The Microscopic Mechanisms of Nonlinear Rectification on Si-MOSFETs Terahertz Detector.

Studying the nonlinear photoresponse of different materials, including III-V semiconductors, two-dimensional materials and many others, is attracting burgeoning interest in the terahertz (THz) field. Especially, developing field-effect transistor (FET)-based THz detectors with preferred nonlinear plasma-wave mechanisms in terms of high sensitivity, compactness and low cost is a high priority for advancing performance imaging or communication systems in daily life. However, as THz detectors continue to shrink in size, the impact of the hot-electron effect on device performance is impossible to ignore, and the physical process of THz conversion remains elusive. To reveal the underlying microscopic mechanisms, we have implemented drift-diffusion/hydrodynamic models via a self-consistent finite-element solution to understand the dynamics of carriers at the channel and the device structure dependence. By considering the hot-electron effect and doping dependence in our model, the competitive behavior between the nonlinear rectification and hot electron-induced photothermoelectric effect is clearly presented, and it is found that the optimized source doping concentrations can be utilized to reduce the hot-electron effect on the devices. Our results not only provide guidance for further device optimization but can also be extended to other novel electronic systems for studying THz nonlinear rectification.

Data-driven optical method for full-field stress measurements.

We demonstrate an optical method to directly determine full-field stress by combining a data-driven method with digital image correlation (DIC) strain data. In order to obtain the full-field stress distribution, the full-field strain measured by 2D-DIC and an isotropic ideal elastoplastic material stress-strain dataset are used. The proposed data-driven full-field stress measurement method determines the full-field stress components by performing iterative calculations using the dataset and a distance-functional-based data-driven algorithm without assuming any constitutive equations. The proposed method is implemented in an experiment-in-loop simulation and a practical application. The stress fields of uniaxial tensile and compact tensile processes are determined by the developed algorithm. The results show that the proposed data-driven method can obtain accurate full-field stress using an already established material stress-strain dataset. Furthermore, the proposed method satisfies the equilibrium and compatibility constraints and therefore allows the correction of erroneous strain results from DIC calculations, resulting in more accurately calculated full-field strain and stress values.

Ultrasensitive Self-Driven Terahertz Photodetectors Based on Low-Energy Type-II Dirac Fermions and Related Van der Waals Heterojunctions.

The exotic electronic properties of topological semimetals (TSs) have opened new pathways for innovative photonic and optoelectronic devices, especially in the highly pursuit terahertz (THz) band. However, in most cases Dirac fermions lay far above or below the Fermi level, thus hindering their successful exploitation for the low-energy photonics. Here, low-energy type-II Dirac fermions in kitkaite (NiTeSe) for ultrasensitive THz detection through metal-topological semimetal-metal heterostructures are exploited. Furthermore, a heterostructure combining two Dirac materials, namely, graphene and NiTeSe, is implemented for a novel photodetector exhibiting a responsivity as high as 1.22 A W-1 , with a response time of 0.6 µs, a noise-equivalent power of 18 pW Hz-0.5 , with outstanding stability in the ambient conditions. This work brings to fruition of Dirac fermiology in THz technology, enabling self-powered, low-power, room-temperature, and ultrafast THz detection.

An inner boundary condition of moisture diffusion model for simulating transient nonlinear moisture transport in Chinese fir.

This paper proposed an inner boundary condition of moisture diffusion model for simulating transient nonlinear moisture transport of Chinese fir (Cunninghamia lanceolata). The inner boundary condition is serviced for simulate the moisture diffusion of multi-layer boards and is mainly used for the boundary conditions inside component, which presents the diffusion of moisture between wood and its adjacent wood. Furthermore, the established simulation model contains fiber orientation information and is used to simulate the moisture diffusion under different boundary conditions, which considers the constrained boundary. Simulation of simple boundary condition models and the proposed inner boundary condition model under different boundary conditions for multilayer board specimen exposed to constant temperature and constant humidity with a known initial moisture content, and the model was then validated in a laboratory climate chamber. Different from the simple boundary condition model the direct error of the proposed inner boundary model was less than 2% (moisture content), which indicates the proposed inner boundary condition could improve the accuracy of moisture diffusion model. The results show that the inner boundary condition model can comprehensively analyze the transient nonlinear moisture transfer process in different fiber directions with high accuracy.

