Jet-loaded cold atomic beam source for strontium.

We report on the design and characterization of a cold atom source for strontium (Sr) based on a two-dimensional magneto-optical trap (MOT) that is directly loaded from the atom jet of a dispenser. We characterize the atom flux of the source by measuring the loading rate of a three-dimensional MOT. We find loading rates of up to 108 atoms per second. The setup is compact, easy to construct, and has low power consumption. It addresses the longstanding challenge of reducing the complexity of cold beam sources for Sr, which is relevant for optical atomic clocks, quantum simulation, and computing devices based on ultracold Sr.

Enzyme Nanosheet-Based Electrochemical Aspartate Biosensor for Fish Point-of-Care Applications.

Bacterial infections in marine fishes are linked to mass mortality issues; hence, rapid detection of an infection can contribute to achieving a faster diagnosis using point-of-care testing. There has been substantial interest in identifying diagnostic biomarkers that can be detected in major organs to predict bacterial infections. Aspartate was identified as an important biomarker for bacterial infection diagnosis in olive flounder (Paralichthys olivaceus) fish. To determine aspartate levels, an amperometric biosensor was designed based on bi-enzymes, namely, glutamate oxidase (GluOx) and aspartate transaminase (AST), which were physisorbed on copolymer reduced graphene oxide (P-rGO), referred to as enzyme nanosheets (GluOx-ASTENs). The GluOx-ASTENs were drop casted onto a Prussian blue electrodeposited screen-printed carbon electrode (PB/SPCE). The proposed biosensor was optimized by operating variables including the enzyme loading amount, coreactant (α-ketoglutarate) concentration, and pH. Under optimal conditions, the biosensor displayed the maximum current responses within 10 s at the low applied potential of -0.10 V vs. the internal Ag/AgCl reference. The biosensor exhibited a linear response from 1.0 to 2.0 mM of aspartate concentrations with a sensitivity of 0.8 µA mM-1 cm-2 and a lower detection limit of approximately 500 µM. Moreover, the biosensor possessed high reproducibility, good selectivity, and efficient storage stability.

Organic Dispersion of Mo3Se3- Single-Chain Atomic Crystals Using Surface Modification Methods.

In this study, single-chain atomic crystals (SCACs), Mo3Se3-, which can be uniformly dispersed, with an atomically thin diameter of ∼0.6 nm were modified to disperse in an organic solvent. Various surfactants were chosen to provide steric hindrance to aqueous-dispersed Mo3Se3- by modifying the surface of Mo3Se3-. The organic dispersions of surface-modified Mo3Se3- SCACs in nonpolar solvent (toluene, benzene, and chloroform) were stable with a uniform diameter of 2 nm, and they have enhanced stability from oxidation (>10 days). With the surfactants that have a polystyrene tail group (PS-NH2), the surface-modified Mo3Se3- SCAC showed high compatibility with a polystyrene polymer matrix. Using the surface-modified Mo3Se3- SCAC, a homogeneous Mo3Se3-/polystyrene/toluene organogel was prepared. More importantly, the Mo3Se3-/polystyrene organogel exhibits significantly enhanced mechanical properties, with the improvement of 202.27% and 279.52% for tensile strength and elongation, respectively, compared with that of the pure organogel. The surface-modified Mo3Se3- had a similar structure with a polymer matrix, and the properties of the polymer can be improved even with a small addition of Mo3Se3-.

Spatiotemporal neural network with attention mechanism for El Niño forecasts.

To learn spatiotemporal representations and anomaly predictions from geophysical data, we propose STANet, a spatiotemporal neural network with a trainable attention mechanism, and apply it to El Niño predictions for long-lead forecasts. The STANet makes two critical architectural improvements: it learns spatial features globally by expanding the network's receptive field and encodes long-term sequential features with visual attention using a stateful long-short term memory network. The STANet conducts multitask learning of Nino3.4 index prediction and calendar month classification for predicted indices. In a comparison of the proposed STANet performance with the state-of-the-art model, the accuracy of the 12-month forecast lead correlation coefficient was improved by 5.8% and 13% for Nino3.4 index prediction and corresponding temporal classification, respectively. Furthermore, the spatially attentive regions for the strong El Niño events displayed spatial relationships consistent with the revealed precursor for El Niño occurrence, indicating that the proposed STANet provides good understanding of the spatiotemporal behavior of global sea surface temperature and oceanic heat content for El Niño evolution.

