Zinc oxide-aluminum oxide nanocomposite solid phase microextraction for diazepam and oxazepam trace determination.

A new efficient ZnO-Al2O3 nanocomposite (ZANC) was synthesized to form solid-phase microextraction (SPME) fiber. The prepared fiber was used for trace determination of benzodiazepines by gas chromatography-flame ionization detector in urine samples. The effective parameters on the extraction process including extraction time, salt percentage, desorption time and sample pH were optimized by a factorial design method. The method was evaluated at the optimum conditions and limits of detection (LODs) were calculated 20 µg/L for diazepam and oxazepam. The method repeatability for oxazepam and diazepam (50 µg/L, n = 4) was calculated at 8.8 % and 6.4 %. Also, the method reproducibility was obtained, 7.45 % and 6.61 % for oxazepam and diazepam (50 µg/L, n = 4). Also, fiber-to-fiber relative standard deviation (RSDs%) for the target analytes were less than 15.5 %. The method linearity is within the range of 62-500 µg/L for diazepam and oxazepam. The ZANC-SPME fiber showed a good lifetime (60 times) with high chemical stability. The high thermal stability of ZANC-SPME fiber was attained at 280 °C. The extraction results of poly dimethylsiloxan/divinyl benzene (PDMS/DVB) fiber were compared by ZANC-SPME fiber. Therefore, the method is proposed as a suitable technique for benzodiazepines detection in the urine sample.

High-throughput ab initio design of atomic interfaces using InterMatch.

Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for an optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe2. Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/α-RuCl3 by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed online.

Charge Density Wave Order and Electronic Phase Transitions in a Dilute d-Band Semiconductor.

As one of the most fundamental physical phenomena, charge density wave (CDW) order predominantly occurs in metallic systems such as quasi-1D metals, doped cuprates, and transition metal dichalcogenides, where it is well understood in terms of Fermi surface nesting and electron-phonon coupling mechanisms. On the other hand, CDW phenomena in semiconducting systems, particularly at the low carrier concentration limit, are less common and feature intricate characteristics, which often necessitate the exploration of novel mechanisms, such as electron-hole coupling or Mott physics, to explain. In this study, an approach combining electrical transport, synchrotron X-ray diffraction, and density-functional theory calculations is used to investigate CDW order and a series of hysteretic phase transitions in a dilute d-band semiconductor, BaTiS3 . These experimental and theoretical findings suggest that the observed CDW order and phase transitions in BaTiS3 may be attributed to both electron-phonon coupling and non-negligible electron-electron interactions in the system. This work highlights BaTiS3 as a unique platform to explore CDW physics and novel electronic phases in the dilute filling limit and opens new opportunities for developing novel electronic devices.

Quenched Excitons in WSe2/α-RuCl3 Heterostructures Revealed by Multimessenger Nanoscopy.

We investigate heterostructures composed of monolayer WSe2 stacked on α-RuCl3 using a combination of Terahertz (THz) and infrared (IR) nanospectroscopy and imaging, scanning tunneling spectroscopy (STS), and photoluminescence (PL). Our observations reveal itinerant carriers in the heterostructure prompted by charge transfer across the WSe2/α-RuCl3 interface. Local STS measurements show the Fermi level is shifted to the valence band edge of WSe2 which is consistent with p-type doping and verified by density functional theory (DFT) calculations. We observe prominent resonances in near-IR nano-optical and PL spectra, which are associated with the A-exciton of WSe2. We identify a concomitant, near total, quenching of the A-exciton resonance in the WSe2/α-RuCl3 heterostructure. Our nano-optical measurements show that the charge-transfer doping vanishes while excitonic resonances exhibit near-total recovery in "nanobubbles", where WSe2 and α-RuCl3 are separated by nanometer distances. Our broadband nanoinfrared inquiry elucidates local electrodynamics of excitons and an electron-hole plasma in the WSe2/α-RuCl3 system.

Machine Learning for Optical Scanning Probe Nanoscopy.

The ability to perform nanometer-scale optical imaging and spectroscopy is key to deciphering the low-energy effects in quantum materials, as well as vibrational fingerprints in planetary and extraterrestrial particles, catalytic substances, and aqueous biological samples. These tasks can be accomplished by the scattering-type scanning near-field optical microscopy (s-SNOM) technique that has recently spread to many research fields and enabled notable discoveries. Herein, it is shown that the s-SNOM, together with scanning probe research in general, can benefit in many ways from artificial-intelligence (AI) and machine-learning (ML) algorithms. Augmented with AI- and ML-enhanced data acquisition and analysis, scanning probe optical nanoscopy is poised to become more efficient, accurate, and intelligent.

Ultralocalized Optoelectronic Properties of Nanobubbles in 2D Semiconductors.

