Accepted
, , Received Date: 2025-08-14
Abstract +
This paper provides a comprehensive review of recent advances in high-performance photodetectors based on two-dimensional materials and in-sensor computing for intelligent image processing, aiming to address the challenges of the “memory wall” and “power wall” caused by the separation of sensing, storage, and computing in traditional image sensors. Traditional image processing relies on the von Neumann architecture, where a large volume of raw data generated at the sensing end must be transmitted to independent computing units or cloud platforms for processing, leading to high energy consumption, significant latency, bandwidth burden, and security risks. Owing to their atomic thickness, high carrier mobility, weak short-channel effects, and tunable optoelectronic properties, two-dimensional (2D) materials provide an ideal physical foundation for achieving function integration of perception and computation. This paper discusses the topic from three perspectives: optical signal perception, image preprocessing, and advanced image processing. In terms of optical signal perception, 2D materials and their heterostructures exhibit ultrahigh responsivity, broadband operation, and fast response in light-intensity detection, enable miniaturized spectrometers through bandgap modulation and computational spectroscopy, and achieve compact, full-polarization analysis via twisted layers and metasurface structures. In image preprocessing, 2D material devices can perform convolution and feature extraction at the sensing end through linear photoresponse, suppress noise and extend dynamic range via superlinear and sublinear responses, and mimic biological visual adaptation in spectral and polarization domains to enhance image quality and robustness. In advanced image processing, the tunable photoresponse and memristive characteristics of 2D materials enable sensor-level integration of sensing, storage, and computation, This allows for the realization of matrix-vector multiplication and convolution operations within convolutional neural networks, significantly reducing power consumption and improving efficiency. Meanwhile, by implementing spike-rate and temporal encoding of optical signals in spiking neural networks, 2D material devices can achieve event-driven image recognition and classification under low-power and low-latency conditions. Furthermore, this paper highlights the challenges faced by 2D material image sensors, including scalable fabrication, heterogeneous integration with silicon technology, array- and circuit-level optimization, environmental stability and encapsulation, and system-level implementation, while envisioning their broad application prospects in intelligent imaging, wearable electronics, autonomous driving, and biomedical diagnostics. It is concluded that with the joint progress in materials science, device engineering, and artificial intelligence, 2D materials are expected to drive the development of next-generation low-power, high-performance, intelligent image processing platforms, and to become an essential foundation for future information perception and processing technologies.
, , Received Date: 2025-06-20
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The increasing demands for high-speed imaging, aerospace, and optical communication have driven in-depth research on broadband photodetectors with high sensitivity and fast response. Two-dimensional (2D) materials have atomic-scale thickness, tunable bandgaps, and excellent carrier transport properties, making them ideal candidates for next-generation optoelectronics. However, their limited light absorption and intrinsic recombination losses remain key challenges. This paper provides an overview of recent progress of 2D-material-based broadband photodetectors. First, the fundamental optoelectronic properties of 2D materials, including bandgap modulation, carrier dynamics, and light–matter interactions, are discussed to clarify their broadband detection potential. Representative material systems, such as narrow-band gap semiconductors, 2D topological materials, and perovskites, are summarized, showing the detection ability from the ultraviolet to the mid-infrared regions. To overcome intrinsic limitations, four optimization strategies are highlighted: heterostructure engineering for efficient charge separation and extended spectral response; defect engineering to introduce mid-gap states and enhance sub-bandgap absorption; optical field enhancement through plasmonic nanostructures and optical cavities to improve responsivity; strain engineering for reversible band structure tuning, particularly suited for flexible devices. These strategies have achieved significant improvements in responsivity, detectivity, and bandwidth, with some devices implementing ultrabroadband detection and multifunctionality. In summary, 2D materials and their hybrids have shown great potential in broadband photodetection, with progress made in material innovation and device architecture optimization. The reviewed strategies—heterostructure integration, defect modulation, optical field enhancement, and strain engineering—collectively demonstrate the different ways of overcoming intrinsic limitations and improving device performance. Looking ahead to the future, the reasonable combination of these methods is expected to further expand the detection window, improve sensitivity, and achieve multifunctional operations, thereby paving the way for the multifunctional applications of the next-generation broadband photodetectors in imaging, sensing, and optoelectronic systems