Screen-printed carbon electrode modified with de-bundled single-walled carbon nanotubes for voltammetric determination of norepinephrine in ex vivo rat tissue.

A voltammetric sensor for norepinephrine (NE) detection was developed by modifying a disposable screen-printed carbon electrode (SPCE) with de-bundled single-walled carbon nanotubes (D-SWCNTs). The de-bundling was carried out using a newly synthesized polymeric dispersant, a co-polymer of polystyrene sulfonate and methacrylate of lipoic acid. The D-SWCNTs/SPCE showed better sensitivity towards NE compared to the bare SPCE and that modified with bundled SWCNTs. The sensor was optimized for detecting NE by differential pulse voltammetry (DPV) in terms of the D-SWCNTs concentration, DPV parameters, and solution pH. Under the optimum conditions, the sensor exhibited a dynamic linear range of 100 nM-2.0 µM NE, and the detection limit was 62.0 nM (S/N = 3). Additionally, the effects of possible interferents were investigated. The relative standard deviation for five successive measurements of 2.0 µM NE was 7.6%, and approximately 75.8% of the sensor activity was retained after four weeks of storage. The practical potential of this sensor was demonstrated by quantifying NE in ex vivo rat tissue samples.

Robust Nanozyme-Enzyme Nanosheets-Based Lactate Biosensor for Diagnosing Bacterial Infection in Olive Flounder (Paralichthys olivaceus).

Bacterial infections in fish farms increase mass mortality and rapid detection of infection can help prevent its widespread. Lactate is an important biomarker for early diagnosis of bacterial infections in farmed olive flounder (Paralichthys olivaceus). To determine the lactate levels, we designed a disposable amperometric biosensor based on Prussian blue nanozyme and lactate oxidase (LOX) entrapped in copolymer-reduced graphene oxide (P-rGO) on screen-printed carbon electrodes. Because LOX is inherently unstable, P-rGO nanosheets were utilized as a base matrix to immobilize it. After optimization in terms of enzyme loading, operating potential, and pH, the biosensor displayed maximum current responses within 5 s at the applied potential of -0.1 V vs. internal Ag/AgCl. The biosensor had Langmuir-type response in the lactate concentration range from 10 µM to 1.6 mM, a dynamic linear response range of 10-100 µM, a sensitivity of 15.9 µA mM-1 cm-2, and a lower detection limit of 3.1 µM (S/N = 3). Additionally, the biosensor featured high reproducibility, good selectivity, and stability till four weeks. Its practical applicability was tested in olive flounder infected by Streptococcus parauberis against the uninfected control. The results were satisfactory compared to those of a standard colorimetric assay kit, validating our method.

Controlling Graphene Wrinkles through the Phase Transition of a Polymer with a Low Critical Solution Temperature.

A novel method for controlling reduced graphene oxide (rGO) wrinkles through a phase transition in a solution using a low critical solution temperature (LCST) polymer dispersant has been developed. The polymer dispersant is designed by control of architecture and composition using reversible addition-fragmentation chain transfer polymerization. Synthesized poly(2-(dimethylaminoethyl) methacrylate-block-styrene) (PDbS) can be successfully functionalized on the rGO surface via noncovalent functionalization. PDbS-functionalized rGO (PDbS-rGO) exhibits good dispersibility in an aqueous phase at room temperature and forms wrinkles on the PDbS-rGO surface because of phase transition at the LCST of the polymer dispersant. The formation of PDbS-rGO wrinkles is controlled by varying the aggregation number of the polymer dispersant on the PDbS-rGO surface that strongly depends on temperature. This is confirmed by transmission electron microscopy, scanning electron microscopy, and Raman spectroscopy (ID' /IG ratios are 0.560, 0.579, and 0.684, which correspond to 45, 70, and 95 °C, respectively). In addition, the mechanism of wrinkle control is proved by gold nanoparticles that are grown in polymer dispersant on the PDbS-rGO surface.

