bluuebunny/crossref_metadata_2025 huggingface dataset:
Few-shot transfer learning for holographic image reconstruction using a recurrent neural network
Authors: Huang Luzhe , Yang Xilin , Liu Tairan , Ozcan Aydogan
Published: June 2022

Deep learning-based methods in computational microscopy have been shown to be powerful but, in general, face some challenges due to limited generalization to new types of samples and requirements for large and diverse training data. Here, we demonstrate a few-shot transfer learning method that helps a holographic image reconstruction deep neural network rapidly generalize to new types of samples using small datasets. We pre-trained a convolutional recurrent neural network on a dataset with three different types of samples and ∼2000 unique sample field-of-views, which serves as the backbone model. By fixing the trainable parameters of the recurrent blocks and transferring the rest of the convolutional blocks of the pre-trained model, we reduced the number of trainable parameters by ∼90% compared with standard transfer learning, while achieving equivalent generalization. We validated the effectiveness of this approach by successfully generalizing to new types of samples only using 80 unique field-of-views for training, and achieved (i) ∼2.5-fold convergence speed acceleration, (ii) ∼20% computation time reduction per epoch, and (iii) improved generalization to new sample types over baseline network models trained from scratch. This few-shot transfer learning approach can potentially be applied in other microscopic imaging methods, helping to generalize to new types of samples without the need for extensive training time and data.
Long-range stray field mapping of statically magnetized nanoparticles using magnetoresistive sensor
Authors: Trisnanto Suko Bagus , Kasajima Tamon , Akushichi Taiju , Takemura Yasushi
Published: June 2022

Analyzing the spatial distribution of stray field from magnetic nanoparticles is a crucial step to design and optimize the magnetometric system for a clinical magnetic particle imaging (MPI) scanner. Here, we used a magnetoresistive (MR) sensor to probe the stray field directly from a commercial magnetic nanoparticle suspension conditioned under a static field. For a given 20 mT by a small permanent magnet, the stray field of a liquid sample with a 0.7 mgFe iron mass is in nanotesla order measured by the MR sensor at 50 mm apart from the sample, while the magnetization is comparable to several microtesla. This field decay demands picotesla sensitivity of the sensing system to record the stray field for a further distance or a smaller excitation field. Moreover, from a two-dimensional trajectory of sample and magnet movements relative to the sensor position, we confirmed that the spatial distribution of the stray field appeared to correlate with sample geometry. The distribution became broadening for low iron mass concentration of the sample. From this observation, an MR sensor proves its potential for locating the magnetic nanoparticles under a quasistatic field, which can be extensively implemented for a single-sided MPI scanner.
Uncertainty quantification of phase transition quantities from cluster weighting calculations
Authors: Blasius Jan , Zaby Paul , Dölz Jürgen , Kirchner Barbara
Published: June 2022

In this work, we investigate how uncertainties in experimental input data influence the results of quantum cluster equilibrium calculations. In particular, we focus on the calculation of vaporization enthalpies and entropies of seven organic liquids, compare two computational approaches for their calculation, and investigate how these properties are affected by changes in the experimental input data. It is observed that the vaporization enthalpies and entropies show a smooth dependence on changes in the reference density and boiling point. The reference density is found to have only a small influence on the vaporization thermodynamics, whereas the boiling point has a large influence on the vaporization enthalpy but only a small influence on the vaporization entropy. Furthermore, we employed the Gauss--Hermite estimator in order to quantify the uncertainty in thermodynamic functions that stems from inaccuracies in the experimental reference data for the example of the vaporization enthalpy of (R)-butan-2-ol. We quantify the uncertainty as 30.95 · 10−3 kJ mol−1. In addition, we compare the convergence behavior and computational effort of the Gauss–Hermite estimator with the Monte Carlo approach and show the superiority of the former. Using this study, we present how uncertainty quantification can be applied to examples from theoretical chemistry.
The performance of OPC water model in prediction of the phase equilibria of methane hydrate
Authors: Hao Xiluo , Li Chengfeng , Liu Changling , Meng Qingguo , Sun Jianye
Published: June 2022

