Light-driven nanoscale vectorial currents.

Controlled charge flows are fundamental to many areas of science and technology, serving as carriers of energy and information, as probes of material properties and dynamics1 and as a means of revealing2,3 or even inducing4,5 broken symmetries. Emerging methods for light-based current control5-16 offer particularly promising routes beyond the speed and adaptability limitations of conventional voltage-driven systems. However, optical generation and manipulation of currents at nanometre spatial scales remains a basic challenge and a crucial step towards scalable optoelectronic systems for microelectronics and information science. Here we introduce vectorial optoelectronic metasurfaces in which ultrafast light pulses induce local directional charge flows around symmetry-broken plasmonic nanostructures, with tunable responses and arbitrary patterning down to subdiffractive nanometre scales. Local symmetries and vectorial currents are revealed by polarization-dependent and wavelength-sensitive electrical readout and terahertz (THz) emission, whereas spatially tailored global currents are demonstrated in the direct generation of elusive broadband THz vector beams17. We show that, in graphene, a detailed interplay between electrodynamic, thermodynamic and hydrodynamic degrees of freedom gives rise to rapidly evolving nanoscale driving forces and charge flows under the extremely spatially and temporally localized excitation. These results set the stage for versatile patterning and optical control over nanoscale currents in materials diagnostics, THz spectroscopies, nanomagnetism and ultrafast information processing.

Enhancement of PVDF Sensing Characteristics by Retooling the Near-Field Direct-Write Electrospinning System.

This research aimed to develop a direct-write near-field electrospinning system (DW-NFES) with three-axis positioning of controllable speed, torque and position to produce sizable and high-quality piezoelectric fibers for sensing purposes. Sensor devices with high electrical response signals were developed and tested. To achieve DW-NFES purpose, a servo motor controller was designed to develop a high response rate, accurate positioning, and stable mobile device through the calculation of bandwidth and system time delay. With this retooled system of DW-NFES, controllable and uniform size fibers in terms of diameters, stretching force, and interspaces can be obtained. Sensor devices can be made selectively without a complicated lithography process. The characteristics of this DW-NFES platform were featured by high response rate, accurate positioning, and stable movement to make fibers with high piezoelectric property. In this study, polyvinylidene fluoride (PVDF) was used to explore and enhance their sensing quality through the platform. The parametric study of the process factors on piezoelectric sensing signals mainly included the concentration of electrospinning PVDF solution, high voltage electric field, and collection speed. Finally, the surface morphology and piezoelectric properties of the as-electrospun PVDF fibers were examined by scanning electron microscopy (SEM) and characterized by electrical response measurement techniques. The results showed that the fiber spinning speed of the DW-NFES system could be increased to ~125 from ~20 mm/s and the accuracy precision was improved to ~1 from ~50 µm, compared to conventional step motor system. The fiber diameter reached ~10 µm, and the electrospinning pitch reached to as small as ~10 µm. The piezoelectric output voltage of the electrospun fibers was increased ~28.6% from ~97.2 to ~125 mV; the current was increased ~27.6% from ~163 to ~208 nA, suggesting that the piezoelectric signals can be enhanced significantly by using this retooled system. Finally, an external control module (Arduino-MAGE) was introduced to control the PVDF piezoelectric fiber sensors integrated as a sensing array. The behavior of long-term sedentary patients can be successfully detected by this module system to prevent the patients from the bedsores.

Improvement of Model Predictive Current Control Sensing Strategy for a Developed Small Flux-Switching Permanent Magnet Motor.

