This study presents a high-precision, long-range absolute time-grating linear displacement sensor based on a multilayer cascade structure. In the layer I structure, electric field coupling between the fixed and moving rulers generates an induction signal on the moving ruler. In the layer II structure, the transmitting stage receives this signal via internal wiring, and signal cascading is achieved through secondary coupling between the transmitting and receiving stages. The cascade structure makes full use of the available space above the fixed ruler, eliminating the need to expand the sensing areas of the fixed and moving rulers. This structure enhances signal strength through multilayer coupling and avoids the need for moving part leads. The sensor's electrode array enables long-range measurements, with absolute positioning determined by a simple subtraction between two single-row incremental time-grating sensor signal phases, bypassing complex coding and decoding. Experimental analysis reveals traveling wave crosstalk, causing nonlinear measurement errors. Time-division multiplexing completely suppresses crosstalk and enhances measurement accuracy. After optimization, the sensor's peak-to-peak measurement error is reduced by approximately three times, achieving an accuracy of +/- 0.2 mu m over a 400 mm range after compensation.

Eigenmode expansion (EME) is a widely used method for modeling the electromagnetic wave propagation in multimode waveguides, where it breaks down signals into local eigenmodes and calculates them independently. Nevertheless, this methodology may challenge the causality mandated by the theory of special relativity, thus potentially disrupting the cause-and-effect relationship. This study experimentally explored light transmission in the multimode coreless fiber and found discrepancies between the EME method and measurement. To reconcile these inconsistencies, we introduced a light cone model, providing an alternative interpretation guided by the principles of special relativity. Remarkably, this innovative model did not merely resolve the observed discrepancies between the theory and experiments, but also presented a pioneering technique for designing microbend sensors. Through experimentation, we achieved the remarkable sensitivity of 500 dB/m−1 at a bending curvature of 0 m−1. Our research advances the understanding of multimode systems and paves the way for innovative sensing and communications applications in compact devices.

We investigate the dissociation pathways of doubly ionized hydrogen cyanide (HCN2+) produced via 1.0 keV electron beam impact. Using a coincidence ion imaging spectrometer, we identify two distinct dissociation mechanisms: prompt decomposition, characterized by localized correlation islands in time-of-flight spectra, and delayed fragmentation, evidenced by elongated spectral tails. Kinetic energy release distributions indicate that the deprotonation channel (HCN2+ → H+ + CN+) stems from low-lying electronic states of the dication, aligning with prior photon double-ionization studies. However, metastable state lifetimes exhibit significant prolongation compared to photon-induced processes. Calculations of potential energy surfaces combined with reaction rate theory suggest that this discrepancy may arise from differences in vibrational state populations between the two ionization methods.

Optical-fiber-based surface plasmon resonance (SPR) biosensors, featuring label-free, high integration, and small size, have aroused great interest in recent years. However, the reported sensors always presented with a length of several millimeters even longer, and faced a huge task in sensitivity improvement. In this study, a dual-mechanism enhanced miniature optical fiber SPR bio-probe based on nanodiamonds (NDs) is proposed and demonstrated. The probe is composed of a multimode fiber terminated by a short section of no-core fiber, whose surface is deposited with a gold film. Then, carboxylated NDs are exploited to improve the probe sensitivity simultaneously from two aspects, namely plasmonic and biological aspects. On the one hand, the plasmonic sensing field is enhanced by chemically-modifying NDs on the gold surface, which generates 46.5% improvement in bulk refractive index sensitivity. On the other hand, NDs are chemically-bonded with second antibodies to further improve the biological signal using sandwich method. As a result, the sensitivity of probe to the immunodetection of biological protein (mouse immunoglobulin G in this work) is significantly improved by more than an order of magnitude. Besides, test results prove a good specificity and the capability of working in serum environment for the probe. Our work first demonstrates the NDs application as a gain medium in the second signal amplification of SPR biosensing. Meanwhile, the obtained miniature and high sensitivity bio-probe is very suitable for the case requiring a tiny probe size or sample volume.

We present a dual-mechanism nanodiamond-enhanced miniature fiber SPR probe. Its synergistic plasmonic/biological enhancement achieves order-of-magnitude sensitivity improvement in mouse IgG immunodetection for ultrasensitive trace-sample biosensing.