The optical properties of transition-metal dichalcogenides have previously been modified at the nanoscale by using mechanical and electrical nanostructuring. However, a clear experimental picture relating the local electronic structure with emission properties in such structures has so far been lacking. Here, we use a combination of scanning tunneling microscopy (STM) and near-field photoluminescence (nano-PL) to probe the electronic and optical properties of single nanobubbles in bilayer heterostructures of WSe2 on MoSe2. We show from tunneling spectroscopy that there are electronic states deeply localized in the gap at the edge of such bubbles, which are independent of the presence of chemical defects in the layers. We also show a significant change in the local band gap on the bubble, with a continuous evolution to the edge of the bubble over a length scale of ∼20 nm. Nano-PL measurements observe a continuous redshift of the interlayer exciton on entering the bubble, in agreement with the band-to-band transitions measured by STM. We use self-consistent Schrödinger-Poisson simulations to capture the essence of the experimental results and find that strong doping in the bubble region is a key ingredient to achieving the observed localized states, together with mechanical strain.

Coupling between magnetic order and charge transport in a two-dimensional magnetic semiconductor.

Semiconductors, featuring tunable electrical transport, and magnets, featuring tunable spin configurations, form the basis of many information technologies. A long-standing challenge has been to realize materials that integrate and connect these two distinct properties. Two-dimensional (2D) materials offer a platform to realize this concept, but known 2D magnetic semiconductors are electrically insulating in their magnetic phase. Here we demonstrate tunable electron transport within the magnetic phase of the 2D semiconductor CrSBr and reveal strong coupling between its magnetic order and charge transport. This provides an opportunity to characterize the layer-dependent magnetic order of CrSBr down to the monolayer via magnetotransport. Exploiting the sensitivity of magnetoresistance to magnetic order, we uncover a second regime characterized by coupling between charge carriers and magnetic defects. The magnetoresistance within this regime can be dynamically and reversibly tuned by varying the carrier concentration using an electrostatic gate, providing a mechanism for controlling charge transport in 2D magnets.

Nanometer-Scale Lateral p-n Junctions in Graphene/α-RuCl3 Heterostructures.

The ability to create nanometer-scale lateral p-n junctions is essential for the next generation of two-dimensional (2D) devices. Using the charge-transfer heterostructure graphene/α-RuCl3, we realize nanoscale lateral p-n junctions in the vicinity of graphene nanobubbles. Our multipronged experimental approach incorporates scanning tunneling microscopy (STM) and spectroscopy (STS) and scattering-type scanning near-field optical microscopy (s-SNOM) to simultaneously probe the electronic and optical responses of nanobubble p-n junctions. Our STM/STS results reveal that p-n junctions with a band offset of ∼0.6 eV can be achieved with widths of ∼3 nm, giving rise to electric fields of order 108 V/m. Concurrent s-SNOM measurements validate a point-scatterer formalism for modeling the interaction of surface plasmon polaritons (SPPs) with nanobubbles. Ab initio density functional theory (DFT) calculations corroborate our experimental data and reveal the dependence of charge transfer on layer separation. Our study provides experimental and conceptual foundations for generating p-n nanojunctions in 2D materials.

Nano-spectroscopy of excitons in atomically thin transition metal dichalcogenides.

Excitons play a dominant role in the optoelectronic properties of atomically thin van der Waals (vdW) semiconductors. These excitons are amenable to on-demand engineering with diverse control knobs, including dielectric screening, interlayer hybridization, and moiré potentials. However, external stimuli frequently yield heterogeneous excitonic responses at the nano- and meso-scales, making their spatial characterization with conventional diffraction-limited optics a formidable task. Here, we use a scattering-type scanning near-field optical microscope (s-SNOM) to acquire exciton spectra in atomically thin transition metal dichalcogenide microcrystals with previously unattainable 20 nm resolution. Our nano-optical data revealed material- and stacking-dependent exciton spectra of MoSe2, WSe2, and their heterostructures. Furthermore, we extracted the complex dielectric function of these prototypical vdW semiconductors. s-SNOM hyperspectral images uncovered how the dielectric screening modifies excitons at length scales as short as few nanometers. This work paves the way towards understanding and manipulation of excitons in atomically thin layers at the nanoscale.

Extracting the Strain Matrix and Twist Angle from the Moiré Superlattice in van der Waals Heterostructures.

When two atomic layers are brought into contact at a relative twist angle, a large-scale pattern, called a moiré superlattice, emerges due to the (angular or lattice) mismatch between the layers. This has profound consequences in terms of the Hamiltonian of the system but was also considered in several publications as a means to extract the local strain tensor. While extracting the twist angle based on knowledge of the periodicity of the moiré is trivial in the case of a regular moiré pattern, in many examples in the literature, that is not the case. In particular, extracting the strain tensor and twist angle maps from a spatially varying moiré pattern is not straightforward. This article aims to provide a practical tool to extract the strain tensor and twist angle from an experimentally observable pattern. It further addresses the limitation of any such approach in the absence of additional experimental information beyond the moiré superlattice pattern.

Deep Learning Analysis of Polaritonic Wave Images.