Molecular dynamics (MD) simulations were performed to determine the three-phase coexistence line of sI methane hydrates. The MD simulations were carried out at four different pressures (4, 10, 40, and 100 MPa) by using the direct phase coexistence method. In current simulations, water was described by either TIP4P/Ice or “optimal” point charge (OPC) models and methane was described as a simple Lennard-Jones interaction site. Lorentz–Berthelot (LB) combining rules were used to calculate the parameters of the cross interactions. For the OPC model, positive deviations from the energetic LB rule were also considered based on the solubility of methane in water. For the TIP4P/Ice water model, the obtained three phase coexistence temperatures showed good agreement with experiment data at higher pressures, which is consistent with previous predictions. For the OPC water model, simulations using the classic and the modified LB parameters both showed negative deviations to the experimental values. Our results also indicated that the deviation of the T3 prediction by the OPC model was not closely correlated with the predicted melting point of ice. At 4 MPa, the modified OPC model showed a better prediction of hydrate equilibrium temperature, even better than the prediction by TIP4P/Ice. Considering the relatively higher accuracy in biomolecular MD of the OPC model, it is suggested that this model may have a better performance in hydrate MD simulations of biomolecule-based additives.
An introduction to terahertz time-domain spectroscopic ellipsometry
Authors: Chen X. , Pickwell-MacPherson E.
Published: June 2022

In the past, terahertz spectroscopy has mainly been performed based on terahertz time-domain spectroscopy systems in a transmission or a window/prism-supported reflection configuration. These conventional approaches have limitations in regard to characterizing opaque solids, conductive thin films, multiple-layer structures, and anisotropic materials. Ellipsometry is a self-reference characterization technique with a wide adaptability that can be applied for nearly all sample types. However, terahertz ellipsometry has not yet been widely applied, mainly due to the critical requirement it places on the optical setting and the large discrepancy with regard to traditional terahertz spectroscopy and conventional optical ellipsometry. In this Tutorial, we introduce terahertz time-domain spectroscopic ellipsometry from the basic concept, theory, optical configuration, error calibration to characterization methods. Experimental results on silicon wafers of different resistivities are presented as examples. This Tutorial provides key technical guidance and skills for accurate terahertz time-domain spectroscopic ellipsometry.
Classical and Quantum Optics
Authors: Mondal Partha Pratim
Published: June 2022

Classical and Quantum Optics is the first text to cover classical and quantum optics as a single subject with the premise that genuine understanding of light requires mastery of both fields. It addresses all aspects of light equally, including geometric optics, wave optics, electromagnetic optics, and quantum optics. This timely book supplies the tools needed to fully explore the behavior of light.

Classical and Quantum Optics:Approaches the topic from a conceptual perspective without assuming the reader's knowledgeIncludes relatively little math, making it ideal for students in applied sciences and engineeringStarts with well-established hypotheses and builds on them to explain physical effects and experimental observations

Classical and Quantum Optics is suitable for emerging researchers and professionals in optics, natural sciences, engineering, and interdisciplinary fields, as well as students in physics, applied sciences, and engineering.
Ray and Matrix Optics: A Simple Theory of Light
Authors: Mondal Partha Pratim
Published: June 2022

Ray or geometric optics is probably the simplest theory of light that is scientifically sound and mathematically rigorous. The theory is largely based on everyday observations and Fermat’s principle, which dictates that light takes minimal time to travel between two points. This translates into minimum distance between two points, and, hence, the path of minimum time is also the path of minimum distance. Using this as a guiding principle, the laws of reflection and refraction can be arrived at. Moreover, light propagation through a vacuum and various optical elements (e.g., lenses and optical plates), interfaces between different media, and reflection off surfaces (e.g., mirrors) can be explained. This leads to the most important imaging equation, the lensmaker’s formula, which is central to the fabrication of optical elements. To facilitate simple formulations of problems, I have extensively used sign conventions along with the paraxial ray approximation. In addition, I introduce matrix formulation for geometric optics (also known as matrix optics) for realizing complex optical systems (such as beam-expanders and objective lenses). Since aberrations are an integral part of optical system design, a generalized approach is used. In this chapter, we have incorporated all the necessary details for constructing precision optical systems.
Atom–Field Interaction
Authors: Mondal Partha Pratim
Published: June 2022

