Abstract: The recent advantages of the fabrication of artificial nanochannels enabled new research on the molecular transport, permeance, and selectivity of various gases and molecules. However, the physisorption/chemisorption of the unwanted molecules (usually hydrocarbons) inside nanochannels results in the alteration of the functionality of the nanochannels. We investigated contamination due to hydrocarbon molecules, nanochannels made of graphene, hexagonal boron nitride, BC2N, and molybdenum disulfide using molecular dynamics simulations. We found that for a certain size of nanochannel (i.e., h = 0.7 nm), as a result of the anomalous hydrophilic nature of nanochannels made of graphene, the hydrocarbons are fully adsorbed in the nanochannel, giving rise to full uptake. An increasing temperature plays an important role in unclogging, while pressure does not have a significant role. The results of our pioneering work contribute to a better understanding and highlight the important factors in alleviating the contamination and unclogging of nanochannels, which are in good agreement with the results of recent experiments.

Abstract: This study reports the low temperature and low pressure conversion (up to 160 °C, p = 3.5 bar) of CO2 and H2 to CO using plasmonic Au/TiO2 nanocatalysts and mildly concentrated artificial sunlight as the sole energy source (up to 13.9 kW·m-2 = 13.9 suns). To distinguish between photothermal and non-thermal contributors, we investigated the impact of the Au nanoparticle size and light intensity on the activity and selectivity of the catalyst. A comparative study between P25 TiO2-supported Au nanocatalysts of a size of 6 nm and 16 nm displayed a 15 times higher activity for the smaller particles, which can only partially be attributed to the higher Au surface area. Other factors that may play a role are e.g., the electronic contact between Au and TiO2 and the ratio between plasmonic absorption and scattering. Both catalysts displayed ≥84% selectivity for CO (side product is CH4). Furthermore, we demonstrated that the catalytic activity of Au/TiO2 increases exponentially with increasing light intensity, which indicated the presence of a photothermal contributor. In dark, however, both Au/TiO2 catalysts solely produced CH4 at the same catalyst bed temperature (160 °C). We propose that the difference in selectivity is caused by the promotion of CO desorption through charge transfer of plasmon generated charges (as a non-thermal contributor).

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: In this work, the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) submitted to an external magnetic field are studied using a Metropolis algorithm. The influence on the M(B) curves of the size distribution of the nanoparticles, of uniaxial anisotropy, and of dipolar interaction between the cores are examined, as well as the influence of drying the samples under a zero or non-zero magnetic field. It is shown that the anisotropy impacts the shape of the magnetization curves, which then deviate from a pure Langevin behaviour, whereas the dipolar interaction has no influence on the curves at 300 K for small particles (with a radius of 3 nm). The fitting of the magnetization curves of particles with magnetic anisotropy to a Langevin model (including a size distribution of the particles) can then lead to erroneous values of the distribution parameters. The simulation results are qualitatively compared to experimental results obtained for iron oxide nanoparticles (with a 3.21 nm median radius).

Abstract: Owing to its inherent non-trivial geometry, the unique structural motif of the recently discovered kagome topological superconductor AV(3)Sb(5) (A = K, Rb, Cs) is an ideal host of diverse topologically non-trivial phenomena, including giant anomalous Hall conductivity, topological charge order, charge density wave (CDW), and unconventional superconductivity. Despite possessing a normal-state CDW order in the form of topological chiral charge order and diverse superconducting gaps structures, it remains unclear how fundamental atomic-level properties and many-body effects including Fermi surface nesting, electron-phonon coupling, and orbital hybridization contribute to these symmetry-breaking phenomena. Here, the direct participation of the V3d-Sb5p orbital hybridization in mediating the CDW phase transition in CsV3Sb5 is reported. The combination of temperature-dependent X-ray absorption and first-principles studies clearly indicates the inverse Star-of-David structure as the preferred reconstruction in the low-temperature CDW phase. The results highlight the critical role that Sb orbitals play and establish orbital hybridization as the direct mediator of the CDW states and structural transition dynamics in kagome unconventional superconductors. This is a significant step toward the fundamental understanding and control of the emerging correlated phases from the kagome lattice through the orbital interactions and provides promising approaches to novel regimes in unconventional orders and topology.

