Double Resonance Research Articles

A light-temperature neuron and its adaptive regulation

Abstract The appropriate firing modes for a neuron can be excited under the external stimulus. From the viewpoint of physical, the intrinsic biophysical effects, functional encoding, and the mechanism for the transcription of external signals play an extremely important role in building reliable neuron models. In this paper, a light-temperature neuron model is proposed by connecting a phototube and a thermistor into a nonlinear circuit for investigating the information encoding and responses of neurons under the external optical signals and temperature signals. In this neuron model, a phototube is used to encode external light signals, similar to artificial eyes, and a thermistor can encode temperature intensity. Furthermore, the Hamilton energy (HE) function of neurons is calculated based on the Helmholtz’s theorem, and a self-regulation method is designed by applying the ratio of electric field energy to magnetic field energy to estimate the self-regulation of neurons. The results show that the proposed neuron can reproduce the main characteristics of biological neurons by adjusting the external stimulus. The double coherence resonance is induced under noise temperature. These results could be helpful for researching the collective behaviors in functional neural networks.

Probing coherence properties of shallow implanted NV snsembles under different oxygen terminations

Abstract Nitrogen vacancy (NV) color centers in diamond have shown great potential for various applications in quantum technology due to their long coherence times, high sensitivity to magnetic fields and atomic scale resolution. However, one major challenge in utilizing near surface NV centers is the decoherence caused by spins and charges fluctuating on the surface, which affects the spin properties of the sensors. To reduce the induced noise, various oxygen surface treatments such as low power oxygen plasma treatment and annealing under oxygen atmosphere have been explored to terminate the diamond surface and reduce its impact on NV coherence. We showed that the NV center's coherence time can be enhanced up to a factor of 3 over a large spectral range of noise. Double electron electron resonance (DEER) measurements revealed an extra source of decoherence, scaling similarly as the P1 spin bath. The improvement in coherence times is accompanied with an increase in measured ketone/ether content and reduction of sp2 signal in X-ray photoelectron spectroscopy (XPS) measurements. Finally we compared the performance of different NV ensembles and surface treatments for sensing external proton spins. The oxygen annealing is an effective procedure of enhancing the spin coherence times and reducing broad band spin noise experienced by shallow implanted ensemble NV centers in diamond.

Formamidinium Incorporates into Rb-based Non-Perovskite Phases in Solar Cell Formulations.

Organic-inorganic hybrid perovskite materials, such as formamidinium lead iodide (FAPbI3), are among the most promising emerging photovoltaic materials. However, the spontaneous phase transition from the photoactive perovskite phase to an inactive non-perovskite phase complicates the application of FAPbI3 in solar cells. To remedy this, alkali metal cations, most often Cs+, Rb+ or K+, are included during perovskite synthesis to stabilize the photoactive phase. The atomic-level mechanisms of stabilization are complex. While Cs+ dopes directly into the perovskite lattice, Rb+ does not, but instead forms an additional non-perovskite phase, and the mechanism by which Rb confers increased stability remains unclear. Here, we use 1H-87Rb double resonance NMR experiments to show that FA+ incorporates into the Rb-based non-perovskite phases (FAyRb1-yPb2Br5 and δ-FAyRb1-yPbI3) for both bromide and iodide perovskite formulations. This is demonstrated by changes in the 1H and 87Rb chemical shifts, 1H-87Rb heteronuclear correlation spectra, and 87Rb{1H} REDOR spectra. Simulation of the REDOR dephasing curves suggests up to ~60 % FA+ incorporation into the inorganic Rb-based phase for the bromide system. In light of these results, we hypothesize that the substitution of FA+ into the non-perovskite phase may contribute to the greater stability conferred by Rb salts in the synthesis of FA-based perovskites.

