Large Dynamic Range Research Articles

Dynamic Range of a Digital Radio Receiver with a Photonic Analog-to-Digital Converter

The article is devoted to determining the requirements for the preliminary, analog part of the receiver and its structure when using a photonic ADC. The subject of research in this case is the issues of ensuring a large dynamic range of signals at the input of a receiver with a photonic ADC. The parameters and properties of the PADC with optical quantization and discretization are investigated. The distinctive features of the PADC are a high sampling rate, about 100 GHz, the possibility of increasing the carrier-to-noise ratio (CNR) and the effective number of bits (ENOB) due to the amplification of the carrier or modulating signal, and a low noise factor of microwave photonic elements. The presented advantages make it possible to reduce the structure of the analog part of the receiver by eliminating the mixer and anti-aliasing filter, as well as to achieve better sensitivity due to a lower level of internal noise. The study also revealed a limitation of the dynamic range imposed by the photonic element base. The reason for the limitation is the nonlinearity of the electro-optical modulators used and the limitation of the upper limit of the dynamic range to the photodetectors used. All this leads to requirements under which the analog part must provide significant amplification of the received radio signal, as well as the implementation of a variable gain. As a result, structural solutions are presented in the form of multichannel switching circuits. The principle of operation lies in the fact that each channel, consisting of a cascade of linear amplifiers and a PADC, has a different gain, and in the digital processing unit, channels are compared and switched depending on the signal level. At the same time, the level should be in the 'corridor' of acceptable values for the application of the PADC and within the dynamic range. The presented structural solutions will make it possible to implement radio receivers capable of receiving and processing a microwave signal without transferring the signal to an intermediate frequency. At the same time, the required signal amplification level of 105 - 106 can be achieved, which makes it possible to achieve a signal level of 2.5-9.5 V, at which the photonic analog-to-digital converter has the best CNR and ENOB indicators.

An Infrared Near-Sensor Reservoir Computing System Based on Large-Dynamic-Space Memristor with Tens of Thousands of States for Dynamic Gesture Perception.

To efficiently process the massive amount of sensor data, it is demanding to develop a new paradigm. Inspired by neurobiological systems, an infrared near-senor reservoir computing (RC) system, consisting of infrared sensors and memristors based on single-crystalline LiTaO3 and LiNbO3 (LN) thin film respectively, is demonstrated. The analog memristor is used as a reservoir in the RC system to process sensor signals with spatiotemporal characteristics. LN crystal structure stacked with oxygen octahedra provides favorable conditions for reliable Mott variable-range hopping conduction, which provides the memristor with tens of thousands of reservoir states within a large dynamic range. With the characteristics, the analog sensor signals with high data fidelity can be directly fed to the memristive reservoir, and the spatiotemporal features can be separated and mapped. The system demonstrated a dynamic gesture perception task, achieving an accuracy of 99.6%, which highlights the great application potential of the memristor in signal sensor processing and will advance the application of artificial intelligence in sensor systems. Crystal ion slicing techniques are used to fabricate a single-crystalline thin film for both the memristor and sensor, which opens up the possibility of realizing monolithic integration of a memristor-based near-sensor computing system.

Graphene oxide based optical fiber humidity sensor having a linear response throughout a large dynamic range and optimum sensitivity.

The main objective of the present research is to develop an optical fiber relative humidity (RH) sensor with a high sensitivity, linear response over a wide dynamic range, and optimum response/recovery times by employing the simplest optical fiber sensing configuration. An optical fiber RH sensor that exploits the intensity modulation scheme through evanescent wave absorption spectroscopy and fulfills the objective is reported here. The fiber sensor employs graphene oxide (GO) diffused silica nanostructured thin sensing film as the cladding on the centrally decladded straight and uniform multimode optical fiber. Detailed experimental investigations are carried out to analyze the response characteristics of the proposed sensor. In comparison to other GO based optical fiber RH sensors, a linear response over the widest dynamic range (15.0%-95.3%RH) and shortest (fastest) response/recovery times (0.1436s/0.1547s) are observed for the proposed sensor. The linear sensitivity for the developed sensor is observed to be 0.1036dB/%RH. In addition, the proposed sensor exhibits a very good degree of reversibility, reliability, and repeatability.