This paper presents an improved control system for a small flux-switching permanent magnet motor (FSPM) to enhance its performance and torque sensing. The analytical magnetic circuit design was used to determine the related motor parameters, such as the air gap flux density, permeance coefficient (Pc), torque, winding turns, pole number, width, length, magnet geometry, and the current density of FSPM. The electromagnetic analysis of this motor was performed by software (ANSYS Maxwell) to optimize the motor performance. In this study, the performance of FSPM was investigated by the uniform design experimentation (UDE). For the control system, the model predictive current control (MPCC) is currently recognized as a high-performance control strategy, due to its quick response and simple principle. This model contained the nonlinear part of the system, to improve the torque ripple of FSPM. A modified MPCC strategy was proposed to improve the distortion of the current waveform and decrease the computational burden. The new modified control architecture was mainly composed of three parts, such as the estimation of electromotive force (EMF), current prediction, and optimal vector selection/vector duration. When the reference voltage vector was obtained, the three-phase duties were easily determined by the principle of space vector modulation (SVM). The results show the different strategy methods between the newly proposed modified MPCC and traditional proportional integral (PI) controller. In the control of FSPM, a modified MPCC strategy was able to achieve a better performance response and decrease the computational burden. At a low speed of 350 rpm, the proposed modified MPCC can achieve a better dynamic response. The nonlinear problem of the startup speed was also effectively resolved. The torque sensing performance of the simulation and the experimental test value were compared. The torque sensing performance of the simulation and the actual test value were also examined. In this study, the optimization focused not only on the motor design and fabrication, but also on an improved motor control strategy and torque sensing, in order to achieve the integrity of the FSPM system.

Broadband Linear-to-Circular Polarization Conversion Enabled by Birefringent Off-Resonance Reflective Metasurfaces.

Due to the scarcity of circular polarization light sources, linear-to-circular polarization conversion is required to generate circularly polarized light for a variety of applications. Despite significant past efforts, broadband linear-to-circular polarization conversion remains elusive particularly in the terahertz and midinfrared frequency ranges. Here we propose a novel mechanism based on coupled mode theory, and experimentally demonstrate at terahertz frequencies that highly efficient (power conversion efficiency approaching unity) and ultrabroadband (fractional bandwidth up to 80%) linear-to-circular polarization conversion can be accomplished by the judicious design of birefringent metasurfaces. The underlying mechanism operates in the frequency range between well separated resonances, and relies upon the phase response of these resonances away from the resonant frequencies, as well as the balance of the resonant and nonresonant channels. This mechanism is applicable for any operating frequencies from microwave to visible. The present Letter potentially opens a wide range of opportunities in wireless communications, spectroscopy, and emergent quantum materials research where circularly polarized light is desired.

High-Temperature Refractory Metasurfaces for Solar Thermophotovoltaic Energy Harvesting.

Solar energy promises a viable solution to meet the ever-increasing power demand by providing a clean, renewable energy alternative to fossil fuels. For solar thermophotovoltaics (STPV), high-temperature absorbers and emitters with strong spectral selectivity are imperative to efficiently couple solar radiation into photovoltaic cells. Here, we demonstrate refractory metasurfaces for STPV with tailored absorptance and emittance characterized by in situ high-temperature measurements, featuring thermal stability up to at least 1200 °C. Our tungsten-based metasurface absorbers have close-to-unity absorption from visible to near-infrared and strongly suppressed emission at longer wavelengths, while our metasurface emitters provide wavelength-selective emission spectrally matched to the band-edge of InGaAsSb photovoltaic cells. The projected overall STPV efficiency is as high as 18% when a fully integrated absorber/emitter metasurface structure is employed, which is comparable to the efficiencies of the best currently available commercial single-junction PV cells and can be further improved to potentially exceed those in mainstream photovoltaic technologies. Our work opens a path forward for high-performance STPV systems based on refractory metasurface structures.

Mechanical property characterization of hundreds of single nuclei based on microfluidic constriction channel.

As label-free biomarkers, the mechanical properties of nuclei are widely treated as promising biomechanical markers for cell type classification and cellular status evaluation. However, previously reported mechanical parameters were derived from only around 10 nuclei, lacking statistical significances due to low sample numbers. To address this issue, nuclei were first isolated from SW620 and A549 cells, respectively, using a chemical treatment method. This was followed by aspirating them through two types of microfluidic constriction channels for mechanical property characterization. In this study, hundreds of nuclei were characterized, producing passage times of 0.5 ± 1.2 s for SW620 nuclei in type I constriction channel (n = 153), 0.045 ± 0.047 s for SW620 nuclei in type II constriction channel (n = 215) and 0.50 ± 0.86 s for A549 nuclei in type II constriction channel. In addition, neural network based pattern recognition was used to classify the nuclei isolated from SW620 and A549 cells, producing successful classification rates of 87.2% for diameters of nuclei, 85.5% for passage times of nuclei and 89.3% for both passage times and diameters of nuclei. These results indicate that the characterization of the mechanical properties of nuclei may contribute to the classification of different tumor cells.