Formamidinium Incorporates into Rb‐based Non‐Perovskite Phases in Solar Cell Formulations

AbstractOrganic‐inorganic hybrid perovskite materials, such as formamidinium lead iodide (FAPbI3), are among the most promising emerging photovoltaic materials. However, the spontaneous phase transition from the photoactive perovskite phase to an inactive non‐perovskite phase complicates the application of FAPbI3 in solar cells. To remedy this, alkali metal cations, most often Cs+, Rb+ or K+, are included during perovskite synthesis to stabilize the photoactive phase. The atomic‐level mechanisms of stabilization are complex. While Cs+ dopes directly into the perovskite lattice, Rb+ does not, but instead forms an additional non‐perovskite phase, and the mechanism by which Rb confers increased stability remains unclear. Here, we use 1H−87Rb double resonance NMR experiments to show that FA+ incorporates into the Rb‐based non‐perovskite phases (FAyRb1‐yPb2Br5 and δ‐FAyRb1‐yPbI3) for both bromide and iodide perovskite formulations. This is demonstrated by changes in the 1H and 87Rb chemical shifts, 1H−87Rb heteronuclear correlation spectra, and 87Rb{1H} REDOR spectra. Simulation of the REDOR dephasing curves suggests up to ~60 % FA+ incorporation into the inorganic Rb‐based phase for the bromide system. In light of these results, we hypothesize that the substitution of FA+ into the non‐perovskite phase may contribute to the greater stability conferred by Rb salts in the synthesis of FA‐based perovskites.

Magnetic field sensor based on multiple Fano resonance in metal-insulator-metal waveguide coupled with cross-shape resonator

Abstract In this paper, an innovative plasmonic magnetic field sensor (MFS) that exploits a Metal-insulator-Metal (MIM) waveguide configuration with an asymmetric cross-shaped resonator is constructed. The design enables the observation of double Fano resonance in the transmission spectrum, resulting from the coupling between continuous spectrum and discrete spectrum. By incorporating magnetic fluid in the asymmetric cross-shape resonator, the Fano line shapes can be tuned by the external magnetic field. Finite-Difference Time-Domain (FDTD) is used to simulate the spectra response to external magnetic fields and geometrical sizes. The proposed structure exhibits remarkable magnetic field sensitivity of 12.1 p m / O e within the detection range of 15 O e to 199 O e . The resolution of MIM magnetic field sensors can reach 0.0826 O e . The optimal figure of merit (FOM) and maximum Q factor of the Fano dip are about 6.9 × 10 − 4 / O e and 66.74, respectively. Meanwhile, The proposed Fano resonance MFS has some advantages, including compact size, high sensitivity, and cost-effectiveness. A strong linear relationship between the magnetic field and resonance wavelength indicates that the proposed structure can find potential applications in diverse fields such as magnetic field sensors, aircraft navigation, and even nuclear energy generation.

Double Resonance of Electromagnetically Induced Transparency of Rydberg Atom in Counter-Propagating Configuration

The double resonance phenomenon of EIT is studied through the ladder three-level Rydberg system. A probe laser with the wavelength λp=852.35 nm is used to coupling the ground state 6S1/2 to the middle state 6P3/2, and a coupling laser with the wavelength λc=509.08 nm is implemented to couple the state 6P3/2 to the Rydberg state 62D5/2. A special optical scheme is designed, in which the co-propagating and counter-propagating configurations are both used. As a result, the double resonance of electromagnetically induced transparency (EIT) with the Rydberg atom is observed. By comparing the distance between the double peaks, it is found that the double resonance phenomenon comes from the Doppler effect, and the distance between the two resonance peaks in the absorption spectrum is related to the detuning of the resonant lasers.

High‐Frequency Electron Paramagnetic Resonance and Electron‐Nuclear Double Resonance Spectroscopy Study of the Ga Vacancy in β‐Ga2O3

The Ga vacancy (VGa) defect in β‐Ga2O3, generated by proton irradiation, is studied using high‐frequency electron paramagnetic resonance (EPR) and electron‐nuclear double resonance spectroscopy. The previous X‐band EPR studies of this defect, attributed to VGa2−, are extended to higher frequencies (240 GHz) and lower temperatures (T = 6 K). The spin Hamiltonian parameters of the VGa2− center are determined: electron spin S = 1/2, g‐tensor: gb = 2.0313, gc = 2.0079, and ga = 2.0025; the hyperfine interaction parameters with 2 equivalent Ga neighbors: Ab = 14.0 G, Ac = 14.6 G, and Aa* = 12.8 G for 69Ga; the superhyperfine interaction with distant Ga neighbors ASHF(69Ga) = 11 MHz; and the quadrupole interaction Qb(69Ga) = 0.32 MHz and Qb(71Ga) = 0.22 MHz. These results shall allow to refine the assignment of this center to a split vacancy or an unrelaxed VGa2− defect.

