The current work demonstrates the mechanical, thermal, and morphological characteristics of green composites processed by injection moulding. Bamboo fibre (BF) was chemically treated with 2

Various dark matter search experiments employ phonon-based crystal detectors operated at cryogenic temperatures. Some of these detectors, including certain silicon detectors used by the SuperCDMS collaboration, are able to achieve single-charge sensitivity when a voltage bias is applied across the detector. The total amount of phonon energy measured by such a detector is proportional to the number of electron-hole pairs created by the interaction. However, crystal impurities and surface effects can cause propagating charges to either become trapped inside the crystal or create additional unpaired charges, producing non-quantized measured energy as a result. A new analytical model for describing these detector response effects in phonon-based crystal detectors is presented. This model improves upon previous versions by demonstrating how the detector response, and thus the measured energy spectrum, is expected to differ depending on the source of events. We use this model to extract detector response parameters for SuperCDMS HVeV detectors, and illustrate how this robust modelling can help statistically discriminate between sources of events in order to improve the sensitivity of dark matter search experiments.

In this paper, a 3 bit encoder was proposed which was based on double plasmon-induced transparency (PIT) effect. This structure consists of the bright -bright mode and realizes a double PIT window in the 0.1-3 THz range. Electric field distributions reveal that the double PIT effect is originated from the strong destructive interference between three bright modes, the Lorentz oscillation coupling model is utilized to confirm the finite -integration time -domain (FITD) simulation regardless of the x -polarization direction or y -polarization direction. When the incident light is x -polarized, encoding frequencies were at 0.976 THz, 1.525 THz and 2.069 THz, respectively; while in y -polarization, encoding frequencies were at 1.579 THz, 1.935 THz and 2.589 THz, respectively. Results depict that the Modulation Depth (MD) could reach 98 % regardless of the x -polarization direction or the ypolarization direction. As an electro-optical switch, the maximum MD could reach >= 98 %, the minimum IL could reach 0.35 dB, the maximum ER could reach >= 14 dB. Besides the encoder, the proposed structure is of great importance for the design of optical switches, terahertz modulators and slow light devices.

A terahertz (THz) graphene metamaterial decoder, for the first time, is presented which can achieve a 2-4 decoding function and can be used to detect the content of gaseous tetrahydrofuran (THF) in air. The characteristics of the decoder were simulated and optimized by using the finite integration time-domain (FITD) method. The performance of decoding and sensing of the device was investigated. When this device is used as a 2-4 decoder, the maximum modulation depth (MD) is 99.60%, the minimum extinction ratio (ER) is 12.63 dB, and the maximum insertion loss (IL) is 0.67 dB. When this device is used as a sensor for THF detection, the sensitivity (S) can be up to 39.90 nm center dot L/mmol, along with a quality factor (Q) of 17.1 and a detection limit (DL) as low as 0.31 mmol/L. The results show that the performance of the device in both decoding and sensing functions is relatively good. Simultaneously, due to its insensitivity to the angle of incidence, this device has an anti-interference ability in complex environments. Therefore, this device possesses certain reference significance in decoding, detection, data communication, information anti-counterfeiting, and other related fields.

This study explores the dynamics of charge transport within a cryogenic P-type Ge particle detector, fabricated from a crystal cultivated at the University of South Dakota (USD). By subjecting the detector to cryogenic temperatures and an Am-241 source, we observe evolving charge dynamics and the emergence of cluster dipole states, leading to the impact ionization process at 40 mK. Our analysis focuses on crucial parameters: the zero-field cross-section of cluster dipole states and the binding energy of these states. For the Ge detector in our investigation, the zero-field cross-section of cluster dipole states is determined to be $8.45 \times 10^{-11}\pm 4.22\times 10^{-12}~cm^2$. Examination of the binding energy associated with cluster dipole states, formed by charge trapping onto dipole states during the freeze-out process, reveals a value of $0.034 \pm 0.0017$ meV. These findings shed light on the intricate charge states influenced by the interplay of temperature and electric field, with potential implications for the sensitivity in detecting low-mass dark matter.

High accuracy and real-time Doppler frequency estimation in deep space is essential for spacecraft ranging, orbit determination and planetary atmospheric measurement. Considering the problems of frequent lose-lock, high processing cost and performance degradation of current systems, an open-loop tracking system guided by the on-line self-calibrating trajectory model is proposed to achieve deep space high accuracy real-time Doppler frequency estimation. It includes a tracking guidance model to predict the target Doppler frequency changing for signal dynamic compensation and reduce the residual frequency estimation complexity, and a multi-stages residual estimation module to improve the frequency tracking accuracy. The proposed scheme is validated by both simulation test and actual space experiment data. The real-time frequency tracking error in simulation is 75.9mHz while the tracking residuals of MEX data is 3.7~7.1mHz. It shows competitive performance to post processing schemes with mHz class accuracy.