Resonance coupling and polarization conversion in terahertz metasurfaces with twisted split-ring resonator pairs.

We investigate edge-coupling of twisted split-ring resonator (SRR) pairs in the terahertz (THz) frequency range. Using a simple coupled-resonator model we show that such a system exhibits resonance splitting and cross-polarization conversion. Numerical simulations and experimental measurements agree well with theoretical calculations, verifying the resonance splitting as a function of the coupling strength given by the SRR separation. We further show that a metal ground plane can be integrated to significantly enhance the resonance coupling, which enables the effective control of resonance splitting and the efficiency and bandwidth of the cross-polarization conversion. Our findings improve the fundamental understanding of metamaterials with a view of accomplishing metamaterial functionalities with enhanced performance, which is of great interest in realizing THz functional devices required in a variety of applications.

Demonstration of a highly efficient terahertz flat lens employing tri-layer metasurfaces.

We demonstrate a terahertz flat lens based on tri-layer metasurfaces allowing for broadband linear polarization conversion, where the phase can be tuned through a full 2π range by tailoring the geometry of the subwavelength resonators. The lens functionality is realized by arranging these resonators to create a parabolic spatial phase profile. The fabricated 124-µm-thick device is characterized by scanning the beam profile and cross section, showing diffraction-limited focusing and ∼68% overall efficiency at the operating frequency of 400 GHz. This device has potential for applications in terahertz imaging and communications, as well as beam control in general.

86% internal differential efficiency from 8 to 9 µm-emitting, step-taper active-region quantum cascade lasers.

8.4 µm-emitting quantum cascade lasers (QCLs) have been designed to have, right from threshold, both carrier-leakage suppression and miniband-like carrier extraction. The slope-efficiency characteristic temperature T1, the signature of carrier-leakage suppression, is found to be 665 K. Resonant-tunneling carrier extraction from both the lower laser level (ll) and the level below it, coupled with highly effective ll-depopulation provide a very short ll lifetime (~0.12 ps). As a result the laser-transition differential efficiency reaches 89%, and the internal differential efficiency ηid, derived from a variable mirror-loss study, is found to be 86%, in good agreement with theory. A study of 8.8 µm-emitting QCLs also provides an ηid value of 86%. A corrected equation for the external differential efficiency is derived which leads to a fundamental limit of ~90% for the ηid values of mid-infrared QCLs. In turn, the fundamental wallplug-efficiency limits become ~34% higher than previously predicted.

Behind the color switching in gasochromic VO2.

Gasochromic VO2 thin films were fabricated by the sol-gel spin-coating technique. The results of X-ray absorption spectroscopy and resonant inelastic X-ray scattering spectroscopy reveal that the origin of gasochromic coloration in VO2 is strongly related to the modulation of its structure and the electron-electron correlation. Upon gasochromic coloration, not only does the valence state change with the incorporation of hydrogen, but also the film undergoes the modification of the local atomic structure. The structural distortion varies the strength of hybridization of the O 2p-V 3d states and the bond distance of V-O and V-O varies. In the hydric process, the local atomic structure of VO2 changes from that of an un-symmetric to that of a symmetric V-O framework. The incorporated hydrogen adds electrons into the V 3d t2g orbital, enhancing the electron-electron correlation by reducing the V-V distance. This work presents a new physical insight in which the modulation of the electron-electron correlation is exploited to control the bleached and colored states, giving rise to the gasochromic phenomenon. The strong correlation among atomic spatial rearrangement, electronic structures, and transmittance supports a cooperative mechanism of the VO2 gasochromic transition. These results reveal a clear correlation between the dynamics of the lattice structure and the electronic properties and suggest a possible pathway to gasochromism and elucidation of its mechanism.