An optimized fluorescent biosensor for monitoring long-chain fatty acyl-CoAs metabolism in vivo

Long-chain fatty acyl-CoAs (LCACoAs) are intermediates in lipid metabolism that exert a wide range of cellular functions. However, our knowledge about the subcellular distribution and regulatory impacts of LCACoAs is limited by a lack of methods for detecting LCACoAs in living cells and tissues. Here, we report our development of LACSerHR, a genetically encoded fluorescent biosensor that enables precise measurement of subtle fluctuations in the levels of endogenous LCACoAs in vivo. LACSerHR significantly improve the fluorescent brightness and analyte affinity, in vitro and in vivo testing showcased LACSerHR's large dynamic range. We demonstrate LACSerHR's capacity for real-time evaluation of LCACoA levels in specific subcellular compartments, for example in response to disruption of ACSL enzyme function in HEK293T cells. Moreover, we show the application of LACSerHR for sensitive measurement of elevated LCACoA levels in the livers of mouse models for two common metabolic diseases (NAFLD and type 2 diabetes). Thus, our LACSerHR sensor is a powerful, broadly applicable tool for studying LCACoAs metabolism and disease.

Broadband Electric Field Sensor With Large Dynamic Range and High Sensitivity Based on Lithium Niobate on Insulator

Broadband Electric Field Sensor With Large Dynamic Range and High Sensitivity Based on Lithium Niobate on Insulator

Picomolar-Level Sensing of Cannabidiol by Metal Nanoparticles Functionalized with Chemically Induced Dimerization Binders.

Simple and fast detection of small molecules is critical for health and environmental monitoring. Methods for chemical detection often use mass spectrometers or enzymes; the former relies on expensive equipment, and the latter is limited to those that can act as enzyme substrates. Affinity reagents like antibodies can target a variety of small-molecule analytes, but the detection requires the successful design of chemically conjugated targets or analogs for competitive binding assays. Here, we developed a generalizable method for the highly sensitive and specific in-solution detection of small molecules, using cannabidiol (CBD) as an example. Our sensing platform uses gold nanoparticles (AuNPs) functionalized with a pair of chemically induced dimerization (CID) nanobody binders (nanobinders), where CID triggers AuNP aggregation and sedimentation in the presence of CBD. Despite moderate binding affinities of the two nanobinders to CBD (equilibrium dissociation constants KD of ∼6 and ∼56 μM), a scheme consisting of CBD-AuNP preanalytical incubation, centrifugation, and electronic detection (ICED) was devised to demonstrate a high sensitivity (limit of detection of ∼100 picomolar) in urine and saliva, a relatively short sensing time (∼2 h), a large dynamic range (5 logs), and a sufficiently high specificity to differentiate CBD from its analog, tetrahydrocannabinol. The high sensing performance was achieved with the multivalency of AuNP sensing, the ICED scheme that increases analyte concentrations in a small assay volume, and a portable electronic detector. This sensing system is readily applicable for wide molecular diagnostic applications.

Highly Reliable 3D Channel Memory and Its Application in a Neuromorphic Sensory System for Hand Gesture Recognition.

Brain-inspired neuromorphic computing systems, based on a crossbar array of two-terminal multilevel resistive random-access memory (RRAM), have attracted attention as promising technologies for processing large amounts of unstructured data. However, the low reliability and inferior conductance tunability of RRAM, caused by uncontrollable metal filament formation in the uneven switching medium, result in lower accuracy compared to the software neural network (SW-NN). In this work, we present a highly reliable CoOx-based multilevel RRAM with an optimized crystal size and density in the switching medium, providing a three-dimensional (3D) grain boundary (GB) network. This design enhances the reliability of the RRAM by improving the cycle-to-cycle endurance and device-to-device stability of the I-V characteristics with minimal variation. Furthermore, the designed 3D GB-channel RRAM (3D GB-RRAM) exhibits excellent conductance tunability, demonstrating high symmetricity (624), low nonlinearity (βLTP/βLTD ∼ 0.20/0.39), and a large dynamic range (Gmax/Gmin ∼ 31.1). The cyclic stability of long-term potentiation and depression also exceeds 100 cycles (105 voltage pulses), and the relative standard deviation of Gmax/Gmin is only 2.9%. Leveraging these superior reliability and performance attributes, we propose a neuromorphic sensory system for finger motion tracking and hand gesture recognition as a potential elemental technology for the metaverse. This system consists of a stretchable double-layered photoacoustic strain sensor and a crossbar array neural network. We perform training and recognition tasks on ultrasonic patterns associated with finger motion and hand gestures, attaining a recognition accuracy of 97.9% and 97.4%, comparable to that of SW-NN (99.8% and 98.7%).