Abstract: The Lamé curve is an extension of an ellipse, the latter being a special case. Dr. Johan Gielis further extended the Lamé curve in the polar coordinate system by introducing additional parameters (n1, n2, n3; m): rφ=1Acosm4φn2+1Bsinm4φn3−1/n1, which can be applied to model natural geometries. Here, r is the polar radius corresponding to the polar angle φ; A, B, n1, n2 and n3 are parameters to be estimated; m is the positive real number that determines the number of angles of the Gielis curve. Most prior studies on the Gielis equation focused mainly on its applications. However, the Gielis equation can also generate a large number of shapes that are rotationally symmetric and axisymmetric when A = B and n2 = n3, interrelated with the parameter m, with the parameters n1 and n2 determining the shapes of the curves. In this paper, we prove the relationship between m and the rotational symmetry and axial symmetry of the Gielis curve from a theoretical point of view with the condition A = B, n2 = n3. We also set n1 and n2 to take negative real numbers rather than only taking positive real numbers, then classify the curves based on extremal properties of r(φ) at φ = 0, π/m when n1 and n2 are in different intervals, and analyze how n1, n2 precisely affect the shapes of Gielis curves.

Abstract: For many decades, great efforts have been devoted to pursue a large piezoelectric response by an intelligent design of morphotropic phase boundaries (MPB) in solid solutions, where tetragonal (T) and rhombohedral (R) structures coexist. For example, classical PbZrxTi1-xO3 and Pb(Mg1/3Nb2/3)O-3-PbTiO3 single crystals demonstrate a giant piezoelectric response near MPB. However, as the end member of these solids, perovskite-structured PbTiO3 always adopts the T phase at room temperature. Here, we report a pathway to create room temperature MPB in a single-phase PbTiO3. The uniaxial stress along the c-axis drives a T-R phase transition bridged by a monoclinic (M) phase, which facilitates a polarization rotation in the monodomain PbTiO3. Meanwhile, we demonstrate that the coexistence of T and R phases at room temperature can be achieved via an extremely mismatched heterointerface system. The uniaxial pressure is proved as an efficient way to break the inherent symmetry and able to substantially tailor the phase transition temperature Tc. These findings provide new insights into MPB, offering the opportunity to explore the giant piezoelectric response in single-phase materials. (c) 2022 Elsevier Ltd. All rights reserved.

Abstract: The illicit drug precursor market for the manufacture of amphetamine-type stimulants (ATS), mainly amphetamine, methamphetamine and methylenedioxymethamphetamine (MDMA), has emerged quickly in the last years. The evidence of a more complex and sophisticated drug market underlines the pressing need for new on-site methods to quickly detect precursors of synthetic drugs, with electrochemical analysis as a promising technique. Herein, the electrochemical fingerprints of ten common ATS precursors-3-oxo-2-phenylbutanenitrile (APAAN), 3-oxo-2-phenylbutanamide (APAA), methyl 3-oxo-2-phenylbutanoate (MAPA), benzyl methyl ketone (BMK), 1-(1,3-benzodioxol-5-yl)propan-2-one (PMK), ephedrine, pseudoephedrine, safrole, sassafras oil and piperonal- are reported for the first time. The electrochemical screening disclosed the redox inactivity of BMK, which is an essential starting material for the production of ATS. Therefore, the local derivatization of BMK at an electrode surface by reductive amination is presented as a feasible solution to enrich its electrochemical fingerprint. To prove that, the resulting mixture was analyzed using a set of chromatographic techniques to understand the reaction mechanism and to identify possible electrochemical active products. Two reaction products (i.e. methamphetamine and 1-phenylpropan-2-ol) were found and characterized using mass spectrometry and electrochemical methods. Subsequently, the optimization of the reaction parameters was carefully addressed to set the portable electrochemical sensing strategy. Ultimately, the analysis concept was validated for the qualitative identification of ATS precursors in seizures from a forensic institute. Overall, the electrochemical approach demonstrates to be a useful and affordable analytical tool for the early identification of ATS precursors to prevent trafficking and drug manufacture in clandestine laboratories.

Abstract: Nanoporous membranes based on two dimensional materials are predicted to provide highly selective gas transport in combination with extreme permeance. Here we investigate membranes made from multilayer graphdiyne, a graphene-like crystal with a larger unit cell. Despite being nearly a hundred of nanometers thick, the membranes allow fast, Knudsen-type permeation of light gases such as helium and hydrogen whereas heavy noble gases like xenon exhibit strongly suppressed flows. Using isotope and cryogenic temperature measurements, the seemingly conflicting characteristics are explained by a high density of straight-through holes (direct porosity of similar to 0.1%), in which heavy atoms are adsorbed on the walls, partially blocking Knudsen flows. Our work offers important insights into intricate transport mechanisms playing a role at nanoscale.

Abstract: Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification. ,