In this paper, an absorber with multi-band, tunable, high Q, and high sensitivity, based on terahertz periodic two-dimensional patterned graphene surface plasmon resonance (SPR), is proposed. The absorber consists of a bottom metal film separated by a periodically patterned graphene metamaterial structure and a SiO2 dielectric layer, where the patterned graphene layer is etched by “+” and “L” shapes and circles. It has simple structural features that can greatly simplify the fabrication process. We have analyzed the optical properties of a graphene surface plasmon perfect metamaterial absorber based on graphene in the terahertz region using the finite-difference method in time domain (FDTD). The results show that the absorber device exhibits three perfect absorption peaks in the terahertz bands of f1 = 1.55 THz, f2 = 4.19 THz, and f3 = 6.92 THz, with absorption rates as high as 98.70%, 99.63%, and 99.42%, respectively. By discussing the effects of parameters such as the geometrical dimensions of patterned graphene metamaterial structure “+” width W1, “L” width W2, circular width R, and the thickness of the dielectric layer on the absorption performance of absorber, as well as investigating the chemical potential and relaxation time of patterned-layer graphene material, it was found that the amplitude of the absorption peaks and the frequency of resonance of absorber devices can be dynamically adjusted. Finally, we simulated the spectra as the surrounding refractive index n varied to better evaluate the sensing performance of the structure, yielding structural sensitivities up to 382 GHz/RIU. Based on this study, we find that the results of our research will open new doors for the use of multi-band, tunable, polarization-independent metamaterial absorbers that are insensitive to large-angle oblique incidence.

The SPICE/HeRALD collaboration is performing R&D to enable studies of sub-GeV dark matter models using a variety of target materials. Here we report our recent progress on instrumenting a superfluid $^4$He target mass with a transition-edge sensor based calorimeter to detect both atomic signals (scintillation) and $^4$He quasiparticle (phonon and roton) excitations. The sensitivity of HeRALD to the critical "quantum evaporation" signal from $^4$He quasiparticles requires us to block the superfluid film flow to the calorimeter. We have developed a heat-free film-blocking method employing an unoxidized Cs film, which we implemented in a prototype "HeRALD v0.1" detector of ~10 g target mass. This article reports initial studies of the atomic and quasiparticle signal channels. A key result of this work is the measurement of the quantum evaporation channel's gain of 0.15 $\pm$ 0.01, which will enable $^4$He-based dark matter experiments in the near term. With this gain the HeRALD detector reported here has an energy threshold of 145 eV at 5 sigma, which would be sensitive to dark matter masses down to 220 MeV/c$^2$.

A design is presented here that integrates a five-layer structure which can achieve multiple functions with tunable amplitudes with a dual-band band-pass filter and perfect absorber for sensing applications. When used as a band-pass filter, the design has two center frequencies at 0.708 and 1.733 THz with a 3dB bandwidth of 0.312 and 0.160 THz, respectively. Among them, the maximum transmission of the first frequency band can attain ≥90%, while that of the second frequency band exceeds 70%. Using the phase transition characteristics of VO 2 as the amplitude modulation principle, the amplitude modulation depth can reach 89.36% and 94.24%, respectively. As a sensor, a perfect absorption peak generated by this structure at 1.478 THz was used, with an absorption rate of up to 99%. Simulation results showed its sensitivity, quality factor(Q), and figure of merit (FOM) could reach 0.247 THz/RIU, 21.497, and 3.592 RIU -1 , respectively. The combination of multiple functions gives our design important application values for band-pass filters, modulators, sensors, and other fields.

A 2-bit encoder based on the plasmon-induced transparency (PIT) effect was proposed and investigated in the range from 2 to 7 THz. The Lorentz oscillation coupling model was utilized to confirm the simulation. By tuning the Fermi levels of cross1 and cross2, the 2-bit encoder was achieved. And the minimum MD was 94.73 %, the minimum ER was 12.77 dB, and the maximum IL was 0.32 dB. As a sensor, the structure had a sensitivity of up to 2.33 THz/RIU. In addition, due to the insensitivities to incidence angle and polarization angle, the encoder could be utilized to complex environments. Therefore, these results reveals that our work is significant in terahertz encoders, optical switches, sensors, slow light devices, and modulators.

In this paper, a plasmonic electro-optical encoder based on graphene at THz frequency is proposed. The surface plasmon polaritons (SPPs) in the graphene–insulator–metal structure are excited by an incident TM wave with a wavelength of 9.3 μm. Graphene plasma waveguides have extremely high confinement, relatively low losses, and high tunability. The switching mechanism is based on the application of an external voltage to locally change the chemical potential of the graphene for encoding. Setting the chemical potential to 1 eV allows SPPs to propagate while lowering the chemical potential to 0.1 eV prevents the SPPs from propagating. A 4 × 2 encoder with a minimum encoding extinction ratio (ER) of 37 dB, a maximum modulation depth (MD) of 99.99%, and a structure area of 0.8 μm2 is proposed based on the design rules and simulations using the finite-difference time-domain (FDTD) method. In terms of the obtained results, the proposed structure can be used in optical integrated circuits.