Measurement of CO2 Isotopologue Ratios Using a Hollow Waveguide-Based Mid-Infrared Dispersion Spectrometer.

We demonstrate for the first time the measurement of CO2 isotope ratios (13C/12C and 18O/16O) in a hollow waveguide (HWG) fiber using a mid-infrared heterodyne phase-sensitive dispersion spectrometer (HPSDS). A 4.329 μm interband cascade laser is used to target the absorption lines of three CO2 isotopes (13C16O2, 18O12C16O, and 12C16O2) in a 1 m long and 1 mm inner diameter HWG fiber. The detection limits are 0.29 ppm, 65.78 ppb, and 14.65 ppm with an integration time of 218 s for 13C16O2, 18O12C16O, and 12C16O2, respectively, at a modulation frequency of 160 MHz and a pressure of 230 mbar. The measurement precisions of δ13C and δ18O are 0.89 and 0.88 ‰, respectively, corresponding to an integration time of 167 s. An experimental comparison between a HPSDS and a built wavelength modulation system with second-harmonic detection (WMS-2f) is conducted. The results show that compared to the WMS-2f, the developed HPSDS exhibits a greater linear dynamic range and excellent long-term stability. This work aims to demonstrate a detection technique of CO2 isotope dispersion spectroscopy with a large dynamic range for relevant applications focusing on samples with high concentrations of CO2 (% volume fraction), such as respiratory analysis in medical diagnostics.

Interface Engineering to Drive High-Performance MXene/PbS Quantum Dot NIR Photodiode.

The realization of a controllable transparent conducting system with selective light transparency is crucial for exploring many of the most intriguing effects in top-illuminated optoelectronic devices. However, the performance is limited by insufficient electrical conductivity, low work function, and vulnerable interface of traditional transparent conducting materials, such as tin-doped indium oxide. Here, it is reported that two-dimensional (2D)titanium carbide (Ti3 C2 Tx ) MXene film acts as an efficient transparent conducting electrode for the lead sulfide (PbS) colloidal quantum dots (CQDs) photodiode with controllable near infrared transmittance. The solution-processed interface engineering of MXene and PbS layers remarkably reduces the interface defects of MXene/PbS CQDs and the carrier concentration in the PbS layer. The stable Ti3 C2 Tx /PbS CQDs photodiodes give rise to a high specific detectivity of 5.51×1012 cmW-1 Hz1/2 , a large dynamic response range of 140dB, and a large bandwidth of 0.76MHz at 940nm in the self-powered state, ranking among the most exceptional in terms of comprehensive performance among reported PbS CQDs photodiodes. In contrast with the traditional photodiode technologies, this efficient and stable approach opens a new horizon to construct widely used infrared photodiodes with CQDs and MXenes.

Design and evaluation of EMPIX2, a 100 kfps, high dynamic range pixel detector readout ASIC for electron microscopy

EMPIX2 is a novel hybrid pixel detector readout ASIC for electron microscopy with a maximum frame rate of 100 kfps and a very large dynamic range (5 × 105:1). It features 128 × 128 square pixels at a pitch of 150 μm. Adaptive gain switching and charge pump technology are applied to enhance the dynamic range. The pixels can operate in two modes: pulse mode and continuous mode. In pulse mode, ultra-fast gain switching enables a rapid response to pulsed electron sources, making it highly suitable for UEM applications. In continuous mode, the power consumption and dynamic range are optimized for STEM applications. The readout is frame-based, and digital image data is output by 64 pairs of LVDS drivers working in DDR mode at a clock frequency of 400 MHz. A dedicated data acquisition system was developed for the transmission and processing of the image data. Preliminary verification of the readout chip was performed using an on-chip calibration source.