The interaction of electromagnetic fields with atomic/molecular systems is the genesis of most optical phenomena observed to date. To explain these effects, we need two broad classifications based on both classical and quantum theories. This strategy involves treating (1) fields as classical systems and atoms as quantum systems having discrete energy, (2) fields as quantum systems (particles rather than waves) and atomic systems as classical, or (3) both as quantum systems. Of course, schemes 1 and 2 are easy to solve and visualize, while scheme 3 is the most accurate description but complex in nature. In general, quantum approaches do not lead to exact solutions and require assumptions and simplifications to achieve a reasonably approximate solution. Thus, it is important to choose an appropriate strategy for solving a particular problem. The problem associated with atom–field interactions will also be subjected to different strategies to understand some of the experimentally observed phenomena such as Rabi oscillations. In this chapter, we will derive a master equation that serves as the starting point for solving a large number of problems associated with atom–field interactions.
Harnessing interpretable and unsupervised machine learning to address big data from modern X-ray diffraction
Authors: Venderley Jordan , Mallayya Krishnanand , Matty Michael , Krogstad Matthew , Ruff Jacob , Pleiss Geoff , Kishore Varsha , Mandrus David , Phelan Daniel , Poudel Lekhanath , Wilson Andrew Gordon , Weinberger Kilian , Upreti Puspa , Norman Michael , Rosenkranz Stephan , Osborn Raymond , Kim Eun-Ah
Published: June 2022

The information content of crystalline materials becomes astronomical when collective electronic behavior and their fluctuations are taken into account. In the past decade, improvements in source brightness and detector technology at modern X-ray facilities have allowed a dramatically increased fraction of this information to be captured. Now, the primary challenge is to understand and discover scientific principles from big datasets when a comprehensive analysis is beyond human reach. We report the development of an unsupervised machine learning approach, X-ray diffraction (XRD) temperature clustering (X-TEC), that can automatically extract charge density wave order parameters and detect intraunit cell ordering and its fluctuations from a series of high-volume X-ray diffraction measurements taken at multiple temperatures. We benchmark X-TEC with diffraction data on a quasi-skutterudite family of materials, (Ca

x

Sr

1
−
x

)
3
Rh
4
Sn
13
, where a quantum critical point is observed as a function of Ca concentration. We apply X-TEC to XRD data on the pyrochlore metal, Cd
2
Re
2
O
7
, to investigate its two much-debated structural phase transitions and uncover the Goldstone mode accompanying them. We demonstrate how unprecedented atomic-scale knowledge can be gained when human researchers connect the X-TEC results to physical principles. Specifically, we extract from the X-TEC–revealed selection rules that the Cd and Re displacements are approximately equal in amplitude but out of phase. This discovery reveals a previously unknown involvement of

5

d
2

Re, supporting the idea of an electronic origin to the structural order. Our approach can radically transform XRD experiments by allowing in operando data analysis and enabling researchers to refine experiments by discovering interesting regions of phase space on the fly.
Dynamical differential covariance recovers directional network structure in multiscale neural systems
Authors: Chen Yusi , Rosen Burke Q. , Sejnowski Terrence J.
Published: June 2022

Investigating neural interactions is essential to understanding the neural basis of behavior. Many statistical methods have been used for analyzing neural activity, but estimating the direction of network interactions correctly and efficiently remains a difficult problem. Here, we derive dynamical differential covariance (DDC), a method based on dynamical network models that detects directional interactions with low bias and high noise tolerance under nonstationarity conditions. Moreover, DDC scales well with the number of recording sites and the computation required is comparable to that needed for covariance. DDC was validated and compared favorably with other methods on networks with false positive motifs and multiscale neural simulations where the ground-truth connectivity was known. When applied to recordings of resting-state functional magnetic resonance imaging (rs-fMRI), DDC consistently detected regional interactions with strong structural connectivity in over 1,000 individual subjects obtained by diffusion MRI (dMRI). DDC is a promising family of methods for estimating connectivity that can be generalized to a wide range of dynamical models and recording techniques and to other applications where system identification is needed.
Who predicted what?
Authors: Wang Shan , Tang Lei
Published: June 2022