A portable monoenergetic 24 keV neutron source based on the ^124Sb-^9Be photoneutron reaction and an iron filter has been constructed and characterized. The coincidence of the neutron energy from SbBe and the low interaction cross-section with iron (mean free path up to 29 cm) makes pure iron specially suited to shield against gamma rays from ^124Sb decays while letting through the neutrons. To increase the ^124Sb activity and thus the neutron flux, a >1 GBq ^124Sb source was produced by irradiating a natural Sb metal pellet with a high flux of thermal neutrons in a nuclear reactor. The design of the source shielding structure makes for easy transportation and deployment. A hydrogen gas proportional counter is used to characterize the neutrons emitted by the source and a NaI detector is used for gamma background characterization. At the exit opening of the neutron beam, the characterization determined the neutron flux in the energy range 20-25 keV to be 5.36±0.20 neutrons per cm^2 per second and the total gamma flux to be 213±6 gammas per cm^2 per second (numbers scaled to 1 GBq activity of the ^124Sb source). A liquid scintillator detector is demonstrated to be sensitive to neutrons with incident kinetic energies from 8 to 17 keV, so it can be paired with the source as a backing detector for neutron scattering calibration experiments. This photoneutron source provides a good tool for in-situ low energy nuclear recoil calibration for dark matter experiments and coherent elastic neutrino-nucleus scattering experiments.

Memristor crossbars (MC) are being widely adopted in research for energy-efficient deep learning (DL) due to their low power and fast switching characteristics, and nonvolatile nature. MCs have been demonstrated as an excellent vector matrix multiplication engine. However, MCs encounter severe reliability challenges due to aging of their memory cells. The major contributor to MC's aging in deep learning applications is the frequent weight updates. During a weight update operation, target cells in an MC is written with new conductance values. Over time, cells degrade (called aging) and hence, their written conductance values differ from the target value in each weight-update cycle. As a result, aging drastically impacts the overall performance of MC-based deep learning thereby becoming a major obstacle to commercialadop-tionof MCs. Limited attempts have been made to address this challenge. In this paper, we introduce a centralized online test framework to locate aged cell. In addition, the proposed test framework is complimented by a novel aging-aware mapping scheme to demonstrate reliable MC-based deep learning. Experiments with standard CAD tools in conjunction with an established deep learning framework show an average of 84% success rate in identifying aged cells in the crossbar. Complemented by our aging aware mapping scheme, the percentage of erroneous cells in the crossbars was found to be significantly less compared to the crossbars without the mapping scheme.

The recent advances in manufacturing technologies give product design engineers the flexibility to model complex and intricate geometries, reducing the part count. It’s easier to assemble and less expensive when a product’s parts count is reduced, but creating a feasible assembly sequence for a revised product with different topologies requires careful consideration of many heuristics and attributes during the manufacturing process. This research proposed a novel assembly sequence planning (ASP) method for a given product, rapidly generating the feasible plan with minimum assembly levels. This method considers the possibility of assembling multiple parts at a single stage through various feasible directions, which promises reduced assembly time. The proposed method is tested on a fictitious product, and the solution is found to be more efficient than that obtained by current prominent methods.

This paper proposes a novel use of long-short term memory autoencoders coupled with a hardware watchdog timer to the enhance robustness and security of embedded software. With more and more embedded systems being rapidly deployed due to the Internet of Things boom security for embedded systems is becoming a crucial factor. The proposed technique in this paper aims to create a mechanism that can be trained in an unsupervised fashion and detect anomalous execution of embedded software. This is done through the use of long-short term memory autoencoders and a hardware watchdog timer. The proposed technique is evaluated in two scenarios: the first is for detecting generic arbitrary code execution. It can accomplish this with an average accuracy of 91%. The second scenario detecting when there is a malfunction and the program starts executing instructions randomly. It can detect this with an average of accuracy of 88%.

Low mass nuclear recoil dark matter and coherent-elastic-neutrino-nucleus-scattering (CE nu NS) searches confront similar challenges in choosing ultra-low threshold and large-mass detectors. We report experimental results from a 100 g single-crystal sapphire detector design with a diameter of 76 mm and thickness of 4 mm instrumented with transition edge sensors (TES). Sapphire is a crystal of aluminum oxide (Al2O3) and has been found to be a good candidate for light mass dark matter search experiments due to its lower atomic mass compared to other detector materials such as germanium and silicon. This new phonon-assisted sapphire detector was characterized to yield a baseline recoil energy resolution of 28.4 +/- 0.4 eV. The detector is designed to be sensitive to low-energy rare interactions with an intention to investigate the low-mass region of dark matter phase-space and search for CE nu NS at the reactor site.