Double localized surface plasmon‒enhanced-second-harmonic generation behavior of equilateral triangular aluminum nanoprisms

This paper presents second-harmonic generation (SHG) behaviors for different-sized equilateral triangular aluminum nanoprisms. These behaviors were observed under the double localized surface plasmon (LSP) resonance condition. The SHG conversion efficiency was substantially enhanced when the excitation and SHG wavelengths were simultaneously tuned to the LSP-resonance wavelengths. The fundamental and higher-order LSP modes could be used to enhance the SHG conversion efficiency. The nonlinear light‒matter interaction associated with the double LSP resonance was numerically analyzed while focusing on the spatial overlap of the near-field distributions between the excitation and SHG wavelengths. The double LSP resonance enhanced SHG behaviors have been realized by using several elegantly designed plasmonic metal nanostructures consisting of multi-elements. Our present study demonstrates this double LSP resonance enhanced SHG behavior from a single, simple-shape triangular aluminum nanoprism.

Research on high-quality factor sensing characteristics of all-dielectric nanopore array metasurface based on POA-DELM

Abstract Based on the optical properties of symmetric structures independent of each other in the orthogonal direction, an all-dielectric nano-square hole array metasurface which is symmetric along the diagonal is proposed. By changing the size of square nanopores, the symmetry of the periodic unit structure is broken and the double Fano resonance can be excited. The influence of each structural parameter on the sensing performance of the metasurface is analyzed respectively. As the main structural parameters and performance index, the metasurface height and the lengths of the main and sub-diagonal square nanoholes are selected as the input parameters, and the figure of merit (FOM) value is used as the output value. Then the nonlinear mapping relationship between the input and the output is established through deep extreme learning machine (DELM). Different optimization algorithms are used to optimize the weighted FOM values globally. The four evaluation indicators including root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and model fit (R-squared, R2) are used to assess the training effectiveness of the model. It is shown that the indexes are 0.9986, 0.9725, 3.1612 and 0.9733 respectively, and the FOM values of the dual Fano resonance after pelican optimization algorithm ( POA ) optimization are as high as 9.88 × 103 and 1.28 × 105, which demonstrate the effectiveness of POA-DELM proposed in this paper.

Pulsed EPR Methods in the Angstrom to Nanometre Scale Shed Light on the Conformational Flexibility of a Fluoride Riboswitch.

Riboswitches control gene regulation upon external stimuli such as environmental factors or ligand binding. The fluoride sensing riboswitch from Thermotoga petrophila is a complex regulatory RNA proposed to be involved in resistance to F- cytotoxicity. The details of structure and dynamics underpinning the regulatory mechanism are currently debated. Here we demonstrate that a combination of pulsed electron paramagnetic resonance (ESR/EPR) spectroscopies, detecting distances in the angstrom to nanometre range, can probe distinct regions of conformational flexibility in this riboswitch. PELDOR (pulsed electron-electron double resonance) revealed a similar preorganisation of the sensing domain in three forms, i.e. the free aptamer, the Mg2+-bound apo, and the F--bound holo form. 19F ENDOR (electron-nuclear double resonance) was used to investigate the active site structure of the F--bound holo form. Distance distributions without a priori structural information were compared with in silico modelling of spin label conformations based on the crystal structure. While PELDOR, probing the periphery of the RNA fold, revealed conformational flexibility of the RNA backbone, ENDOR indicated low structural heterogeneity at the ligand binding site. Overall, the combination of PELDOR and ENDOR with sub-angstrom precision gave insight into structural organisation and flexibility of a riboswitch, not easily attainable by other biophysical techniques.