Deep learning (DL) is an emerging analysis tool across the sciences and engineering. Encouraged by the successes of DL in revealing quantitative trends in massive imaging data, we applied this approach to nanoscale deeply subdiffractional images of propagating polaritonic waves in complex materials. Utilizing the convolutional neural network (CNN), we developed a practical protocol for the rapid regression of images that quantifies the wavelength and the quality factor of polaritonic waves. Using simulated near-field images as training data, the CNN can be made to simultaneously extract polaritonic characteristics and material parameters in a time scale that is at least 3 orders of magnitude faster than common fitting/processing procedures. The CNN-based analysis was validated by examining the experimental near-field images of charge-transfer plasmon polaritons at graphene/α-RuCl3 interfaces. Our work provides a general framework for extracting quantitative information from images generated with a variety of scanning probe methods.

Moiré metrology of energy landscapes in van der Waals heterostructures.

The emerging field of twistronics, which harnesses the twist angle between two-dimensional materials, represents a promising route for the design of quantum materials, as the twist-angle-induced superlattices offer means to control topology and strong correlations. At the small twist limit, and particularly under strain, as atomic relaxation prevails, the emergent moiré superlattice encodes elusive insights into the local interlayer interaction. Here we introduce moiré metrology as a combined experiment-theory framework to probe the stacking energy landscape of bilayer structures at the 0.1 meV/atom scale, outperforming the gold-standard of quantum chemistry. Through studying the shapes of moiré domains with numerous nano-imaging techniques, and correlating with multi-scale modelling, we assess and refine first-principle models for the interlayer interaction. We document the prowess of moiré metrology for three representative twisted systems: bilayer graphene, double bilayer graphene and H-stacked MoSe2/WSe2. Moiré metrology establishes sought after experimental benchmarks for interlayer interaction, thus enabling accurate modelling of twisted multilayers.

Relationship of serum serotonin and salivary cortisol with sensation seeking.

The present study was conducted to investigate the possible relationship of serum serotonin and salivary cortisol with the sensation seeking (SS) trait. Blood and saliva samples were taken from 57 male volunteers (mean age 23±5years) to measure serum serotonin and salivary cortisol concentrations. Zuckerman's Sensation Seeking Scale (SSS-V) was used to assess SS. Pearson's correlation coefficient revealed that high serum serotonin levels did not correlate significantly with low SS scores (r=0.12). However, a negative correlation between SS scores and salivary cortisol levels (r=-0.34, p<0.01) was significant, suggesting that high SS scores are related to low concentrations of salivary cortisol. The negative correlation between salivary cortisol and SS is clearly compatible with the optimal level of Catecholamine system activity (CSA), component of SS theory, indicating that high sensation seekers (HSSers) tend to seek excitement and novelty to compensate for the shortage of CSA achieving optimal arousal. Further investigation is needed before conclusions can be drawn regarding the relationship of serum serotonin and SS.

CD40ligand-expressing dendritic cells induce regression of hepatocellular carcinoma by activating innate and acquired immunity in vivo.

UNLABELLED: Dendritic cells (DCs) are professional antigen-presenting cells able to prime T-cells against tumor-associated antigens (TAA), but their potential to induce hepatocellular carcinoma (HCC) regression is still limited. CD40/CD40L interaction is essential for DC activation and induction of antigen-specific T-cells. In this study, transduction of TAA-pulsed DC with a CD40L-encoding adenovirus (Ad-CD40L) was used to improve the immune response induced by DC toward HCC. Bone marrow-derived DC from C3H/HeNcrl mice were cultured with granulocyte-macrophage colony-stimulating factor and interleukin-4. On day 6, tumor-lysate pulsed DCs were infected with adenoviruses. HCCs were induced by inoculation of mice with Hepa129-cells subcutaneously. When tumor-volume was 100 to 400 mm(3), DCs were injected intratumorally, subcutaneously, or intravenously. Ad-CD40L transduction exerted CD40/CD40L interactions between DCs, increasing DC immunostimulation with up-regulation of CD80/CD86- and interleukin-12 (IL-12) expression. Intratumoral injection of CD40L-DC was superior to intravenous or subcutaneous treatments, yielding tumor elimination in almost 70% of mice. Moreover, all tumor-free animals were protected against hepatic tumor cell rechallenge. In a preventive setting, subcutaneous injection of CD40L-expressing DCs protected 50% of mice for more than 3 months toward tumor cell challenge. The induced immune response seemed to be dependent on cross-priming with Th1-lymphocytes in the lymph nodes, because transduced DCs were redetected in lymphoid tissues. In addition, immunohistochemistry of tumors indicated a significant tumor infiltration with CD4+, CD8+ T cells and natural killer (NK) cells. Tumor-infiltrating lymphocytes were tumor-specific, as shown in interferon-gamma (IFN-gamma) enzyme-linked immunosorbent spot and T-cell proliferation assays. CONCLUSION: Transduction of DCs with Ad-CD40L increases significantly the stimulatory capacity of DCs. Intratumoral injection of DCs activates both acquired and innate immunity, inducing complete regression of established tumors and long-term immunity against tumor recurrence. This approach improves the antitumoral potential of DCs.