Light-field modulation and optimization near metal nanostructures utilizing spatial light modulators

Plasmonic modes within metal nanostructures play a pivotal role in various nanophotonic applications.However,a significant challenge arises from the fixed shapes of nanostructures post-fabrication,resulting in limited modes under ordinary illumination.A promising solution lies in far-field control facilitated by spatial light modulators(SLMs),which enable on-site,real-time,and non-destructive manipulation of plasmon excitation.Through the robust modulation of the incident light using SLMs,this approach enables the generation,optimization,and dynamic control of surface plasmon polariton(SPP)and localized surface plasmon(LSP)modes.The versatility of this technique introduces a rich array of tunable degrees of freedom to plasmon-enhanced spectroscopy,offering novel approaches for signal optimization and functional expansion in this field.This paper provides a comprehensive review of the generation and modulation of SPP and LSP modes through far-field control with SLMs and highlights the diverse applications of this optical technology in plasmon-enhanced spectroscopy.

Customized modulation on plasma uniformity by non-uniform magnetic field in capacitively coupled plasma

A two-dimensional fluid model based on COMSOL Multiphysics is developed to investigate the modulation of static magnetic field on plasma homogeneity in a capacitively coupled plasma(CCP)chamber. To generate a static magnetic field, direct current is applied to a circular coil located at the top of the chamber. By adjusting the magnetic field's configuration, which is done by altering the coil current and position, both the plasma uniformity and density can be significantly modulated. In the absence of the magnetic field, the plasma density exhibits an inhomogeneous distribution characterized by higher values at the plasma edge and lower values at the center. The introduction of a magnetic field generated by coils results in a significant increase in electron density near the coils. Furthermore, an increase in the sets of coils improves the uniformity of the plasma. By flexibly adjusting the positions of the coils and the applied current,a substantial enhancement in overall uniformity can be achieved. These findings demonstrate the feasibility of using this method for achieving uniform plasma densities in industrial applications.

Internal electric field modulation by copper vacancy concentration of cuprous sulfide nanosheets for enhanced selective CO_(2) photoreduction

Although the internal electric field(IEF)of photocatalysts is acknowledged as a potent driving force for photocharge separation,modulating the IEF intensity to achieve enhanced photocatalytic performances remains a challenge.Herein,cuprous sulfide nanosheets with different Cu vacancy concentration were employed to study IEF modulation and corresponding direct charge transfer.Among the samples,Cu_(1.8)S nanosheets possessed intensified IEF intensity compared with those of Cu_(2)S and Cu_(1.95)S nanosheets,suggesting that an enhanced IEF intensity could be achieved by introducing more Cu vacancies.This intensified IEF of Cu_(1.8)S nanosheets induced numerous photogenerated electrons to migrate to its surface,and the dissociative electrons were then captured by Cu vacancies,resulting in efficient charge separation spatially.In addition,the Cu vacancies on Cu_(1.8)S nanosheets accumulated electrons as active sites to lower the energy barrier of rate-determining step of CO_(2)photoreduction,leading to the selective conversion of CO_(2)to CO.Herein,the manipulation of IEF intensity through Cu vacancy concentration regulation of cuprous sulfide photocatalysts for efficient charge separation has been discussed,providing a scientific strategy to rationally improve photocata lytic performances for solar energy conversion.

Design of Protograph LDPC-Coded MIMO-VLC Systems with Generalized Spatial Modulation

This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.