BiTiS3 bio-transducer with explosive on-demand generation of NO gas for synergetic cancer therapy

Combined photothermal therapy and nitric oxide (NO)-mediated gas therapy has shown great potential as a cancer treatment. However, the on-demand release of NO at a high concentration presents a challenge owing to the lack of an ideal bio-transducer with a high loading capacity of NO donors and sufficient energy to induce NO release. Here, we present a new 2D BiTiS3 nanosheet that is synthesized, loaded with the NO donor (BNN6), and conjugated with PEG-iRGD to produce a multifunctional bio-transducer (BNN6-BiTiS3-iRGD) for the on-demand production of NO. The BiTiS3 nanosheets not only have a high loading capacity of NO donors (750%), but also exhibit a high photothermal conversion efficiency (59.5%) after irradiation by a 1064-nm laser at 0.5 W/cm2. As a result of the above advantages, the temporal-controllable generation of NO within a large dynamic range (from 0 to 344 μM) is achieved by adjusting power densities, which is among the highest efficiency values reported for NO generators so far. Moreover, the targeted accumulation of BNN6-BiTiS3-iRGD at tumor sites leads to spatial-controllable NO release. In vitro and in vivo assessments demonstrate synergistic NO gas therapy with mild photothermal therapy based on BNN6-BiTiS3-iRGD. Our work provides insights into the design and application of other 2D nanomaterial-based therapeutic platforms.

Adaptive high-gray image enhancement algorithm based on logarithmic mapping and simulated exposure

In the fields of industry, security, military and other areas, high gray-level low contrast images have been widely used. However, due to the large dynamic range of gray level, high noise, blurry detail information and low contrast, it brings difficulties to subsequent image enhancement, target detection and other processes. Ordinary image enhancement algorithms are only suitable for conventional 8-bit images, which are not effective to deal with high-gray and low-contrast images. To address these issues, this paper proposed an adaptive high-gray image enhancement algorithm based on logarithmic mapping and simulated exposure, which was used for processing X-ray film images, infrared images, SAR images and other high gray-level low contrast images. Firstly, a detailed algorithm model construction method was provided for high gray-level low contrast images. Secondly, in order to verify the universality of the algorithm proposed in this paper, qualitative and quantitative experimental analyses were carried out using X-ray film images, infrared images and SAR images respectively. Finally, taking the most complex infrared image in the application environment as an example, the images, enhanced by the algorithm proposed in this paper, were sent to the YOLOv8 neural network for target detection, which improved the detection accuracy. The experiment shows that the algorithm, proposed in this paper, can significantly improve the image quality of high gray-level low contrast images, the detail information is obvious and the contrast is significantly improved. Various indicators are far higher than those of traditional algorithms. At the same time, this algorithm can provide reliable technical support for applications, such as target detection and target tracking in this field.

Spatiotemporal control of RNA metabolism and CRISPR-Cas functions using engineered photoswitchable RNA-binding proteins.

RNA molecules perform various crucial roles in diverse cellular processes, from translating genetic information to decoding the genome, regulating gene expression and catalyzing chemical reactions. RNA-binding proteins (RBPs) play an essential role in regulating the diverse behaviors and functions of RNA in live cells, but techniques for the spatiotemporal control of RBP activities and RNA functions are rarely reported yet highly desirable. We recently reported the development of LicV, a synthetic photoswitchable RBP that can bind to a specific RNA sequence in response to blue light irradiation. LicV has been used successfully for the optogenetic control of RNA localization, splicing, translation and stability, as well as for the photoswitchable regulation of transcription and genomic locus labeling. Compared to classical genetic or pharmacologic perturbations, LicV-based light-switchable effectors have the advantages of large dynamic range between dark and light conditions and submicron and millisecond spatiotemporal resolutions. In this protocol, we provide an easy, efficient and generalizable strategy for engineering photoswitchable RBPs for the spatiotemporal control of RNA metabolism. We also provide a detailed protocol for the conversion of a CRISPR-Cas system to optogenetic control. The protocols typically take 2-3 d, including transfection and results analysis. Most of this protocol is applicable to the development of novel LicV-based photoswitchable effectors for the optogenetic control of other RNA metabolisms and CRISPR-Cas functions.