The Chinese language is a common language of Chinese people all over the world. The study of it is not only the
basis for a comprehensive understanding of its situation, but also a window to explore the development of the Chinese society.
Based on two newspapers of the Chinese mainland and Taiwan from Tagged Chinese Gigaword, this article has chosen and examined the
word 預測 yùcè ‘to predict’ to
explore “who predicated what” through comparing the similarities and differences of its collocates in the subject-predicate
relation and the verb-object relation. This study reflects the preference of different newspapers and provides a window for
looking into a period of history on both sides of the strait, which is conducive to strengthening the communication and exchanges
of Chinese communities.
Automatic medical term extraction from Vietnamese clinical texts
Authors: Vo Chau , Cao Tru , Truong Ngoc , Ngo Trung , Bui Dai
Published: June 2022

In this paper, we propose the first method for automatic Vietnamese medical term discovery and extraction from
clinical texts. The method combines linguistic filtering based on our defined open patterns with nested term extraction and
statistical ranking using C-value. It does not require annotated corpora, external data resources, parameter
settings, or term length restriction. Beside its specialty in handling Vietnamese medical terms, another novelty is that it uses
Pointwise Mutual Information to split nested terms and the disjunctive acceptance condition to extract them. Evaluated on real
Vietnamese electronic medical records, it achieves a precision of about 74% and recall of about 92% and is proved stably effective
with small datasets. It outperforms the previous works in the same category of not using annotated corpora and external data
resources. Our method and empirical evaluation analysis can lay a foundation for further research and development in Vietnamese
medical term discovery and extraction.
Lie theory for asymptotic symmetries in general relativity: The NU group
Authors: Prinz David , Schmeding Alexander
Published: June 2022

We study the Newman–Unti (NU) group from the viewpoint of infinite-dimensional geometry. The NU group is a topological group in a natural coarse topology, but it does not become a manifold and hence a Lie group in this topology. To obtain a manifold structure we consider a finer Whitney-type topology. This turns the unit component of the NU group into an infinite-dimensional Lie group. We then study the Lie theoretic properties of this group. Surprisingly, the group operations of the full NU group become discontinuous, whence the NU group does not support a Lie group structure. The NU group contains the Bondi–Metzner–Sachs (BMS) group as a subgroup, whose Lie group structure was constructed in a previous article. It is well known that the NU Lie algebra splits into a direct sum of Lie ideals of the Lie algebras of the BMS group and conformal rescalings of scri. However, the lack of a Lie group structure on the NU group implies that the BMS group cannot be embedded as a Lie subgroup therein.
Performance evaluation of a 3D split-and-recombination micromixer with asymmetric structures
Authors: Jiao Dezhao , Zhang Ruirong , Zhang Hantian , Ren Shuang , Feng Huicheng , Chang Honglong
Published: June 2022

Micromixers are widely used in lab-on-a-chip devices for analytical chemistry, bioengineering, and biomedicine to achieve rapid mixing and analysis of samples. However, the existing micromixers are mostly two-dimensional structures with low mixing efficiency. Even three-dimensional (3D) micromixers with complex structures have low mixing efficiency in the low Reynolds number range. In this paper, a 3D split-and-recombination (SAR) micromixer inspired by the horseshoe transform principle is proposed to further improve the mixing efficiency. There 3D SAR micromixers with different subchannel sizes were designed and tested in the Reynolds numbers range of 0.1–100. The optimal size of the micromixer was revealed through computational fluid dynamics simulations and experimental test results. A minimum mixing index of 91% is achieved in the range of Reynolds numbers from 0.1 to 100. Especially, for Re ⩾ 20, the mixing index is higher than 99%. The results obtained indicate that this 3D SAR micromixer with an asymmetric structure shows a satisfactory choice in the fluid mixing process of microfluidic systems, and has a potential application in the field of microchip-based biochemical analysis.
Design and investigation of dielectric modulated triple metal gate-oxide-stack Z-shaped gate horizontal pocket TFET device as a label-free biosensor
Authors: Reddy Nelaturi Nagendra , Panda Deepak Kumar
Published: June 2022