High photoelectric conversion efficiency and fast relaxation time of FA_(0.4)MA_(0.6)PbI_(3) applied in ultrafast modulation of terahertz waves

Active control of terahertz(THz)waves is attracting tremendous attentions in terahertz communications and active photonic devices.Perovskite,due to its excellent photoelectric conversion performance and simple manufacturing process,has emerged as a promising candidate for optoelectronic applications.However,the exploration of perovskites in optically controlled THz modulators is still limited.In this work,the photoelectric properties and carrier dynamics of FA_(0.4)MA_(0.6)PbI_(3)perovskite films were investigated by optical pumped terahertz probe(OPTP)system.The ultrafast carrier dynamics reveal that FA_(0.4)MA_(0.6)PbI_(3)thin film exhibits rapid switching and relaxation time within picosecond level,suggesting that FA_(0.4)MA_(0.6)PbI_(3)is an ideal candidate for active THz devices with ultrafast response.Furthermore,as a proof of concept,a FA_(0.4)MA_(0.6)PbI_(3)-based metadevice with integrating plasma-induced transparency(PIT)effect was fabricated to achieve ultrafast modulation of THz wave.The experimental results demonstrated that the switching time of FA_(0.4)MA_(0.6)PbI_(3)-based THz modulator is near to 3.5 ps,and the threshold of optical pump is as low as 12.7μJ cm^(-2).The simulation results attribute the mechanism of ultrafast THz modulation to photo-induced free carriers in the FA_(0.4)MA_(0.6)PbI_(3)layer,which progressively shorten the capacitive gap of PIT resonator.This study not only illuminates the potential of FA_(0.4)MA_(0.6)PbI_(3)in THz modulation,but also contributes to the field of ultrafast photonic devices.

From VIB‑to VB‑Group Transition Metal Disulfides:Structure Engineering Modulation for Superior Electromagnetic Wave Absorption

The laminated transition metal disulfides(TMDs),which are well known as typical two-dimensional(2D)semiconductive materials,possess a unique layered structure,leading to their wide-spread applications in various fields,such as catalysis,energy storage,sensing,etc.In recent years,a lot of research work on TMDs based functional materials in the fields of electromagnetic wave absorption(EMA)has been carried out.Therefore,it is of great significance to elaborate the influence of TMDs on EMA in time to speed up the application.In this review,recent advances in the development of electromagnetic wave(EMW)absorbers based on TMDs,ranging from the VIB group to the VB group are summarized.Their compositions,microstructures,electronic properties,and synthesis methods are presented in detail.Particularly,the modulation of structure engineering from the aspects of heterostructures,defects,morphologies and phases are systematically summarized,focusing on optimizing impedance matching and increasing dielectric and magnetic losses in the EMA materials with tunable EMW absorption performance.Milestones as well as the challenges are also identified to guide the design of new TMDs based dielectric EMA materials with high performance.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

Influence of substrate effect on near-field radiative modulator based on biaxial hyperbolic materials

Relative rotation between the emitter and receiver could effectively modulate the near-field radiative heat transfer(NFRHT)in anisotropic media.Due to the strong in-plane anisotropy,natural hyperbolic materials can be used to construct near-field radiative modulators with excellent modulation effects.However,in practical applications,natural hyperbolic materials need to be deposited on the substrate,and the influence of substrate on modulation effect has not been studied yet.In this work,we investigate the influence of substrate effect on near-field radiative modulator based onα-MoO_(3).The results show that compared to the situation without a substrate,the presence of both lossless and lossy substrate will reduce the modulation contrast(MC)for different film thicknesses.When the real or imaginary component of the substrate permittivity increases,the mismatch of hyperbolic phonon polaritons(HPPs)weakens,resulting in a reduction in MC.By reducing the real and imaginary components of substrate permittivity,the MC can be significantly improved,reaching 4.64 forε_(s)=3 at t=10 nm.This work indicates that choosing a substrate with a smaller permittivity helps to achieve a better modulation effect,and provides guidance for the application of natural hyperbolic materials in the near-field radiative modulator.