Single-molecule imaging reveals aß42:aß40 ratio-dependent oligomer growth on neuronal processes.

Soluble oligomers of the amyloid-ß peptide have been implicated as proximal neurotoxins in Alzheimer's disease. However, the identity of the neurotoxic aggregate(s) and the mechanisms by which these species induce neuronal dysfunction remain uncertain. Physiologically relevant experimentation is hindered by the low endogenous concentrations of the peptide, the metastability of Aß oligomers, and the wide range of observed interactions between Aß and biological membranes. Single-molecule microscopy represents one avenue for overcoming these challenges. Using this technique, we find that Aß binds to primary rat hippocampal neurons at physiological concentrations. Although amyloid-ß(1-40) as well as amyloid-ß(1-42) initially form larger oligomers on neurites than on glass slides, a 1:1 mix of the two peptides result in smaller neurite-bound oligomers than those detected on-slide or for either peptide alone. With 1 nM peptide in solution, Aß40 oligomers do not grow over the course of 48 h, Aß42 oligomers grow slightly, and oligomers of a 1:1 mix grow substantially. Evidently, small Aß oligomers are capable of binding to neurons at physiological concentrations and grow at rates dependent on local Aß42:Aß40 ratios. These results are intriguing in light of the increased Aß42:Aß40 ratios shown to correlate with familial Alzheimer's disease mutations.

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies widely tested in anti-cancer treatment, i.e. VEGF-targeting monoclonal antibody bevacizumab, in combination with chemotherapy for frontline and maintenance therapy for women with newly diagnosed ovarian cancer. Identification of the best predictive biomarkers of bevacizumab response is necessary in order to select patients most likely to benefit from this therapy. Hence, this study investigates the protein expression patterns on immunohistochemical whole slide images of three angiogenesis related proteins, including Vascular endothelial growth factor, Angiopoietin 2 and Pyruvate kinase isoform M2, and develops an interpretable and annotation-free attention based deep learning ensemble framework to predict the bevacizumab therapeutic effect on patients with epithelial ovarian cancer or peritoneal serous papillary carcinoma using tissue microarrays (TMAs). In evaluation with five-fold cross validation, the proposed ensemble model using the protein expressions of both Pyruvate kinase isoform M2 and Angiopoietin 2 achieves a notably high F-score (0.99±0.02), accuracy (0.99±0.03), precision (0.99±0.02), recall (0.99±0.02) and AUC (1.00±0). Kaplan-Meier progression free survival analysis confirms that the proposed ensemble is able to identify patients in the predictive therapeutic sensitive group with low cancer recurrence (p<0.001), and the Cox proportional hazards model analysis further confirms the above statement (p=0.012). In conclusion, the experimental results demonstrate that the proposed ensemble model using the protein expressions of both Pyruvate kinase isoform M2 and Angiopoietin 2 can assist treatment planning of bevacizumab targeted therapy for patients with ovarian cancer.

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles.

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research.

Tuning the Emission Wavelength of Lead Halide Perovskite NCs via Size and Shape Control.

The advent of lead halide perovskite nanocrystals (NCs), which are easily synthesized, ultralow-cost materials and have an impeccable luminous efficiency, has drastically changed the future perspective of semiconductor quantum dot devices. Although the band gap energy of lead perovskite NCs can be tuned by the halide composition, the instability problem prevails for mixed-halide perovskite NCs, caused by phase segregation due to ion migration when an external electric field or light is applied. To avoid this problem and obtain the stable emission of RGB primary colors, in this study, two synthesis pathways of pure-halide perovskite NCs are proposed. One approach is the modified hot injection method with "centrifugation of a frozen eutectic mixture" to separate small NCs efficiently, and the other is the "low-temperature mixing and heat-up method" for target materials including CsPbI3, CsPbBr3, and CH(NH2)2PbBr3 (FAPbBr3). The emission wavelength of FAPbBr3 is tuned ion-stoichiometrically, unlike Cs perovskites. These various synthesis pathways of pure-halide perovskite NCs enable the efficient production of high-quality perovskite NCs and allow precise tuning of the emission color to the desired wavelength. Although there are still several "gaps" remaining in the available emission wavelength, the new methodology proposed in this study could potentially be employed for manufacturing more stable perovskite NC-based optoelectronic devices.