In this article, a dielectric modulated triple metal gate-oxide-stack Z-shaped gate horizontal source pocket tunnel field-effect transistor (DM-TMGOS-ZHP-TFET) structure has been investigated for the application of label free-biosensor. This work explores the advantage of gate work function engineering along with the gate-oxide-stack approach for the ZHP-TFET for the first time. An asymmetric nano-cavity is created adjacent to the source-channel junction to immobilize the target biomolecules conjugation to the proposed device. The sensitivity of the device is thoroughly investigated in terms of average subthreshold swing (SS), threshold voltage (V
th) and the switching ratio (I
on/I
off) of the proposed device with the variation of the dielectric constant value inside the nano-gap under the gate electrode. The device characteristics are investigated with different combinations of metal work functions to match the desired feature and sensitivity of the device. In addition, the sensitivity analysis of the proposed device is analyzed in the presence of both positive and negative charged biomolecules in the cavity region to study the charge effect on label-free detection of the device. A comparative study is conducted between a single metal gate (SMG) ZHP-DM-TFET biosensor with the DM-TMGOS-ZHP-TFET biosensor explores the advantage of gate-work function engineering with a gate-oxide-stack approach. Interestingly the DM-TMGOS-ZHP-TFET biosensor shows superior results with a high current ratio sensitivity of 103 which is ten times more than the SMG-ZHP-DM-TFET biosensor and this device also exhibits low subthreshold characteristics.
Stimulated Raman adiabatic passage in a quantum system near a plasmonic nanoparticle
Authors: Domenikou Natalia , Thanopulos Ioannis , Stefanatos Dionisis , Yannopapas Vassilios , Paspalakis Emmanuel
Published: June 2022

We investigate theoretically the population transfer process in a Λ-type three-level quantum system (QS) near a metallic nanosphere using the stimulated Raman adiabatic passage (STIRAP) technique. We combine density matrix quantum dynamical calculations with first-principle electromagnetic calculations, which quantify the influence of the plasmonic nanoparticle on the electric field of the pump and Stokes pulses in STIRAP as well as on the spontaneous emission rates within the Λ-type system. We study the population transfer process by varying the free-space spontaneous emission rate, the distance of the QS from the nanosphere, the polarization direction with respect to the nanoparticle surface and the relative strength of the pump and Stokes pulses used in STIRAP. We find that when the pump and Stokes fields have tangential and radial polarizations with respect to the nanosphere surface, the transfer efficiency is improved due to the increase of the decay rate of the excited state to the target state relatively to the decay to the initial state. The optimal population transfer is achieved for small interparticle distances, moderate free space spontaneous decay rate, large values of the pump Rabi frequency and small values of the Stokes Rabi frequency. When we exchange the polarization directions of the pump and Stokes fields we can still find a range of parameters where the population transfer remains efficient, but larger Stokes Rabi frequencies are necessary to overcome the increased decay rate from the excited state back to the initial state.
Observing capture with a colloidal model membrane channel
Authors: Knowles Stuart F , Fletcher Marcus , Mc Hugh Jeffrey , Earle Max , Keyser Ulrich F , Thorneywork Alice L
Published: June 2022

We use video microscopy to study the full capture process for colloidal particles transported through microfluidic channels by a pressure-driven flow. In particular, we obtain trajectories for particles as they move from the bulk into confinement, using these to map in detail the spatial velocity and concentration fields for a range of different flow velocities. Importantly, by changing the height profiles of our microfluidic devices, we consider systems for which flow profiles in the channel are the same, but flow fields in the reservoir differ with respect to the quasi-2D monolayer of particles. We find that velocity fields and profiles show qualitative agreement with numerical computations of pressure-driven fluid flow through the systems in the absence of particles, implying that in the regimes studied here particle-particle interactions do not strongly perturb the flow. Analysis of the particle flux through the channel indicates that changing the reservoir geometry leads to a change between long-range attraction of the particles to the pore and diffusion-to-capture-like behaviour, with concentration fields that show qualitative changes based on device geometry. Our results not only provide insight into design considerations for microfluidic devices, but also a foundation for experimental elucidation of the concept of a capture radius. This long standing problem plays a key role in transport models for biological channels and nanopore sensors.
Protonation enhanced superconductivity in PdTe2
Authors: Liu Zhen , Han Tao , Liu Mengqin , Huang Shuting , Zhang Zongyuan , Long Mingsheng , Hou Xingyuan , Shan Lei
Published: June 2022