Comparative evaluation of long non-coding RNA-based biomarkers in the urinary sediment and urinary exosomes for non-invasive diagnosis of bladder cancer.

Bladder cancer (BC) frequently causes a heavy disease burden for patients because of its easy recurrence. There is still a lack of convenient and effective methods to diagnose or monitor BC in the clinic. Emerging evidence suggests that long non-coding RNAs (lncRNAs) in urine are promising biomarkers for BC diagnosis. This study aimed to evaluate the performance of lncRNAs in urine for BC diagnosis. Seven lncRNAs (UCA1, H19, MALAT1, TUG1, GAS5, RMRP, and LINC01517) were selected as candidates by analyzing The Cancer Genome Atlas database or the literature. Expression of the candidate lncRNAs in the urinary sediment and exosomes was determined in a training cohort (n = 42) and an independent validation cohort (n = 56). Compared with normal controls, the patients with BC had a higher expression of RMRP, UCA1 and MALAT1 in the urinary exosomes and a higher expression of MALAT1 in the urinary sediment. Compared with MALAT1 in the urinary sediment, RMRP, UCA1, and MALAT1 in urinary exosomes exhibited higher combined diagnostic performance for BC diagnosis. Furthermore, higher RMRP expression in urinary exosomes was correlated with advanced tumor stages. A lncRNA panel consisting of urinary exosomal RMRP, UCA1 and MALAT1 was used to establish the support vector machine (SVM) model. An area under receiver operating characteristic (ROC) curve of the lncRNA panel predicted by the SVM model was 0.875 (sensitivity = 80.0% and specificity = 81.4%). Therefore, the lncRNA panel consisting of three urinary exosomal RMRP, UCA1 and MALAT1 has the potential to be biomarkers for BC diagnosis.

Hybrid Dirac semimetal-based photodetector with efficient low-energy photon harvesting.

Despite the considerable effort, fast and highly sensitive photodetection is not widely available at the low-photon-energy range (~meV) of the electromagnetic spectrum, owing to the challenging light funneling into small active areas with efficient conversion into an electrical signal. Here, we provide an alternative strategy by efficiently integrating and manipulating at the nanoscale the optoelectronic properties of topological Dirac semimetal PtSe2 and its van der Waals heterostructures. Explicitly, we realize strong plasmonic antenna coupling to semimetal states near the skin-depth regime (λ/104), featuring colossal photoresponse by in-plane symmetry breaking. The observed spontaneous and polarization-sensitive photocurrent are correlated to strong coupling with the nonequilibrium states in PtSe2 Dirac semimetal, yielding efficient light absorption in the photon range below 1.24 meV with responsivity exceeding ∼0.2 A/W and noise-equivalent power (NEP) less than ~38 pW/Hz0.5, as well as superb ambient stability. Present results pave the way to efficient engineering of a topological semimetal for high-speed and low-energy photon harvesting in areas such as biomedical imaging, remote sensing or security applications.

Ultrasensitive and Self-Powered Terahertz Detection Driven by Nodal-Line Dirac Fermions and Van der Waals Architecture.

Terahertz detection has been highly sought to open a range of cutting-edge applications in biomedical, high-speed communications, astronomy, security screening, and military surveillance. Nonetheless, these ideal prospects are hindered by the difficulties in photodetection featuring self-powered operation at room temperature. Here, this challenge is addressed for the first time by synthesizing the high-quality ZrGeSe with extraordinary quantum properties of Dirac nodal-line semimetal. Benefiting from its high mobility and gapless nature, a metal-ZrGeSe-metal photodetector with broken mirror symmetry allows for a high-efficiency photoelectric conversion assisted by the photo-thermoelectric effect. The designed architecture features ultrahigh sensitivity, excellent ambient stability, and an efficient rectified signal even above 0.26 THz. Maximum responsivity larger than 0.11 A W-1 , response time of 8.3 µs, noise equivalent power (NEP) less than 0.15 nW Hz-1/2 , and demonstrative imaging application are all achieved. The superb performances with a lower dark current and NEP less than 15 pW Hz-1/2 are validated through integrating the van der Waals heterostructure. These results open up an appealing perspective to explore the nontrivial topology of Dirac nodal-line semimetal by devising the peculiar device geometry that allows for a novel roadmap to address targeted terahertz application requirements.