A Weakly Supervised Deep Learning Method for Guiding Ovarian Cancer Treatment and Identifying an Effective Biomarker.

Ovarian cancer is a common malignant gynecological disease. Molecular target therapy, i.e., antiangiogenesis with bevacizumab, was found to be effective in some patients of epithelial ovarian cancer (EOC). Although careful patient selection is essential, there are currently no biomarkers available for routine therapeutic usage. To the authors' best knowledge, this is the first automated precision oncology framework to effectively identify and select EOC and peritoneal serous papillary carcinoma (PSPC) patients with positive therapeutic effect. From March 2013 to January 2021, we have a database, containing four kinds of immunohistochemical tissue samples, including AIM2, c3, C5 and NLRP3, from patients diagnosed with EOC and PSPC and treated with bevacizumab in a hospital-based retrospective study. We developed a hybrid deep learning framework and weakly supervised deep learning models for each potential biomarker, and the experimental results show that the proposed model in combination with AIM2 achieves high accuracy 0.92, recall 0.97, F-measure 0.93 and AUC 0.97 for the first experiment (66% training and 34%testing) and high accuracy 0.86 ± 0.07, precision 0.9 ± 0.07, recall 0.85 ± 0.06, F-measure 0.87 ± 0.06 and AUC 0.91 ± 0.05 for the second experiment using five-fold cross validation, respectively. Both Kaplan-Meier PFS analysis and Cox proportional hazards model analysis further confirmed that the proposed AIM2-DL model is able to distinguish patients gaining positive therapeutic effects with low cancer recurrence from patients with disease progression after treatment (p < 0.005).

A surface plasmon enhanced infrared photodetector based on InAs quantum dots.

In this paper, we report a successful realization and integration of a gold two-dimensional hole array (2DHA) structure with semiconductor InAs quantum dot (QD). We show experimentally that a properly designed 2DHA-QD photodetector can facilitate a strong plasmonic-QD interaction, leading to a 130% absolute enhancement of infrared photoresponse at the plasmonic resonance. Our study indicates two key mechanisms for the performance improvement. One is an optimized 2DHA design that permits an efficient coupling of light from the far-field to a localized plasmonic mode. The other is the close spatial matching of the QD layers to the wave function extent of the plasmonic mode. Furthermore, the processing of our 2DHA is amenable to large scale fabrication and, more importantly, does not degrade the noise current characteristics of the photodetector. We believe that this demonstration would bring the performance of QD-based infrared detectors to a level suitable for emerging surveillance and medical diagnostic applications.

All-inorganic perovskite quantum dot light-emitting memories.

Field-induced ionic motions in all-inorganic CsPbBr3 perovskite quantum dots (QDs) strongly dictate not only their electro-optical characteristics but also the ultimate optoelectronic device performance. Here, we show that the functionality of a single Ag/CsPbBr3/ITO device can be actively switched on a sub-millisecond scale from a resistive random-access memory (RRAM) to a light-emitting electrochemical cell (LEC), or vice versa, by simply modulating its bias polarity. We then realize for the first time a fast, all-perovskite light-emitting memory (LEM) operating at 5 kHz by pairing such two identical devices in series, in which one functions as an RRAM to electrically read the encoded data while the other simultaneously as an LEC for a parallel, non-contact optical reading. We further show that the digital status of the LEM can be perceived in real time from its emission color. Our work opens up a completely new horizon for more advanced all-inorganic perovskite optoelectronic technologies.

Comprehensive Profiling of Poor-Risk Paired Primary and Recurrent Triple-Negative Breast Cancers Reveals Immune Phenotype Shifts.