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This study investigates the magnetocaloric effect-based green magnetic refrigeration technology, with a focus on Ni-Mn-Ga Heusler alloys as promising magnetic refrigerant candidates. To elucidate the role of Mn-rich composition in regulating the magnetic and magnetocaloric properties, a multi-scale computational approach integrating first-principles calculations and Monte Carlo simulations was adopted. This methodology enables a detailed analysis of how Mn atoms occupying Ni versus Ga sites influence the alloy’s microstructure, atomic magnetic moments, exchange interactions, and macroscopic magnetocaloric response. The results demonstrate that Mn site occupancy critically governs the magnetic performance: occupation of Ni sites reduces the total magnetic moment and Curie temperature, thereby diminishing the magnetic entropy change; in contrast, Mn occupying Ga sites markedly enhances both the total magnetic moment and the magnetic entropy change. Notably, the Ni8Mn7Ga1 alloy achieves a maximum magnetic entropy change of 2.32 J·kg-1·K-1 under a 2 T magnetic field, substantially surpassing that of the stoichiometric Ni8Mn4Ga4 alloy. Further electronic structure analysis reveals that Mn content variation modulates the density of states near the Fermi level, optimizes orbital hybridization and ferromagnetic exchange interactions, and consequently tailors the magnetic phase transition behavior. Critical exponent analysis confirms that the magnetic interactions are long-range in nature and tend toward mean-field behavior with compositional changes. By establishing a clear “composition-structure-magnetism-magnetocaloric performance” relationship at the atomic scale, this work provides theoretical foundations for designing high-performance, low-hysteresis magnetic refrigeration materials.
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For terahertz systems where reflected signals carry effective information, such as terahertz time-domain reflection systems and full-duplex communication systems, existing nonreciprocal terahertz devices often treat reflected signals as interference and suppress them during isolation. This makes them incompatible with the requirements of such systems for isolating incident signals while directionally extracting and detecting reflected signals. To address this limitation, this study innovatively proposes a terahertz isolator based on a magneto-optical selection–multiport architecture. The device converts linearly polarized light into a specific circular polarization state through orthogonal double gratings and, combined with the magneto-optical selectivity of InSb material, constructs a nonreciprocal transmission path. Furthermore, the magneto-optical regulation mechanism innovatively incorporates branch waveguides with multiple ports and the characteristic of regulating terahertz transmission paths, simultaneously achieving isolation of incident/reflected signals and directional extraction of reflected signals. By simulating the influence of structural dimensions and external environmental conditions on the nonreciprocal characteristics of the device, it is found that under a temperature of 250 K and a magnetic field of 0.3 T, with the structural parameters set as branch length of 170 μm, center-to-center spacings of adjacent branches of 125 μm, 125 μm, 120 μm, and 120 μm, InSb layer thickness of 5 μm, grating layer thickness of 50 μm, and substrate layer thickness of 20 μm, the device achieves a high isolation of 63.12 dB at 0.73 THz. Additionally, at 0.78 THz, the bidirectional transmission efficiency reaches 36.31%, with a 3 dB bandwidth of 0.25 THz. This device offers advantages such as high isolation, low operating magnetic field strength, and integration of dual functions. It reduces interference from incident signals on reflected signals, simplifies subsequent processing steps such as noise reduction and localization of effective reflected signals, and enhances the system's detection performance for weak signals. This provides essential support for expanding terahertz applications to more fields, including non-destructive testing and communication.