Radiation-Induced Paramagnetic Centers in Meso- and Macroporous Synthetic Opals from EPR and ENDOR Data

The paramagnetic defects and radiation-induced paramagnetic centers (PCs) in silica opals can play a crucial role in determining the magnetic and electronic behavior of materials and serve as local probes of their electronic structure. Systematic investigations of paramagnetic defects are essential for advancing both theoretical and practical aspects of material science. A series of silica opal samples with different geometrical parameters were synthesized and radiation-induced PCs were investigated by means of the conventional and pulsed X- and W-band electron paramagnetic resonance, and 1H/2H Mims electron-nuclear double resonance. Two groups of PCs were distinguished based on their spectroscopic parameters, electron relaxation characteristics, temperature and time stability, localization relative to the surface of silica spheres, and their origin. The obtained data demonstrate that stable radiation-induced E’ PCs can be used as sensitive probes for the hydrogen-containing fillers of the opal pores, for the development of compact radiation monitoring equipment, and for quantum technologies.

Silicon double-disk optomechanical resonators from wafer-scale double-layered silicon-on-insulator

Whispering Gallery Mode (WGM) optomechanical resonators are a promising technology for the simultaneous control and measurement of optical and mechanical degrees of freedom at the nanoscale. They offer potential for use across a wide range of applications such as sensors and quantum transducers. Double-disk WGM resonators, which host strongly interacting mechanical and optical modes co-localized around their circumference, are particularly attractive due to their high optomechanical coupling. Large-scale integrated fabrication of silicon double-disk WGM resonators has not previously been demonstrated. In this work, we present a process for the fabrication of double-layer silicon-on-insulator wafers, which we then use to fabricate functional optomechanical double silicon disk resonators with on-chip optical coupling. The integrated devices present experimentally observed optical quality factors of the order of 105 and a single-photon optomechanical coupling of approximately 15 kHz.

Double-slot micro-ring resonators with trapezoidal subwavelength grating as ultra-sensitive biochemical sensors

Silicon-based refractive index sensors are of significance in the detection of gases, biological substances and chemical compounds. Among these, optical microcavities can confine the optical field to the micrometre-scale region, and possess the advantages of high Q factor, small size and easy integration. In this paper, a trapezoidal subwavelength grating (SWG) is introduced into a slot micro-ring resonator, and the mode splitting is employed to enrich the supported standing wave modes and optimize the spatial profiles of the resonant modes. The modes’ Q factor is improved and the high sensitivity and low detection limit is achieved. The optimal trapezoidal subwavelength grating double slot micro-ring resonator (T-SWGDSMRR) structure is obtained by designing the structural parameters and analyzing their effects on the sensing performance parameters and spectral characteristics. The T-SWGDSMRR, designed for detecting the glucose solution, demonstrated a low detection limit of 3.3×10−5 RIU and an ultra-high Q factor of up to 100825, accompanied by a refractive index sensitivity of 424 nm/RIU. Finally, a cascaded double micro-ring sensor is proposed using the vernier effect, through cascading the T-SWGDSMRR with a referential ring, the sensitivity is enhanced to 12828 nm/RIU, and the limit of detection is 3.12×10−6 RIU.

Silicon-based double fano resonances photonic integrated gas sensor

The telecommunication wavelengths are crucial for developing a photonic integrated circuit (PIC). The absorption fingerprints of many gases lie within these spectral ranges, offering the potential to create a miniaturized gas sensor for PIC. This work presents novel double Fano resonances within the telecommunication band, based on silicon metasurfaces for selective gas sensing applications. Our proposed design comprises periodically coupled nanodisk and nanobar resonators mounted on a quartz substrate. Fano resonances can be engineered across the range from λ = 1.52 μm to λ = 1.7 μm by adjusting various geometrical parameters. A double detection sensor of carbon monoxide (CO) at λ = 1.566 μm and nitrous oxide (N2O) at λ = 1.674 μm is developed. The sensor exhibits exceptional refractometric sensitivity to CO of 1,735 nm/RIU with an outstanding FOM of 11,570 at the first Fano resonance (FR1). In addition, the sensor shows a sensitivity to N2O of 194 nm/RIU accompanied by an FOM of 510 at the second Fano resonance (FR2). The structure reveals absorption losses of 6.3% for CO at the FR1, indicating the sensor selectivity to CO. The sensor is less selective at FR2 and limited to spectral shifts induced by each gas type. Our proposed design holds significant promise for the development of a highly sensitive double-sensing refractometric photonic integrated gas sensor.

