface configuration: a positively charged (LaO)+/(TiO2)0 intermediate layer at the LCOtop/STObottom interface and a negatively charged (SrO)0/(CrO2)- intermediate layer at the STOtop/LCObottom interface. Using core-level SW data, we have determined the depth distribution of species, including through the interfaces, and these results are in excellent agreement with scanning transmission electron microscopy and electron energy-loss spectroscopy mapping of local structure and composition. SW-XPS also enabled deconvolution of the LCO and STO contributions to the valence-band (VB) spectra. Using a two-step analytical approach involving first SW-induced core-level binding-energy shifts and then VB modeling, the variation in potential across the complete superlattice is determined in detail. This potential is in excellent agreement with density functional theory models, confirming this method as a generally useful tool for interface studies

Mapping the depleted area of silicon diodes using a micro-focused X-ray beam

For the Phase-II Upgrade of the ATLAS detector at CERN, the current ATLAS Inner Detector will be replaced with the ATLAS Inner Tracker (ITk). The ITk will be an all-silicon detector, consisting of a pixel tracker and a strip tracker. Sensors for the ITk strip tracker are required to have a low leakage current up to bias voltages of -500 V to maintain a low noise and power dissipation. In order to minimise sensor leakage currents, particularly in the high-radiation environment inside the ATLAS detector, sensors are foreseen to be operated at low temperatures and to be manufactured from wafers with a high bulk resistivity of several kΩ·cm. Simulations showed the electric field inside sensors with high bulk resistivity to extend towards the sensor edge, which could lead to increased surface currents for narrow dicing edges. In order to map the electric field inside biased silicon sensors with high bulk resistivity, three diodes from ATLAS silicon strip sensor prototype wafers were studied with a monochromatic, micro-focused X-ray beam at the Diamond Light Source (Didcot, U.K.). For all devices under investigation, the electric field inside the diode was mapped and its dependence on the applied bias voltage was studied.Individual authors1 were supported in part by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The work at SCIPP4 was supported by the Department of Energy, grant DE-SC0010107. This work5 issupported and financed in part by the Spanish Ministry of Science, Innovation and Universities through the Particle Physics National Program, ref. FPA2015-65652-C4-4-R (MICINN/FEDER, UE), and co-financed with FEDER funds