Electrochemical ionic liquid gating is an effective way to intercalate ions into layered materials and modulate the properties. Here we report an enhanced superconductivity in a topological superconductor candidate PdTe2 through electrochemical gating procedure. The superconducting transition temperature was increased to approximately 3.2 K by ionic gating induced protonation at room temperature. Moreover, a further enhanced superconductivity of both superconducting transition temperature and superconducting volume fraction was observed after the gated samples were placed in a glove box for 2 months. This may be caused by the diffusion of protons in the gated single crystals, which is rarely reported in electrochemical ionic liquid gating experiments. Our results further the superconducting study of PdTe2 and may reveal a common phenomenon in the electrochemical gating procedure.
Magnetic APFC modeling and the influence of magneto-structural interactions on grain shrinkage
Authors: Backofen Rainer , Salvalaglio Marco , Voigt Axel
Published: June 2022

We derive the amplitude expansion for a phase-field-crystal (APFC) model that captures the basic physics of magneto-structural interactions. The symmetry breaking due to magnetization is demonstrated, and the characterization of the magnetic anisotropy for a bcc crystal is provided. This model enables a convenient coarse-grained description of crystalline structures, in particular when considering the features of the APFC model combined with numerical methods featuring inhomogeneous spatial resolution. This is shown by addressing the shrinkage of a spherical grain within a matrix, chosen as a prototypical system to demonstrate the influence of different magnetizations. These simulations serve as a proof of concept for the modeling of manipulation of dislocation networks and microstructures in ferromagnetic materials within the APFC model.
Development and didactic analysis of smartphone-based experimental exercises for the smart physics lab
Authors: Kaps A , Stallmach F
Published: June 2022

Smartphone-based experimental exercises were incorporated as part of the homework problems in an introductory mechanics course at a university. A quasi-experimental field study with two cohorts design was performed to measure the impact of such exercises on motivation, interest and conceptual understanding. The empirical results on learning achievement show a significant positive influence of the smartphone-based experimental exercise for the dynamics of rigid bodies topic with a medium effect size of d = 0.42. For the analysis of rotational motion topic, a positive learning achievement for both groups was evidenced, but the effect size of the smartphone-based exercise was rather small at d = 0.20 . The intrinsic and germane cognitive loads turned out to be similar at an intermediate level for both groups. However, the extrinsic cognitive load for the intervention group decreased significantly, which might be the reason why more complex experimental exercises foster conceptual understanding.
Learning about rockets, in stages
Authors: Blanco Philip R
Published: June 2022

A rocket must carry the fuel it expels in order to accelerate its structure and payload. The rocket equation relates the change in speed to the fuel mass expelled. To launch a spacecraft into Earth orbit requires a multi-stage rocket, since otherwise the mass of fuel required would be prohibitive. While the details vary among historical and current launch vehicles, the advantages and physical principles of staging can be demonstrated by analysing the simpler case of a two-stage rocket in free space. I show that a two-stage rocket produces a higher payload speed than a single-stage rocket with the same fuel and structural mass, and introduce the concept of optimal staging to maximise this speed. I also examine how mechanical energy extracted from the expelled fuel is distributed between the stages, payload capsule, and exhaust. A surprising result is that the two-stage rocket deposits more energy into the exhaust stream than its single-stage counterpart. I suggest further investigations that are appropriate for advanced high school or undergraduate students of physics or aerospace engineering. Supplementary materials are provided online for classroom use.
From atoms to stars: an interactive theatre play based on ‘The Little Prince’ novella to describe spatial thinking
Authors: Acuña-Umaña K , Gómez-Quirós C , Herrera-Sancho O A
Published: June 2022