Tunable mid-infrared absorber based on Dirac metamaterials

Abstract In this paper, a tunable metamaterial absorber based on Dirac semimetal is proposed, which consists of three different structures, from top to bottom, namely a double semicircular Dirac semimetal resonator, a silicon dioxide (SiO2) substrate, and a continuous vanadium dioxide (VO2) reflector layer. When the Fermi energy level of the Dirac semimetal is 10\ meV, the absorber absorbs more than 90% in the 39.06-84.76\ THz range. Firstly, taking advantage of the tunability of the conductivity of the Dirac semimetal, the dynamic tuning of the absorption frequency can be achieved by changing the Fermi energy level of the Dirac semimetal without the need to optimise the geometry and remanufacture the structure. Secondly, the structure has been improved by the addition of the phase change material VO2, resulting in a much higher absorption performance of the absorber. Since vanadium dioxide is a temperature-sensitive metal oxide with an insulating phase below the phase transition temperature (about 68℃) and a metallic phase above the phase transition temperature, this paper also analyses the effect of vanadium dioxide on the absorptive performance at different temperatures, with the aim of further improving the absorber performance.

Aspartic Acid Binding on Hydroxyapatite Nanoparticles with Varying Morphologies Investigated by Solid-State NMR Spectroscopy and Molecular Dynamics Simulation.

Hydroxyapatite (HAP) exhibits a highly oriented hierarchical structure in biological hard tissues. The formation and selective crystalline orientation of HAP is a process that involves functional biomineralization proteins abundant in acidic residues. To obtain insights into the process of HAP mineralization and acidic residue binding, synthesized HAP with specific lattice planes including (001), (100), and (011) are structurally characterized following the adsorption of aspartic acid (Asp). The adsorption affinity of Asp on HAP surfaces is evaluated quantitatively and demonstrates a high dependency on the HAP morphological form. Among the synthesized HAP nanoparticles (NPs), Asp exhibits the strongest adsorption affinity to short HAP nanorods, which are composed of (100) and (011) lattice planes, followed by nanosheets with a preferential expression of the (001) facet, to which Asp displays a similar but slightly lower binding affinity. HAP nanowires, with the (100) lattice plane preferentially developed, show significantly lower affinity to Asp and evidence of multilayer adsorption compared to the previous two types of HAP NPs. A combination of solid-state NMR (SSNMR) techniques including 13C and 15N CP-MAS, relaxation measurements and 13C-31P Rotational Echo DOuble Resonance (REDOR) is utilized to characterize the molecular structure and dynamics of Asp-HAP bionano interfaces with 13C- and 15N-enriched Asp. REDOR is used to determine 13C-31P internuclear distances, providing insight into the Asp binding geometry where stronger 13C-31P dipolar couplings correlate with binding affinity determined from Langmuir isotherms. The carboxyl sites are identified as the primary binding groups, facilitated by their interaction with surface calcium sites. The Asp chelation conformations revealed by SSNMR are further refined with molecular dynamics (MD) simulation where specific models strongly agree between the SSNMR and MD models for the various surfaces.

Analysis of Low-Frequency Sound Absorption Performance and Optimization of Structural Parameters for Acoustic Metamaterials for Spatial Double Helix Resonators

Low-frequency noise absorbers often require large structural dimensions, constraining their development in practical applications. In order to improve space utilization, an acoustic metamaterial with a spatial double helix, called a spatial double helix resonator (SDHR), is proposed in this paper. An analytical model of the spatial double-helix resonator is established and verified by numerical simulations and impedance tube experiments. By comparing the acoustic absorption coefficients of the spatial double-helix resonator, it is shown that the results of the analytical model, the numerical model, and the experiments are in good agreement, proving the accuracy of the theoretical model. The effects of different structural parameters on the peak sound absorption coefficient and resonance frequency are quantitatively revealed. The impedance variation law of the model is obtained, and the resistance and reactance distributions at the resonance frequency are analyzed. In the optimization model, the Back Propagation (BP) network is used to construct the mapping between the structural parameters and the resonance frequency and sound absorption coefficient, and this is used as the constraints of the equation, which is combined with Wild Horse Optimization (WHO) to establish the BP-WHO optimization model to minimize the volume of the spatial double helix resonator. The results show that, for a given noise frequency, the optimized structural parameters enhance the space utilization without affecting the performance of the space double helix resonator.