This study reveals eigenmode expansion (EME) challenges causality in multimode waveguides. A light cone model reconciles theory-experiment discrepancies and enables a high-sensitivity microbend sensor (500 dB/m⁻¹).

The fragmentation dynamics of NCCN2+ and NCCN3+ produced by 1-keV electron impact have been investigated using the ion momentum imaging technique. Five two-body and two three-body fragmentation channels are identified including two isomerization pathways. The reaction coordinates of isomerization channels were investigated by quantum chemistry calculation. By measuring the momentum vectors of the fragment ions, the kinetic energy release distributions have been determined. With the help of the Dalitz plot, Newton diagram, and native-frame method, we investigated the fragmentation mechanisms of the three-body fragmentation channels. It is found that the channel NCCN3+ -* N+ + N+ + C+2 only dissociates via the concerted mechanism, while channel NCCN3+ -* C+ + N+ + CN+ presents two sequential fragmentation processes with CN2+ and C2N2+ as intermediate moieties in addition to the concerted fragmentation.

An optical fiber surface plasmon resonance (SPR) sensor, leveraging hyperbolic metamaterials (HMMs) and pH-sensitive hydrogels, has been devised for pH detection in perspiration. Dispersion-tunable HMMs enable the sensor to transcend the inherent structural constraints of an optical fiber and enhance its refractive index (RI) sensitivity. pH-sensitive hydrogels exhibit diverse swelling behaviors due to varying ionization degrees of carboxyl groups under different solution pH conditions, leading to a notable RI change. The sensor achieves a high RI sensitivity of 6963.64 nm RIU-1 and remarkable pH sensitivity of -64.04 and -30.63 nm pH-1 within the pH ranges of 2.7 to 4.7 and 4.7 to 7.5, respectively. Compared to the sensitivity of three other constituents in perspiration, namely, urea, sodium chloride, and glucose, the sensor demonstrates exceptional pH selectivity. Additionally, it maintains good stability during operation and after prolonged storage. It is believed that the sensor has potential in health monitoring, medical diagnosis, disease treatment, etc.

Cellulose foams are renewable and biodegradable materials that are promising substitutes for plastic foams. However, the scale-up fabrication of cellulose foams is severely hindered by technological complexity and cost- and time-consuming drying processes. Here, we developed a facile and robust method to fabricate cellulose foams via oven-drying following surfactant-assisted mechanical foaming of cellulose nanofibers (CNFs). CNFs in the air-water interface reduced the surface tension to stabilize bubbles in the wet foams, and generated densely arranged crystal barriers to seal air in the bubbles while oven-drying to prevent bubbles from collapsing. The optimal CNF foam has an ultra-low density of 12.10 mg/cm3, an ultra-high porosity of 99.14 %, and a low thermal conductivity of 34.87 mW/m/K, allowing it to act as an excellent thermal insulation material. Moreover, CNF foams can be easily integrated with diverse advanced properties such as flame retardancy, ultra-high mechanical strength, hydrophobicity, and magnetic responsiveness by incorporating functional components. The study paves the way for CNF foams to move toward practical applications.

At present, hot spot identification methods for photovoltaic (PV) modules are difficult to accurately characterize the size and location of the hot spots, which brings a challenge to timely handling of the fault. To solve the problem, an enhanced U-Net with visual geometry group-19 (VGG19) and squeeze-and-excitation (SVU-Net) is proposed to achieve accurate identification at the granularity level of pixels. Based on the U-Net architecture, the convolutional layer of VGG19 is used as an encoder to extract feature information of PV module hot spot images. Based on skip connections, detailed information are gradually recovered through the upsampling of the decoder. Specifically, the thermal infrared image of the PV module is processed by the Gaussian blur and image sharpening method to improve the quality of the hot spot image. Then, based on the U-Net architecture, the convolutional layer of VGG19 is used as the encoder to extract low-level and high-level features through a series of convolutional layers and pooling layers. At the same time, a squeeze-and-excitation block is added to the $224 \times 224 \times 64$ convolution in the VGG19 encoder for extracting global features. In addition, to better distinguish the differences between PV hot spots and normal regions, dilated convolutions are used to increase the receptive field and enhance the understanding of the structure and semantics in the image, thereby capturing the surrounding context information of the hot spots. The experimental results show that the accuracy and mean intersection over union (MIoU) of PV hot spots are 98.37% and 91.93%, respectively, by using the proposed method.