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Magnetic refrigeration technology, featuring environmental friendliness, energy efficiency and high performance, is recognized as a next-generation refrigeration technology with the potential to replace gas compression refrigeration technology. However, current magnetic refrigeration materials typically exhibit an excessively narrow phase transition temperature range (≤ 10 K), necessitating the stacking of materials with multiple compositions to meet the practical refrigeration temperature span. In this study, the typical La(Fe, Si)13-based magnetic refrigeration material was selected, and an innovative gradient laser powder bed fusion technology was adopted to 3D-print La0.70Ce0.30Fe11.65-xMnxSi1.35 alloys with horizontal compositional gradients (where the Mn content varies continuously from 0 to 0.64). Systematic characterization of their microstructure, magnetic properties, and magnetocaloric effect indicates that this technology enables controllable gradient distribution of compositions along the powder bed plane and high-throughput preparation, thereby achieving a continuous variation of the Curie temperature of the gradient alloy over a wide temperature range from 134 K to 174 K. With the increase of Mn content, the phase transition of the alloy gradually transforms from a weak first-order phase transition to a second-order phase transition, and the peak shape of the magnetic entropy change curve shifts from "sharp and high" to "broad and flat". The full width at half maximum of the temperature range expands to 83.3 K, allowing the gradient alloy to consistently maintain a high refrigeration capacity (RC ~130 J kg-1， 3 T). This study breaks through the bottlenecks of traditional material preparation and performance via gradient additive manufacturing, providing a novel technical pathway for the high-throughput preparation and performance optimization of magnetic refrigeration materials.
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The ionization process of atoms in infrared (IR) and extreme ultraviolet (XUV) two-color laser field is one of the hot topics in strong field physics. We investigate the above threshold ionization process of atoms subjected to elliptically polarized IR+XUV two-color laser fields, by employing the frequency-domain theory based on the nonperturbative quantum electrodynamics. The results show that the photoelectron energy width of each plateau can be controlled by the polarizations η1 of the IR laser. Specifically, for emission angles less than 45°, the photoelectron energy width decreases as the value η1 increases, whereas for angles more than 45°, it increases with the value η1. Furthermore, when the XUV laser changes from a linearly polarized field to a circularly polarized field, the ionization probability increases. Additionally, the energy width of photoelectrons broadens with the increase of the intensity of the IR laser, while the ionization probability increases with increasing intensity of the XUV laser, and the distance between the two plateaus increases with the increase of the frequency of the XUV laser. Meanwhile, the energy ranges of photoelectrons, as functions of emission angle, laser polarization, intensity and frequency, are predicted by using the classical energy orbital formula satisfied by electrons in the process of ionization, and these predictions are in agreement with quantum numerical results. This work provides theoretical support for the experimental study of the ionization process of atoms and molecules in IR+XUV two-color laser fields.
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Exploring effective approaches to optimize the photoelectronic properties of functional materials is crucial for advancing next-generation optoelectronic devices. However, existing modulation strategies are frequently plagued by drawbacks including complex fabrication processes. However, conventional regulation approaches often suffer from complex processing, and the intrinsic relationship between structural evolution and performance enhancement in one-dimensional transition-metal dichalcogenides (TMDs) under extreme conditions remains elusive, hindering further performance improvement. In this study, high pressure is employed as a continuously tunable and clean external field to regulate the structural and photoelectric properties of one-dimensional transition-metal dichalcogenide nanotubes (NT-WS2). Utilizing a diamond anvil cell (DAC) combined with in situ high-pressure photocurrent measurements, Raman spectroscopy, and X-ray diffraction (XRD), we systematically investigated the pressure- dependent evolution of the crystal structure and photoelectric performance.The results demonstrate a remarkable pressure-driven enhancement in the optoelectronic response of NT- WS2. With increasing pressure, the device responsivity exhibits a dramatic rise from the initial 0.53 A/W to 43.75 A/W at 13.5 GPa—nearly two orders of magnitude higher. Correspondingly, the external quantum efficiency (EQE) and specific detectivity (D*) are enhanced by approximately 67-fold and 10-fold, respectively. The synergistic in situ spectroscopic and structural analyses reveal that this pronounced improvement originates from pressure-induced bandgap narrowing due to strengthened interlayer interactions, together with improved carrier transport facilitated by the compact stacking of nanotubes. This work not only deepens the understanding of the optoelectronic evolution mechanisms of 1D TMDs under extreme conditions but also provides a novel regulatory strategy to guide the design and optimization of high-performance nano-optoelectronic devices.