Voltage-modulated polymer nanopore field-effect transistor for multi-sized nanoparticle detection

Solid-state nanopores offer a range of distinct advantages over biological nanopores,such as structural diversity and greater stability and durability;this makes them highly promising for high-resolution nanoparticle sensing.Biological nanopores can exhibit gating characteristics with stress-responsive switches and can demonstrate specificity toward particular molecules.Drawing inspiration from biological nanopores,this paper introduces a novel polymer nanopore with field-effect characteristics,leveraging a conductive polymer in its construction to showcase intriguing gating behavior.Notably,in this device,the polymer layer serves as the gate,enabling precise control over the source–drain current response inside and outside the pore by simply adjusting the gate voltage.This unique feature allows fine-tuning of the nanopore’s sensitivity to nanoparticles of varying sizes and facilitates its operation in multiple modes.Experimental results reveal that the developed polymer nanopore field-effect transistor demonstrates remarkable selectivity in detecting nanoparticles of various sizes under different applied voltages.The proposed single device demonstrates the exceptional ability to detect multiple types of nanoparticle,showcasing its immense potential for a wide range of applications in biological-particle analysis and medical diagnostics.

Interference-induced suppression of particle emission from a Bose-Einstein condensate in lattice with time-periodic modulations

Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this work,we investigate the collective particle emission from a Bose-Einstein condensate confined in a one-dimensional lattice with periodically modulated interparticle interactions.We give the regimes for discrete modes,and find that the emission can be distinctly suppressed.The configuration induces a broad band,but few particles are ejected due to the interference of the matter waves.We further qualitatively model the emission process and demonstrate the short-time behaviors.This engineering provides a way to manipulate the propagation of particles and the corresponding dynamics of condensates in lattices,and may find application in the dynamical excitation control of other nonequilibrium problems with time-periodic driving.

Enhancing quantum temporal steering via frequency modulation

Various strategies have been proposed to harness and protect space-like quantum correlations in different models under decoherence.However,little attention has been given to temporal-like correlations,such as quantum temporal steering(TS),in this context.In this work,we investigate TS in a frequency-modulated two-level system coupled to a zero-temperature reservoir in both the weak and strong coupling regimes.We analyze the impact of various frequency-modulated parameters on the behavior of TS and non-Markovian.The results demonstrate that appropriate frequency-modulated parameters can enhance the TS of the two-level system,regardless of whether the system is experiencing Markovian or non-Markovian dynamics.Furthermore,a suitable ratio between modulation strength and frequency(i.e.,all zeroes of the 0th Bessel function J_(0)(δ/?))can significantly enhance TS in the strong coupling regime.These findings indicate that efficient and effective manipulation of quantum TS can be achieved through a frequency-modulated approach.

Pit density reduction for AlN epilayers grown by molecular beam epitaxy using Al modulation method

We have investigated homoepitaxy of AlN films grown by molecular beam epitaxy on AlN/sapphire templates byadopting both the continuous growth method and the Al modulation epitaxy(AME)growth method.The continuous growthmethod encounters significant challenges in controlling the growth mode.As the precise Al/N=1.0 ratio is difficult toachieve,either the excessive Al-rich or N-rich growth mode occurs.In contrast,by adopting the AME growth method,sucha difficulty has been effectively overcome.By manipulating the supply time of the Al and nitrogen sources,we were able toproduce AlN films with much improved surface morphology.The first step of the AME method,only supplying Al atoms,is important to wet the surface and the Al adatoms can act as a surfactant.Optimization of the initial Al supply time caneffectively reduce the pit density on the grown AlN surface.The pits density dropped from 12 pits/μm^(2)to 1 pit/μm^(2)andthe surface roughness reduced from 0.72 nm to 0.3 nm in a 2×2μm^(2)area for the AME AlN film homoepitaxially grownon an AlN template.

A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for Automatic Modulation Classification

Automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation signals.The proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed model.The proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to LWNet.Furthermore, the model also has a moderate computation complexity compared with several state-of-the-art methods.

Experimental realization of fractal fretwork metasurface for sound anomalous modulation

Natural creatures and ancient cultures are full of potential sources to provide inspiration for applied sciences.Inspired by the fractal geometry in nature and the fretwork frame in ancient culture,here we design the acoustic metasurface to realize sound anomalous modulation,which manifests itself as an incident-dependent propagation behavior:sound wave propagating in the forward direction is allowed to transmit with high efficiency while in the backward direction is obviously suppressed.We quantitatively investigate the dependences of asymmetric transmission on the propagation direction,incident angle and operating frequency by calculating sound transmittance and energy contrast.This compact fractal fretwork metasurface for acoustic anomalous modulation would promote the development of integrated acoustic devices and expand versatile applications in acoustic communication and information encryption.