Enhancing Spectrometer Performance with Unsupervised Machine Learning.

Solid-state NMR spectroscopy (SSNMR) is a powerful technique to probe structural and dynamic properties of biomolecules at an atomic level. Modern SSNMR methods employ multidimensional pulse sequences requiring data collection over a period of days to weeks. Variations in signal intensity or frequency due to environmental fluctuation introduce artifacts into the spectra. Therefore, it is critical to actively monitor instrumentation subject to fluctuations. Here, we demonstrate a method rooted in the unsupervised machine learning algorithm principal component analysis (PCA) to evaluate the impact of environmental parameters that affect sensitivity, resolution and peak positions (chemical shifts) in multidimensional SSNMR protein spectra. PCA loading spectra illustrate the unique features associated with each drifting parameter, while the PCA scores quantify the magnitude of parameter drift. This is demonstrated both for double (HC) and triple resonance (HCN) experiments. Furthermore, we apply this methodology to identify magnetic field B0 drift, and leverage PCA to "denoise" multidimensional SSNMR spectra of the membrane protein, EmrE, using several spectra collected over several days. Finally, we utilize PCA to identify changes in B1 (CP and decoupling) and B0 fields in a manner that we envision could be automated in the future. Overall, these approaches enable improved objectivity in monitoring NMR spectrometers, and are also applicable to other forms of spectroscopy.

Spectral prediction of all dielectric nanopore metasurface based on DBO-DNN model

Based on the optical properties of symmetric structures independent of each other in the orthogonal direction, a class of all-dielectric nanohole array metasurfaces symmetrical along the diagonal is designed. By adding nanopores of different shapes to break the symmetry of the periodic unit structure, the double Fano resonance is excited. The spectral characteristics of metasurfaces with the same structure type are studied by finitedifference timedomain (FDTD) method. The deep neural network (DNN) is used to establish the nonlinear mapping relationship between the input structural parameters and the transmission spectrum. The number of hidden layers in the DNN and the number of neurons in each layer are optimized by the dung beetle optimization (DBO) algorithm. Therefore, the number of hidden layers of the model is determined to be 5, and the number of neurons in each layer is 120, 30, 150, 60, 90, respectively. The mean square error (MSE) is used to evaluate the training effect of DNN after optimization search. After 35,000 epochs of training, MSE is reduced to 0.0003926. The influence of different gradient descent optimization algorithms on the prediction results is explored respectively, and it is found that Adamax is the most effective. The results show that the prediction model can predict the spectrum within 1 s. Compared with the traditional simulation method, the simulation time is effectively saved. Meet the requirements of efficient and rapid design of ultra-thin lenses. For the same type of metasurface structure, the transmission spectrum can be accurately predicted without multiple data sets.

Bayesian Probabilistic Inference of Nonparametric Distance Distributions in DEER Spectroscopy.

Double electron-electron resonance (DEER) spectroscopy measures distance distributions between spin labels in proteins, yielding important structural and energetic information about conformational landscapes. Analysis of an experimental DEER signal in terms of a distance distribution is a nontrivial task due to the ill-posed nature of the underlying mathematical inversion problem. This work introduces a Bayesian probabilistic inference approach to analyze DEER data, assuming a nonparametric distance distribution with a Tikhonov smoothness prior. The method uses Markov Chain Monte Carlo sampling with a compositional Gibbs sampler to determine a posterior probability distribution over the entire parameter space, including the distance distribution, given an experimental data set. This posterior contains all of the information available from the data, including a full quantification of the uncertainty about the model parameters. The corresponding uncertainty about the distance distribution is visually captured via an ensemble of posterior predictive distributions. Several examples are presented to illustrate the method. Compared with bootstrapping, it performs faster and provides slightly larger uncertainty intervals.