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To address the issues of high dynamic power consumption and substantial occupation of silicon integration resources in traditional capacitor-containing neuronal circuits, this study proposes a capacitor-free neuronal circuit based on a charge-controlled memristor. By taking the intrinsic parameters of the charge-controlled memristor as the reference for scaling transformation, dimensionless dynamical equations were derived. The local asymptotic stability of the system was verified using Jacobian matrix eigenvalue decomposition and the Routh-Hurwitz criterion. Gaussian white noise was introduced to simulate interference for detecting coherent resonance, while energy characteristics were analyzed by combining Hamiltonian energy formulas and resistance energy consumption expressions. Additionally, the fourth-order Runge-Kutta method was employed to conduct numerical simulations.
The research results indicate that external stimuli, ionic channel conductance, and reversal potential can flexibly regulate the periodic/chaotic firing modes of the neuron. In the periodic state, the proportion of electric field energy of the charge-controlled memristor in the total energy is higher; in the chaotic state, however, the proportion of magnetic field energy of the inductive coils increases. The circuit exhibits coherent resonance under the influence of noise, and resistor is the main energy-consuming component. The conclusion confirms that the circuit is feasible in principle, with rich dynamical characteristics and good noise robustness. Changing the resistance value can improve energy efficiency while retaining multiple firing modes, which provides theoretical support and an optimization direction for the design of high-integration, low-power neuromorphic computing circuits.
The research results indicate that external stimuli, ionic channel conductance, and reversal potential can flexibly regulate the periodic/chaotic firing modes of the neuron. In the periodic state, the proportion of electric field energy of the charge-controlled memristor in the total energy is higher; in the chaotic state, however, the proportion of magnetic field energy of the inductive coils increases. The circuit exhibits coherent resonance under the influence of noise, and resistor is the main energy-consuming component. The conclusion confirms that the circuit is feasible in principle, with rich dynamical characteristics and good noise robustness. Changing the resistance value can improve energy efficiency while retaining multiple firing modes, which provides theoretical support and an optimization direction for the design of high-integration, low-power neuromorphic computing circuits.
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To reveal the correlation between the anisotropy of electromagnetic absorbing metastructures and the radar cross section (RCS) of its curved components, the typical anisotropic hexagonal honeycomb (HH) metastructure and isotropic sheet gyroid (SG) metastructure are systematically studied. Then, both conformal mapping and non-conformal mapping methods were employed for designing the conformal curved components. These designs were compared using simulation and microwave anechoic chamber testing to evaluate their RCS. The results indicate that the RCS of isotropic sheet gyroid curved components are insensitive to design methods, demonstrating strong design method and absorbing robustness; however, the RCS of anisotropic hexagonal honeycomb curved components exhibit strong dependence on design methods. Compared to anisotropic structures, metastructures with electromagnetic isotropy offer significant advantages in achieving wide-angle and robust low-scattering characteristics for curved components, with lower dependence on design and processing. This study provides important design guidance for developing high-performance radar low-scattering components.