Disposable Voltammetric Sensor Modified with Block Copolymer-Dispersed Graphene for Simultaneous Determination of Dopamine and Ascorbic Acid in Ex Vivo Mouse Brain Tissue.

Dopamine (DA) and ascorbic acid (AA) are two important biomarkers with similar oxidation potentials. To facilitate their simultaneous electrochemical detection, a new voltammetric sensor was developed by modifying a screen-printed carbon electrode (SPCE) with a newly synthesized block copolymer (poly(DMAEMA-b-styrene), PDbS) as a dispersant for reduced graphene oxide (rGO). The prepared PDbS-rGO and the modified SPCE were characterized using a range of physical and electrochemical techniques including Raman spectroscopy, scanning electron microscopy, transmission electron microscopy, cyclic voltammetry, electrochemical impedance spectroscopy, and linear sweep voltammetry. Compared to the bare SPCE, the PDbS-rGO-modified SPCE (PDbS-rGO/SPCE) showed better sensitivity and peak-to-peak separation for DA and AA in mixed solutions. Under the optimum conditions, the dynamic linear ranges for DA and AA were 0.1-300 and 10-1100 µM, and the detection limits were 0.134 and 0.88 µM (S/N = 3), respectively. Furthermore, PDbS-rGO/SPCE exhibited considerably enhanced anti-interference capability, high reproducibility, and storage stability for four weeks. The practical potential of the PDbS-rGO/SPCE sensor for measuring DA and AA was demonstrated using ex vivo brain tissues from a Parkinson's disease mouse model and the control.

Segmented Polyurethanes and Thermoplastic Elastomers from Elemental Sulfur with Enhanced Thermomechanical Properties and Flame Retardancy.

The production of elemental sulfur from petroleum refining has created a technological opportunity to increase the valorization of elemental sulfur by the creation of high-performance sulfur based plastics with improved thermomechanical properties, elasticity and flame retardancy. We report on a synthetic polymerization methodology to prepare the first example of sulfur based segmented multi-block polyurethanes (SPUs) and thermoplastic elastomers that incorporate an appreciable amount of sulfur into the final target material. This approach applied both the inverse vulcanization of S8 with olefinic alcohols and dynamic covalent polymerizations with dienes to prepare sulfur polyols and terpolyols that were used in polymerizations with aromatic diisocyanates and short chain diols. Using these methods, a new class of high molecular weight, soluble block copolymer polyurethanes were prepared as confirmed by Size Exclusion Chromatography, NMR spectroscopy, thermal analysis, and microscopic imaging. These sulfur-based polyurethanes were readily solution processed into large area free standing films where both the tensile strength and elasticity of these materials were controlled by variation of the sulfur polyol composition. SPUs with both high tensile strength (13-24 MPa) and ductility (348 % strain at break) were prepared, along with SPU thermoplastic elastomers (578 % strain at break) which are comparable values to classical thermoplastic polyurethanes (TPUs). The incorporation of sulfur into these polyurethanes enhanced flame retardancy in comparison to classical TPUs, which points to the opportunity to impart new properties to polymeric materials as a consequence of using elemental sulfur.

Polymer-dispersed reduced graphene oxide nanosheets and Prussian blue modified biosensor for amperometric detection of sarcosine.

A new disposable amperometric biosensor for sarcosine (Sar, a biomarker for prostate cancer) was designed based on screen-printed carbon electrodes, Prussian blue, polymer dispersed reduced graphene oxide (P-rGO) nanosheets, and sarcosine oxidase (SOx). Poly(sodium 4-styrenesulfonate-r-LAHEMA) denoted as PSSL was newly synthesized as dispersant for rGO. The P-rGO was utilized for SOx immobilization, the sulfonate and disulfide functionalities in PSSL enable physical adsorption of SOx and its bioactivity and stability properties were improved. The biosensor was optimized by various enzyme concentration, applied potential, and operating pH. Under the optimized conditions, the biosensor exhibited maximum current responses within 5 s at an applied potential of -0.1 V vs. integrated Ag/AgCl reference electrode. The biosensor had a dynamic linear range of 10-400 µM, with a sensitivity of 9.04 µA mM-1 cm-2 and a low detection limit of 0.66 µM (S/N = 3). Additionally, the biosensor possesses strong anti-interference capability, high reproducibility, and storage stability over 3 weeks. Furthermore, its clinical applicability was tested in urine samples from both prostate cancer patients and healthy control, and the analytical recoveries were satisfactory. Therefore, this biosensor has significant potential in the rapid and non-invasive point-of-care testing for prostate cancer diagnosis.