PURPOSE: Emerging data suggest immune checkpoint inhibitors have reduced efficacy in heavily pretreated triple-negative breast cancers (TNBC), but underlying mechanisms are poorly understood. To better understand the phenotypic evolution of TNBCs, we studied the genomic and transcriptomic profiles of paired tumors from patients with TNBC. EXPERIMENTAL DESIGN: We collected paired primary and metastatic TNBC specimens from 43 patients and performed targeted exome sequencing and whole-transcriptome sequencing. From these efforts, we ascertained somatic mutation profiles, tumor mutational burden (TMB), TNBC molecular subtypes, and immune-related gene expression patterns. Stromal tumor-infiltrating lymphocytes (stromal TIL), recurrence-free survival, and overall survival were also analyzed. RESULTS: We observed a typical TNBC mutational landscape with minimal shifts in copy number or TMB over time. However, there were notable TNBC molecular subtype shifts, including increases in the Lehmann/Pietenpol-defined basal-like 1 (BL1, 11.4%-22.6%) and mesenchymal (M, 11.4%-22.6%) phenotypes, and a decrease in the immunomodulatory phenotype (IM, 31.4%-3.2%). The Burstein-defined basal-like immune-activated phenotype was also decreased (BLIA, 42.2%-17.2%). Among downregulated genes from metastases, we saw enrichment of immune-related Kyoto Encyclopedia of Genes and Genomes pathways and gene ontology (GO) terms, and decreased expression of immunomodulatory gene signatures (P < 0.03) and percent stromal TILs (P = 0.03). There was no clear association between stromal TILs and survival. CONCLUSIONS: We observed few mutational shifts, but largely consistent transcriptomic shifts in longitudinally paired TNBCs. Transcriptomic and IHC analyses revealed significantly reduced immune-activating gene expression signatures and TILs in recurrent TNBCs. These data may explain the observed lack of efficacy of immunotherapeutic agents in heavily pretreated TNBCs. Further studies are ongoing to better understand these initial observations.See related commentary by Savas and Loi, p. 526.

Highly Plasmonic Titanium Nitride by Room-Temperature Sputtering.

Titanium nitride (TiN) has recently emerged as an attractive alternative material for plasmonics. However, the typical high-temperature deposition of plasmonic TiN using either sputtering or atomic layer deposition has greatly limited its potential applications and prevented its integration into existing CMOS device architectures. Here, we demonstrate highly plasmonic TiN thin films and nanostructures by a room-temperature, low-power, and bias-free reactive sputtering process. We investigate the optical properties of the TiN films and their dependence on the sputtering conditions and substrate materials. We find that our TiN possesses one of the largest negative values of the real part of the dielectric function as compared to all other plasmonic TiN films reported to date. Two-dimensional periodic arrays of TiN nanodisks are then fabricated, from which we validate that strong plasmonic resonances are supported. Our room-temperature deposition process can allow for fabricating complex plasmonic TiN nanostructures and be integrated into the fabrication of existing CMOS-based photonic devices to enhance their performance and functionalities.

Color, dispersion, and exposure time in performance on rotated figure recognition.

This study investigated the effects of dispersion, color, and rotation of figures on recognition under varied exposure times. A total of 30 women and 15 men, Taiwanese college students ages 18 to 20 years (M = 19.1, SD = 1.2), participated. Subjects were to recognize a target figure and respond with its location in each stimulus by pressing a mouse button. Analysis showed that the effect of rotation on accuracy was significant. Accuracy for the rotation of 180 degrees was greater than those for 60 degrees and 300 degrees. Exposure time also significantly influenced accuracy. The accuracy was greater for 2 and 3 sec. than for 1 sec. No significant effects on accuracy were associated with dispersion and color, and neither had any interactive effect on accuracy. Dispersion significantly affected the response time as response time for dispersion under 0.4 and 0.5 conditions were shorter than those under 0.2 and 0.3 conditions. Significantly less response time was needed for rotation of 180 degrees than for 60 degrees and 300 degrees conditions. Response time was longer for red figures than for blue, green, and yellow figures. No significant effect on response time was associated with duration of exposure. Two interactive two-way effects were found: dispersion x color of figure and dispersion x rotation. Implications for figure or icon design are discussed.