Synergistic Multieffect Catalytic Amplified Cathodic Electrochemiluminescence Biosensor via Target Binding-Induced Aptamer Conformational Changes for the Ultrasensitive Detection of Synthetic Cathinone.

Signal amplification is a powerful approach to increasing the detection sensitivity of electrochemiluminescence (ECL). Here, we developed synergistic multieffect catalytic strategies based on CuCo2O4 nanorod combination of Ag NPs as coreaction accelerators to fabricate an efficient covalent organic framework (PTCA-COF)-based ternary ECL biosensor. Concretely, the high redox reversibility of Co3+/Co2+ and Cu2+/Cu+ would constantly promote the decomposition of S2O82- for ECL emission. Meanwhile, the introduction of Ag NPs with excellent electrocatalytic activity further realized multiple amplification of the ECL signal. Furthermore, the good hydrogen evolution reaction (HER) ability of Ag@CuCo2O4 nanorods could accelerate the proton transmission rate of the system to amplify ECL behavior. In the presence of the target synthetic cathinone 4-chloroethcathinone (4-CEC) as the quenching ECL signal-response probe, the Ferrocene (Fc)-labeled aptamer folded into the conformationally limited stem-loop structure, bringing Fc near the ECL luminophore and resulting in quenched ECL emission. The quenching effect was connected with target-induced aptamer conformational changes and consequently reflected the target concentration. Under optimum conditions, the proposed biosensor realized a highly sensitive assay for 4-CEC with a large dynamic range from 1.0 × 10-12 to 1.0 × 10-6 g/L and a detection limit as low as 2.5 × 10-13 g/L. This study integrated multiple amplification strategies for efficient ECL enhancement, which provided a novel approach to constructing highly bioactive and sensitive sensors.

Practical Considerations for Laser-Induced Graphene Pressure Sensors Used in Marine Applications.

Small, low-power, and inexpensive marine depth sensors are of interest for a myriad of applications from maritime security to environmental monitoring. Recently, laser-induced graphene (LIG) piezoresistive pressure sensors have been proposed given their rapid fabrication and large dynamic range. In this work, the practicality of LIG integration into fieldable deep ocean (1 km) depth sensors in bulk is explored. Initially, a design of experiments (DOEs) approach evaluated laser engraver fabrication parameters such as line length, line width, laser speed, and laser power on resultant resistances of LIG traces. Next, uniaxial compression and thermal testing at relevant ocean pressures up to 10.3 MPa and temperatures between 0 and 25 °C evaluated the piezoresistive response of replicate sensors and determined the individual characterization of each, which is necessary. Additionally, bare LIG sensors showed larger resistance changes with temperature (ΔR ≈ 30 kΩ) than pressure (ΔR ≈ 1-15 kΩ), indicating that conformal coatings are required to both thermally insulate and electrically isolate traces from surrounding seawater. Sensors encapsulated with two dip-coated layers of 5 wt% polydimethylsiloxane (PDMS) silicone and submerged in water baths from 0 to 25 °C showed significant thermal dampening (ΔR ≈ 0.3 kΩ), indicating a path forward for the continued development of LIG/PDMS composite structures. This work presents both the promises and limitations of LIG piezoresistive depth sensors and recommends further research to validate this platform for global deployment.

Awake responses suggest inefficient dense coding in the mouse retina.

The structure and function of the vertebrate retina have been extensively studied across species with an isolated, ex vivo preparation. Retinal function in vivo, however, remains elusive, especially in awake animals. Here, we performed single-unit extracellular recordings in the optic tract of head-fixed mice to compare the output of awake, anesthetized, and ex vivo retinas. While the visual response properties were overall similar across conditions, we found that awake retinal output had in general (1) faster kinetics with less variability in the response latencies; (2) a larger dynamic range; and (3) higher firing activity, by ~20 Hz on average, for both baseline and visually evoked responses. Our modeling analyses further showed that such awake response patterns convey comparable total information but less efficiently, and allow for a linear population decoder to perform significantly better than the anesthetized or ex vivo responses. These results highlight distinct retinal behavior in awake states, in particular suggesting that the retina employs dense coding in vivo, rather than sparse efficient coding as has been often assumed from ex vivo studies.