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The Back-n white neutron facility at the China Spallation Neutron Source (CSNS) provides neutrons in the 0.3 eV –300 MeV energy range, severing as a crucial platform for neutron-induced nuclear reaction studies in China. With a flight length of about 76 m, neutrons in Endstation 2 show excellent neutron energy resolution, providing nice conditions for experiments such as neutron capture cross-section measurements relevant to astrophysical nucleosynthesis and key nuclear data. Measurements of neutron capture reactions mainly employ low- to intermediate-energy neutrons (below 1 MeV), and the precision of experimental results strongly depends on the neutron energy spectrum in this energy range. Benefiting from the stable operation of the CSNS, the neutron energy spectrum of Back-n remains highly stable over extended periods, but it also evolves with structural adjustments of the CSNS’s components such as the target and beam window. In this work, the 6Li-Si beam monitor at Back-n Endstation 2 was used to measure the low- to intermediate-energy neutron spectrum under the 50-15-40 collimator configuration in different preiods. Relative neutron energy spectra in the 0.3 eV-1 MeV range (100 bpd) were obtained before and after the proton beam window replacement in 2024 and the target structure adjustment in 2025. The unfolding threshold was extended down to 10 eV, achieving total uncertainty of 1%–6.8%. The results indicate that the new proton beam window reduced the neutron flux intensity in the eV to keV energy range and significantly altered the spectral shape, while adjustments to the target slightly increased the neutron flux intensity in the eV to keV range and marginally modified the spectral shape. Additionally, by analyzing the neutron energy spectra under two different commonly used collimator configurations, the differences in their spectral shapes were also compared. This work provides essential data support for neutron capture cross-section measurements and related studies carried out at the Back-n ES#2. The datasets presented in this paper are openly available at https://www.scidb.cn/s/ArAvAn.
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In order to develop a rapid and cost-effective new approach to produce periodic microstructures on solid surfaces, and help to understand the physical mechanism of the enhancement of laser-induced breakdown spectroscopy (LIBS) signals induced by surface periodic microstructures, in this article, spherical copper powder with about 74 μm diameter was used to imprint semispherical surface periodic microstructures on polyvinyl chloride (PVC) sheets under 15 T pressures. A platinum conducting layer about 100 nm thickness was coated on the PVC surface using a vacuum sputter coater and then nickel plates with the replicated microstructures on one surface were prepared using electroplating method. The signal enhancement effect induced by micro-structured surface in LIBS was experimentally observed and compared with that achieved while using flat surface nickel plate, the temperature and electron density of the induced plasma was measured according to Boltzmann plot method and the Stark broadening of Hα line of hydrogen. By systematically analyzing these results, it is concluded that the main physical mechanism of the signal enhancement in LIBS caused by the semi-spherical surface periodic microstructure is due to the increased surface area of the sample can be irradiated by the laser beam, leading to mass increase for the ablated sample material if compared with that of flat surface irradiated by the same laser beam. Comparative analysis was also conducted with experimental phenomena and signal enhancement mechanisms of using cylindrical surface periodic microstructures with a certain depth (20 μm diameter, 15 μm depth and 40 μm period ). It was found that the depth of the microstructure helps to achieve better signal enhancement effects. This provides useful references for subsequent microstructure parameter design in the future. Finally, lead in aqueous solution samples was detected with surface-enhanced LIBS (SENLIBS) technique, while Pb I 405.78 nm line was selected as the analytical line. In comparison with flat surface nickel substrate, 23-folds detection sensitivity and slightly improved signal reproducibility can be achieved while using nickel substrates with hemispherical surface periodic microstructure. The results indicate that nickel plates with hemispherical surface periodic microstructure show better analytical performance than flat surface nickel plates in elemental analysis of aqueous solution samples by SENLIBS.