A Personalized Mass Spectrometry-Based Assay to Monitor M-Protein in Patients with Multiple Myeloma (EasyM).

PURPOSE: M-protein is a well-established biomarker used for multiple myeloma monitoring. Current improvements in multiple myeloma treatment created the need to monitor minimal residual disease (MRD) with high sensitivity. Measuring residual levels of M-protein in serum by MS was established as a sensitive assay for disease monitoring. In this study we evaluated the performance of EasyM-a noninvasive, sensitive, MS-based assay for M-protein monitoring. EXPERIMENTAL DESIGN: Twenty-six patients enrolled in MCRN-001 clinical trial of two high-dose alkylating agents as conditioning followed by lenalidomide maintenance were selected for the study. All selected patients achieved complete responses (CR) during treatment, whereas five experienced progressive disease on study. The M-protein of each patient was first sequenced from the diagnostic serum using our de novo protein sequencing platform. The patient-specific M-protein peptides were then measured by targeted MS assay to monitor the response to treatment. RESULTS: The M-protein doubling over 6 months measured by EasyM could predict the relapse in 4 of 5 relapsed patients 2 to 11 months earlier than conventional testing. In 21 disease-free patients, the M-protein was still detectable by EasyM despite normal FLC and MRD negativity. Importantly, of 72 MRD negative samples with CR status, 62 were positive by EasyM. The best sensitivity achieved by EasyM, detecting 0.58 mg/L of M-protein, was 1,000- and 200-fold higher compared with serum protein electrophoresis and immunofixation electrophoresis, respectively. CONCLUSIONS: EasyM was demonstrated to be a noninvasive, sensitive assay with superior performance compared with other assays, making it ideal for multiple myeloma monitoring and relapse prediction.

Photothermal CO detection in a hollow-core negative curvature fiber.

We demonstrate the first, to the best of our knowledge, photothermal carbon monoxide (CO) sensor using a hollow-core negative curvature fiber. The hollow-core fiber features a typical structure of one ring cladding containing eight nontouching capillaries to form a negative curvature core-surround. The photothermal effect in a 40-µm hollow core is induced by CO absorption at 2327 nm and detected by a Mach-Zehnder interferometer operating at 1533 nm. By using wavelength modulation spectroscopy, we achieve a normalized noise equivalent absorption coefficient of 4.4×10-8 cm-1 WHz-1/2. As CO has a very slow vibrational-translational relaxation process, we enhance the photothermal signal by enhancing the relaxation with the water vapor additive.

Interband cascade laser absorption sensor for real-time monitoring of formaldehyde filtration by a nanofiber membrane.

It is important to reduce the indoor formaldehyde (H2CO) level to improve indoor air quality. To investigate the H2CO filtration by a novel nanofiber membrane made from metal-organic frameworks (MOFs), we developed a laser absorption gas sensor for real-time H2CO monitoring using a room-temperature interband cascade laser (ICL) emitting at 3.6 µm. Wavelength modulation spectroscopy combined with a multipass gas cell (36 m path length) was implemented to achieve a detection sensitivity of 3 ppb H2CO at 1-s averaging time. We custom-designed a permeation H2CO generator that produces reference H2CO/N2 mixtures with an uncertainty of 6.4% in concentration. With the time-resolved continuous measurements, we observed a high filtration efficiency of 83% for the MOF filter, which, however, decreases linearly to 30% after operating for 3 h. Hence, the ICL-based gas sensor has proved to be a promising technique to assess novel nanomaterials for indoor air purification and pollutant control applications.