High Precision and Stabilization PGC Demodulation Scheme for Fiber Optic Interferometric Sensors

Ellipse fitting algorithm (EFA) has attracted tremendous interest in phase demodulation schemes to eliminate nonlinear errors, however, there is an inherent drawback that the EFA fails to work when the desired phase signal is small. A high precision and stabilization phase generated carrier (PGC) demodulation scheme using hyper least squares (LS) fitting of ellipse is proposed for the first time, to our best knowledge. The contaminated quadrature signals obtained after mixing and low pass filtering are processed by a hyper LS based EFA to eliminate nonlinear errors. Hyper LS relies on algebraic distance minimization with a carefully chosen scale normalization and statistical bias is eliminated up to second order noise terms, which is far superior to the traditional LS. The temporary stability of the fitting result is used to resolve the drawback of the EFA. A module for judging the ellipse arc of quadrature signals is developed. The EFA is executed when the Lissajous figure is larger than 1/4 ellipse arc, otherwise the fitting result of the previous executed EFA is used to correct the ellipse. Experimental results show that the proposed scheme is highly precise and stable regardless of the desired signal amplitude. It has a high response linearity of 99.997%, a minimum detectable phase of 3.16 μrad and a large dynamic range of 123.52 dB @1 kHz & 1% THD.

Whitening method for passive water pipeline assessment using ambient noise

Previous studies have verified the feasibility of using ambient noise in water pipeline networks as natural signals to assess pipeline condition passively. This passive technology uses correlation peaks of the ambient noise as characteristics to identify pipe faults and deterioration, and it requires the noise power spectrum density (PSD) to be adequately whitened. However, conventional noise whitening methods cannot provide sufficient whitening for the ambient noise in water pipelines due to the significant noise PSD variations that are unevenly distributed across the wide relative bandwidth of the noise signals. This paper proposes a tailored whitening process for water pipeline ambient noise by applying logarithmic transforms on both the magnitude and frequency axes to compresses the large dynamic range of the PSD magnitude and bandwidth. Numerical simulations and field experiment results have verified that the proposed method can effectively whiten the noise signals in water pipelines, and accurately restore the amplitude of correlation peaks to be consistent with the theoretical derivation using white noise assumptions. The theoretical derivation also reveals the relation between the amplitudes of correlation peaks and the noise spatial distribution, fault distance and its reflection/transmission coefficients. The feasibility of estimating the reflection coefficient of pipe faults from the correlation results with appropriately whitened noise is also investigated in this paper.

Research on a capacitive MEMS pressure sensor based on through glass via

AbstractThe paper reports the fabrication and characterization of a capacitive Microelectro Mechanical Systems pressure sensor based on through glass vias (TGV), which had a large dynamic range by operating in touch mode. The substrate with TGV offers the advantage of elimination of parasitic capacitances owing to the superior insulation property of glass. The fabrication process was introduced. In particular, anodic bonding was applied in high vacuum to realize the hermetic package to obtain large operating range and high sensitivity. The performance of the sensor with a sensitive diaphragm of 700 μm × 1400 μm was characterized in the pressure range from −80 to 180 kPa. The sensitivity was determined as 0.072 pF/kPa over the range of 160 kPa with a good linearity of 97%.

Selective Mapping scheme based on Modified Forest Optimization Algorithm for PAPR reduction in FBMC system

Filter Bank Multicarrier(FBMC)is considered as one of the most standardized waveform for fifth generation (5G) mobile communication system application FBMC endures lot of nonlinear effects which occurs because of high Peak Average Power Ratio (PAPR). High value of PAPR due to the large dynamic range of multicarrier signal is one of the most significant issues in FBMC multicarrier based modulation technique. This paper presents one investigated PAPR reduction technique named as Selected Mapping (SLM) to minimize high PAPR by utilizing the complex signal divide into real and imaginary parts and then select minimum PAPR signal based on Modified Forest Optimization Algorithm (MFOA)to achieve good PAPR which can maintain the FBMC based system performance with a required Bit Error Rate (BER). The associated method was produced with the aim of optimize the phase factors so that the phase rotation operation is accomplished to minimize PAPR by fixing the MFOA into the conventional SLM. The simulation results demonstrate that the proposed technique gives better performance in terms of BER and PAPR compared to other SLM based optimization techniques.