In recent years, utilizing nitrogen-vacancy color centers in diamond for temperature sensing has drawn great attention. However, increasing the sensitivity has encountered challenges due to the intrinsic temperature-dependent energy level shift, i.e . , temperature responsivity, being limited to -74 kHz/K. In this Letter, we take advantage of the magnetic field to regulate the energy level to enhance temperature sensitivity. The sensor is formed by adhering a micron-sized diamond on the end face of an optical fiber, and a small magnet is mounted at a certain distance with the diamond exploiting a cured polydimethylsiloxane block as the bridge. The temperature change leads to the variation of the distance between the diamond and the magnet, thus affecting the magnetic strength felt by the diamond. This finally contributes an additional temperature-induced energy level shift, giving rise to an enhanced sensitivity. Experimental results demonstrated the proposed scheme and achieved a 4.2-fold improvement in the temperature responsivity and a 2.1-fold enhancement in sensitivity. Moreover, the diamond and the fiber-optic integrated structure improve the portability of the sensor.

The longitudinal relaxation time (termed as T 1 ) of nitrogen-vacancy (NV) centers in nanodiamonds can be affected by surface electric or magnetic noise, which has been exploited to develop cutting-edge quantum relaxometry for biochemical sensing. In this work, a tiny all-fiber quantum probe based on longitudinal relaxometry was developed by chemically-anchoring nanodiamonds on the surface of a cone fiber tip. The dependences of T 1 on surface electric and magnetic noise were discussed in theories first and then experimentally demonstrated in varied pH and Gd 3+ concentration solutions, respectively. Because of NV centers being subject to enhanced coupling from surface noise, T 1 reduced from 290 to 245 µs when pH changed from 3 to 9 and reduced to 220 µs when Gd 3+ concentration increased to 10 mM, agreeing well with theoretical results. Based on these, the Gd 3+ -tagged-biotin and streptavidin model was designed and implemented on the all-fiber probe, and results demonstrated the detection of biotin with a limit of 168 nM and good specificity. This paper opens a new way to develop an all-fiber quantum probe by exploiting the unique electrical spin properties of NV centers, and the probe shows great potential for biological detection with high sensitivity and specificity.

In this study, a novel noise - shaping (NS) successive approximation register (SAR) analog - to - digital converter (ADC) architecture is proposed, incorporating a noise transfer function (NTF) strengthening method (NSM). The order of NTF is strengthened by using an extra capacitive digital - to - analog converter (CDAC) and a cascaded Finite Impulse Response - Infinite Impulse Response (FIR - IIR) filter. The prototype converter uses an 8 - bit split capacitor CDAC. The NSM is implemented on an NS SAR ADC in 40nm process technology, achieving an Effective Number of Bits (ENOB) of 16.6 bits at an effective bandwidth of 200 kHz with an oversampling ratio (OSR) of 32 and has been validated over process - voltage - temperature (PVT). The proposed ADC consumes 1.32 mW at a 1.1V supply voltage which occupies an active area of 0.0903 mm 2 . The Schrier figure - of - merit (FoM) of 182.8 dB is obtained.

Diffractive optical element is advantageous for miniaturization, arraying and integration of optical systems. They have been widely used in beam shaping, diffractive imaging, generating beam arrays, spectral optimization and other aspects. Currently, the vast majority of diffractive optics are not tunable. This limits the applicability and functionality of these devices. Here we report a tunable diffractive optical element controlled by light in the visible band. The diffractive optical element consists of a square gold microarray deposited on a deformable substrate. The substrate is made of a liquid crystal elastomer. When pumped by a 532 nm laser, the substrate is deformed to change the crystal lattice. This changes the far-field diffraction pattern of the device. The proposed concept establishes a light-controlled soft platform with great potential for tunable/reconfigurable photonic devices, such as filters, couplers, holograms and structural color displays.