In this paper, two parallel graphene strip structures are adopted to achieve tunable plasma-induced transparency (PIT) sensors in the terahertz band. Both graphene bands act as bright modes, and a PIT window appears due to the weak hybridization between them. A Lorentzian oscillation coupling model is fitted to the simulation results of the proposed structure by the finite-difference time-domain (FDTD) method and is in good agreement with the simulation results. The performance of the PIT system can be controlled by tuning the geometrical parameters of the structure. In addition, the resonant frequency of the PIT window can be dynamically adjusted by changing the chemical potential and carrier mobility of the graphene strips. When the chemical potential of graphene increases from 0.2 eV to 1 eV, the amplitude modulation depth of the PIT window (2.832 THz, 3.684 THz, and 4.386 THz) can reach 92.39%, 96.14%, and 90.4%, respectively. Furthermore, due to its dispersion characteristics, the realized PIT window has a sensitive response to the surrounding medium, and the sensitivity can be as high as 1.25 THz/RIU. This PIT effect-based graphene microstructure has important implications for the future design of terahertz modulators, optical switches, and ultrasensitive sensors.

A portable monoenergetic 24 keV neutron source based on the 124 Sb- 9 Be photoneutron reaction and an iron filter has been constructed and characterized. The coincidence of the neutron energy from SbBe and the low interaction cross-section with iron (mean free path up to 29 cm) makes pure iron specially suited to shield against gamma rays from 124 Sb decays while letting through the neutrons. To increase the 124 Sb activity and thus the neutron flux, a >1 GBq 124 Sb source was produced by irradiating a natural Sb metal pellet with a high flux of thermal neutrons in a nuclear reactor. The design of the source shielding structure makes for easy transportation and deployment. A hydrogen gas proportional counter is used to characterize the neutrons emitted by the source and a NaI detector is used for gamma background characterization. At the exit opening of the neutron beam, the characterization determined the neutron flux in the energy range 20–25 keV to be 6.00±0.30 neutrons per cm 2 per second and the total gamma flux to be 245±8 gammas per cm 2 per second (numbers scaled to 1 GBq activity of the 124 Sb source). A liquid scintillator detector is demonstrated to be sensitive to neutrons with incident kinetic energies from 8 to 17 keV, so it can be paired with the source as a backing detector for neutron scattering calibration experiments. This photoneutron source provides a good tool for in-situ low energy nuclear recoil calibration for dark matter experiments and coherent elastic neutrino-nucleus scattering experiments.

We present a new analysis of previously published of SuperCDMS data using a profile likelihood framework to search for sub-GeV dark matter (DM) particles through two inelastic scattering channels: bremsstrahlung radiation and the Migdal effect. By considering these possible inelastic scattering channels, experimental sensitivity can be extended to DM masses that are undetectable through the DM-nucleon elastic scattering channel, given the energy threshold of current experiments. We exclude DM masses down to $220~\textrm{MeV}/c^2$ at $2.7 \times 10^{-30}~\textrm{cm}^2$ via the bremsstrahlung channel. The Migdal channel search provides overall considerably more stringent limits and excludes DM masses down to $30~\textrm{MeV}/c^2$ at $5.0 \times 10^{-30}~\textrm{cm}^2$.

Research on artificial neural network computing based on conventional integrated circuit chips has made significant progress, but it faces technical bottlenecks such as reduced energy consumption, computing speed, and efficiency. So, it is seeking integrated chips based on optical interconnections to solve the current dilemma. Fortunately, the small size and very localized graphene surface plasmon waves offer the possibility of optical integrated chips. In this paper, we propose a graphene-based one-bit optical numerical comparator. The comparator is located on the top of a 0.4-μm2 rectangular dielectric layer, mainly consisting of Y-shaped graphene nanoribbons. The on/off effect of the graphene nanoribbons is achieved by applying an external voltage to change the chemical potential energy of the graphene switching bands. The proposed optical numerical comparator with 9.55-μm TM mode light achieves a minimum extinction ratio of 31.12 dB and amplitude modulation of 0.77 dB, as shown by the finite-difference time-domain (FDTD) method. Compared with the current optical numerical comparators, it has the advantages of a high extinction ratio, small size, low loss, and high stability. In addition, the effect of process deviation of graphene nanoribbons on the reliability of the designed optical numerical comparator is analyzed by simulation. It is beneficial to developing integrated photonic devices and has some significance for developing ultra-high-frequency and integrating artificial neural network computing.