Microwave electrometry with Rydberg atoms in a vapor cell using microwave amplitude modulation

We have theoretically and experimentally studied the dispersive signal of the Rydberg atomic electromagneticallyinduced transparency(EIT)Autler–Townes(AT)splitting spectra obtained using amplitude modulation of the microwave(MW)electric field.In addition to the two zero-crossing points interval△f_(zeros),the dispersion signal has two positive maxima with an interval defined as the shoulder interval△f_(sho),which is theoretically expected to be used to measure a much weaker MW electric field.The relationship of the MW field strength E_(MW)and△f_(sho)is experimentally studied at the MW frequencies of 31.6 GHz and 9.2 GHz respectively.The results show that△f_(sho)can be used to characterize the much weaker E_(MW)than that of△f_(zeros)and the traditional EIT–AT splitting interval△f_(m);the minimum E_(MW)measured by△f_(sho)is about 30 times smaller than that by△f_(m).As an example,the minimum E_(MW)at 9.2 GHz that can be characterized by△f_(sho)is 0.056 mV/cm,which is the minimum value characterized by the frequency interval using a vapor cell without adding any auxiliary fields.The proposed method can improve the weak limit and sensitivity of E_(MW)measured by the spectral frequency interval,which is important in the direct measurement of weak E_(MW).

Recent Advance in Synaptic Plasticity Modulation Techniques for Neuromorphic Applications

Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years.Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation,improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions.Herein,several fascinating strategies for synap-tic plasticity modulation through chemical techniques,device structure design,and physical signal sensing are reviewed.For chemical techniques,the underly-ing mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted.Based on device structure design,the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions.Besides,integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light,strain,and temperature.Finally,considering that the relevant technology is still in the basic exploration stage,some prospects or development suggestions are put forward to promote the development of neuromorphic devices.

Improvement and security analysis of multi-ring discrete modulation continuous variable quantum secret sharing scheme

In order to avoid the complexity of Gaussian modulation and the problem that the traditional point-to-point communication DM-CVQKD protocol cannot meet the demand for multi-user key sharing at the same time, we propose a multi-ring discrete modulation continuous variable quantum key sharing scheme(MR-DM-CVQSS). In this paper, we primarily compare single-ring and multi-ring M-symbol amplitude and phase-shift keying modulations. We analyze their asymptotic key rates against collective attacks and consider the security key rates under finite-size effects. Leveraging the characteristics of discrete modulation, we improve the quantum secret sharing scheme. Non-dealer participants only require simple phase shifters to complete quantum secret sharing. We also provide the general design of the MR-DM-CVQSS protocol.We conduct a comprehensive analysis of the improved protocol's performance, confirming that the enhancement through multi-ring M-PSK allows for longer-distance quantum key distribution. Additionally, it reduces the deployment complexity of the system, thereby increasing the practical value.

Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: Radiological exploration enhanced with PCA-based machine learning in a rat femoral model

The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based implants.Thus,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities.The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model.In addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical applications.Compared to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation.The bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in humerus.In the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy site.Principal component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D scoring.The study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

Deep Learning Based Signal Detection for Quadrature Spatial Modulation System

With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. In QSM, the traditional signal detection methods sometimes are unable to meet the actual requirement of low complexity of the system. Therefore, this paper proposes a signal detection scheme for QSM systems using deep learning to solve the complexity problem. Results from the simulations show that the bit error rate performance of the proposed deep learning-based detector is better than that of the zero-forcing(ZF) and minimum mean square error(MMSE) detectors, and similar to the maximum likelihood(ML) detector. Moreover, the proposed method requires less processing time than ZF, MMSE,and ML.