This study proposes a novel 24-bit delta sigma analogue-to-digital converter (ADC) for an audio system-on-chip (SOC) with a fully differential switched-capacitor preamplifier and a capacitor-array DAC feedback structure. This system reduces the equivalent input noise and overcomes the nonlinearity and circuit complexity caused by the multi-bit quantiser, This structure also improves the accuracy of the quantiser and achieves zero static-power consumption. Combined with the capacitor array DAC feedback structure, the entire system does not require additional reference voltage, which reduces power consumption and is more conducive to system integration on the chip simultaneously. Finally, the design achieves a maximum signal-to-noise ratio (SNR) of 120 dB and a low static power consumption of 5 mW at a sampling rate of 24.576 MHz.

The hot spot effect can cause damage to PV modules and seriously affect the safe and stable operation of PV systems. Fast and accurate detection of hot spot faults is of great importance to extend the life of PV modules and reduce power generation costs. In this paper, we propose a conditionally generated adversarial network-based hot spot detection method for PV modules, which can achieve accurate hot spot detection with small samples. Specifically, for the problem of sparse infrared image data of PV module hot spot, the hot spot dataset is expanded by a conditional generation adversarial network. The new dataset is segmented by a semantic segmentation network, which improves the problem of insufficient training of model parameters caused by the small amount of data in the original model. Through experimental validation, the proposed method optimizes the image segmentation effect and achieves accurate detection of hot spots of PV modules compared with the original model.

This study introduces a novel design of a quad-core voltage-controlled oscillator (VCO) that incorporates even-mode magnetic coupling capacitance (EMCC). A capacitor is connected via magnetic coupling and strategically positioned at the central location of the balun. As a result, it primarily impacts low-frequency signals rather than high-frequency modes. This approach effectively addresses the trade-off between the coupling coefficient and the balun Q factor. The VCO exhibits an operational bandwidth spanning from 19.19 to 43.6 GHz, with a Frequency Tuning Range (FTR) of 77.7% at 31.39 GHz. The phase noise demonstrates a value of −112.92 dBc/Hz @1MHz offset. The figure of merit (FoM) can reach a maximum value of 188.45 dBc/Hz @1MHz offset. The figure of merit for Area (FoMA) is observed to fall within the range of 197-200.4 dBc/Hz @1MHz offset, whereas the figure of merit for tuning (FoM T ) is determined to be 206.1 dBc/Hz. In order to satisfy the testing criteria and maintain the desired output power under a 50ohm load condition, a buffer is employed. The effective realization of this design has been accomplished through the utilization of a 40nm CMOS process.

Abstract In this study, a digital calibration method applicable for a continuous‐time sigma‐delta analogue‐to‐digital converter is proposed using the AC injection technique. The proposed technique directly calibrates the integration accuracy of a converter instead of only trimming the capacitors. Compared with the existing calibration methods, the proposed method does not require complex timing logic processing or additional capacitors and does not adversely impact the dynamic performance of the converter. Furthermore, it ensures the accuracy of the converter, regardless of the non‐ideal effects of advanced processes.

The three-body fragmentation dynamics of BrCNq+ (q = 3-6) produced by 1-keV electron impact has been investigated using the ion momentum imaging technique. Up to 11 three-body Coulomb explosion channels were identified and analyzed. The corresponding kinetic energy release (KER) distributions were obtained and compared with the predictions of the Coulomb explosion model. By means of the Dalitz plot, Newton diagram, and native frame method, we have studied the concerted and sequential fragmentation mechanisms for channels leading to Brl+ + C+ + N+ (l = 1-3). The KER for the intermediate dications BrC2+ and CN2+ from the sequential mechanism were determined and the electronic states of the intermediate molecular ion CN2+ were discussed. For the channels leading to higher charge states of the carbon and nitrogen ions, only the concerted fragmentation mechanism was observed.

Pathways of two-body fragmentation of BrCNq+ (q = 2, 3) have been explored by combined experimental and theoretical studies. In the experiment, the BrCN molecule is ionized by 1 keV electron impact and the created fragment ions are detected using an ion momentum imaging spectrometer. Six two-body fragmentation channels are identified. By measuring the momentum vectors of the fragment ions, the kinetic energy release (KER) distributions for these channels have been determined. Theoretically, the potential energy curves of BrCNq+ (q = 2, 3) as a function of Br-C and C-N internuclear distances are calculated by the complete active space self-consistent field method. By comparing the measured KER and theoretical predictions, pathways for the fragmentation channels are assigned. The relative branching ratios of the channels are also determined.