EXPAREL® (Long-Acting Liposomal Bupivacaine) Use for Popliteal Nerve Block in Postoperative Pain Control after Ankle Fracture Fixation.

EXPAREL® has been used successfully to prolong postoperative pain control when applied as a wound infiltrate. EXPAREL® has not yet been approved for use in regional anesthesia to prolong postoperative pain control. We conducted a clinical case series of 4 patients using EXPAREL® for sciatic blocks via the popliteal fossa approach. Our results suggested that there is a large degree of variability in response to the medication. These inconsistent results and the possibility of bimodal kinetics creating analgesic gaps as seen in two of our patients indicate that more studies with larger sample size are needed to better characterize these phenomena and determine if more consistent results can be obtained in a future clinical trial.

Polymer wrapping-induced dispersion of single walled carbon nanotubes in ethylene glycol under mild sonication.

SWCNTs were individually dispersed in ethylne glycol (EG) via mild bath-type sonication using quaternized poly(furfuryl methacrylate)-co-(2-(dimethylamino)ethyl methacrylate) p(FMA-co-QDMAEMA) as a dispersing agent. QDMAEMA, which has alkyl groups, was more favorable to the dispersion ability of single walled carbon nanotubes (SWCNTs). The dispersion mechanism of SWCNTs in EG via helical wrapping of polymer chains along their sidewalls was suggested based on transmission electron microscopic observation.

Parallel Low-Loss Measurement of Multiple Atomic Qubits.

We demonstrate low-loss measurement of the hyperfine ground state of rubidium atoms by state dependent fluorescence detection in a dipole trap array of five sites. The presence of atoms and their internal states are minimally altered by utilizing circularly polarized probe light and a strictly controlled quantization axis. We achieve mean state detection fidelity of 97% without correcting for imperfect state preparation or background losses, and 98.7% when corrected. After state detection and correction for background losses, the probability of atom loss due to the state measurement is <2% and the initial hyperfine state is preserved with >98% probability.

Amplified Arctic warming by phytoplankton under greenhouse warming.

Phytoplankton have attracted increasing attention in climate science due to their impacts on climate systems. A new generation of climate models can now provide estimates of future climate change, considering the biological feedbacks through the development of the coupled physical-ecosystem model. Here we present the geophysical impact of phytoplankton, which is often overlooked in future climate projections. A suite of future warming experiments using a fully coupled ocean-atmosphere model that interacts with a marine ecosystem model reveals that the future phytoplankton change influenced by greenhouse warming can amplify Arctic surface warming considerably. The warming-induced sea ice melting and the corresponding increase in shortwave radiation penetrating into the ocean both result in a longer phytoplankton growing season in the Arctic. In turn, the increase in Arctic phytoplankton warms the ocean surface layer through direct biological heating, triggering additional positive feedbacks in the Arctic, and consequently intensifying the Arctic warming further. Our results establish the presence of marine phytoplankton as an important potential driver of the future Arctic climate changes.

El Niño in a changing climate.

El Niño events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on subdecadal timescales. Understanding changes in the frequency or characteristics of El Niño events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies show that the canonical El Niño has become less frequent and that a different kind of El Niño has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Niño, termed the central Pacific El Niño (CP-El Niño; also termed the dateline El Niño, El Niño Modoki or warm pool El Niño), differs from the canonical eastern Pacific El Niño (EP-El Niño) in both the location of maximum SST anomalies and tropical-midlatitude teleconnections. Here we show changes in the ratio of CP-El Niño to EP-El Niño under projected global warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set. Using calculations based on historical El Niño indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Niño compared to the EP-El Niño. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Niño to EP-El Niño, the occurrence ratio of CP-El Niño/EP-El Niño is projected to increase as much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.