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Hydrogenation or protonation offers a feasible pathway for exploring exotic physical functionality and phenomena within correlated oxide system through introducing an ion degree of freedom. This breakthrough endows with great potential for boosting multidisciplinary device applications in artificial intelligence, correlated electronics and energy conversions. Unlike conventional substitutional chemical doping, hydrogenation enables the controllable and reversible control over the charge-lattice-spin-orbital coupling and magnetoelectric states in correlated system, free of the solid-solution limits. Our findings identify proton evolution as a powerful tuning knob to cooperatively regulate the magnetoelectric transport properties in correlated oxide heterostructures, specifically in metastable VO2 (B)/La0.7Sr0.3MnO3 (LSMO) systems grown via laser molecular beam epitaxy (LMBE). Upon hydrogenation, correlated VO2 (B)/LSMO heterostructure undergoes a reversible magnetoelectric phase transition from a ferromagnetic half-metallic state to a weakly ferromagnetic insulating state, accompanied by a pronounced out-of-plane lattice expansion due to the incorporation of protons and the formation of O-H bonds, as confirmed by X-ray diffraction (XRD). Proton evolution extensively suppresses both the electrical conductivity and ferromagnetic order in pristine VO2 (B)/LSMO system, with a remarkable recovery through dehydrogenation via annealing in an oxygen-rich atmosphere, underscoring the high reversibility of hydrogen-induced magnetoelectric transitions. Spectroscopic analyses related to X-ray photoelectron spectroscopy (XPS) and synchrotron-based soft X-ray absorption spectroscopy (sXAS) provide further insights into the physical origin underlying the hydrogen-mediated magnetoelectric transitions. Hydrogen-related band filling in d-orbital of correlated oxides accounts for the electron localization in VO2 (B)/LSMO heterostructure through hydrogenation, while the suppression in the Mn3+-Mn4+ double exchange instead leads to the magnetic transitions. The present work not only expands the hydrogen-related phase diagram for correlated oxide system but also establishes a versatile pathway for designing exotic magnetoelectric functionalities via ionic evolution, with great potential for developing protonic devices.
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This article proposes a pattern recognition method for the superposition state orbital angular momentum (OAM) of vortex beams based on Convolutional Neural Network (CNN) and improved Vision Transformer (VIT). Organically integrating the local feature extraction advantages of CNN with the global fast classification ability of VIT driven by sparse attention mechanism, using three sets of LG beam patterns with superimposed light field intensity distribution maps of ocean turbulence distortion as input, achieving efficient and accurate recognition of end-to-end wavefront distortion. Using MATLAB numerical simulation to simulate the superposition state LG beam in ocean turbulent environment, power spectrum inversion method is used to simulate ocean turbulence, and recognition accuracy and confusion matrix are used as evaluation indicators for OAM pattern recognition. The experimental results show that the CNN-VIT model exhibits excellent performance in OAM pattern recognition accuracy under different ocean turbulence intensity, wavelength, transmission distance, and mode interval. Compared with existing CNN and VIT, the proposed model has improved recognition accuracy by 23.5% and 9.65% respectively under strong ocean turbulence conditions,exhibiting strong generalization ability under unknown ocean turbulence strengths. This demonstrates the potential application of the CNN-VIT model in OAM pattern recognition of vortex light superposition states.
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Metasurface holography based on planar optical devices has attracted considerable attention due to its potential for miniaturizing optical components and systems. However, traditional on-axis holography suffers from inherent zeroth-order diffraction and twin-image effects, which significantly degrade image quality and limit its practical applications. Off-axis metasurface holography, in contrast, provides a promising solution to overcome these limitations. In this work, we design a metasurface hologram composed of titanium dioxide (TiO2) nanopillars on a silicon dioxide (SiO2) substrate, taking advantage of TiO’s high refractive index and low optical loss in the visible range to achieve efficient phase control. The unit cell height is set to 600 nm to ensure sufficient phase accumulation, and the working wavelength is 635 nm. The hologram is constructed by mapping the continuous 0-2π phase distribution obtained from computational holography onto the unit cell array, while varying the nanopillar diameter allows full phase coverage. We systematically investigate the effect of the unit cell period on the imaging position in off-axis holography. Numerical simulations show that as the period increases from 280 nm to 350 nm, the center of the holographic image gradually shifts toward the center of the image plane. The optimal period is found to be 324 nm, at which the image is reconstructed precisely at the designed position. Further simulations with different off-axis angles (0°-45°) and varying nanopillar heights (600–2000 nm) confirm that the imaging position remains fixed at the target location, indicating that it is predominantly determined by the unit cell period rather than other structural parameters. These results demonstrate that by carefully selecting the unit cell period, the holographic image can be accurately reconstructed at a predetermined location with high image quality, providing theoretical guidance for the design of high-precision off-axis metasurface holographic imaging systems.
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