The implementation of theatre as a didactic tool for teaching science provides a new perspective on the importance of interdisciplinary approaches in the construction of meaningful learning experiences. Gamification and collaborative work are functional strategies to teach scientific concepts in a creative way. However, there are still conceptual issues about spatial thinking that are difficult for students to understand owing to the lack of visualization of objects and their development through a characteristic chronicle. Here we show an innovative way to unifying science, technology, engineering, arts and mathematics (STEAM) careers through the development of an interactive theatrical play inspired by The Little Prince novella, to promote a culture of integration of science, theatre and literature. One of the more significant findings to emerge from this study is that the didactic strategies used are key ingredients in order to design an unique theatre play based on a link between history of atomic models and literature towards full understanding of spatial macroscales and microscales thinking. Due to the successful in the qualitative assessment results, we are devising to continue exploring the use of these didactic strategies to achieve an integrated and greater impact on students’ learning processes.
Video analysis of one-dimensional motion and collision for distance learning laboratory
Authors: Eadkhong Thammarong , Sirisathitkul Chitnarong , Danworaphong Sorasak
Published: June 2022

Video analysis is carried out for one-dimensional motion and collision experiments using Tracker. Physical variables, i.e. displacement, time, and velocity, can be deducted from the analysis and allows one to connect them to the equation of motion and energy conservation. Corresponding equations of motions are given without neglecting the effect of friction and air resistance. Their solutions are used as models for data-fitting purposes. The fitting results allow one to find the surface friction coefficient and the air resistance parameter for the first experiment and friction for the second experiment. These experiments and analyses can be implemented for at least sophomore-level physics in a university. However, if simplified by removing all resistant parts, they can be used for high-school or first-year students in a university. The video files can be distributed to students for online courses that are prevalently ongoing worldwide due to the COVID pandemic. Students can observe the experiments and analyse data at home. With scheduled online consulting sessions, students can conduct the analysis with helps from instructors.
From skating rink to physics assignment—viewing a photo from a mechanics perspective
Authors: Malmqvist Karin , Pendrill Ann-Marie
Published: June 2022

Circular motion changes the perception of up and down. For a skater, the need to lean in towards the centre of an arc constitutes an embodiment of centripetal acceleration. This paper presents a discussion between a physicist and a high-school science teacher without previous physics studies at university level. The discussions started as part of a course assignment and focused on a photo of skaters practicing a ‘wing’, which is a move in synchronised skating. The skating experiences are integrated with an understanding of the relations between radius, acceleration and the angles the total force from the ice deviates from the vertical.
A deeper look at entropy change in the free expansion of an ideal gas
Authors: Reed B Cameron
Published: June 2022

The increase in entropy during the volume-doubling free expansion of an ideal gas is a staple example of thermodynamics classes. While the result,

Δ
S
=
(
n
R
)
ln
2

, is correct, the common textbook argument which leads to it can be potentially confusing. An improved but still very simple replacement model is described here and the difficulty in the common argument is discussed.
Role of excimer formation and induced photoemission on the Ar metastable kinetics in atmospheric pressure Ar–NH3 dielectric barrier discharges
Authors: Robert Raphaël , Hagelaar Gerjan , Sadeghi Nader , Magnan Romain , Stafford Luc , Massines Françoise
Published: June 2022

Tunable diode laser absorption spectroscopy was used to record the space-and time-resolved number density of argon metastable atoms, Ar(1s3) (Paschen notation), in plane-to-plane dielectric barrier discharges (DBDs) operated in a Penning Ar–NH3 mixture at atmospheric pressure. In both low-frequency (LF 650 V, 50 kHz) discharges and dual LF–radiofrequency (RF 190 V, 5 MHz) discharges operated in α–γ mode, the density of Ar(1s3) revealed a single peak per half-period of the LF voltage, with rise and decay times in the sub-microsecond time scale. These results were compared to the predictions of a 1D fluid model based on continuity and momentum equations for electrons, argon ions (Ar+ and Ar2
+) and excited argon 1s atoms as well electron energy balance equation. Using the scheme commonly reported for Ar-based DBDs in the homogeneous regime, the Ar metastable kinetics exhibited much slower rise and decay times than the ones seen in the experiments. The model was improved by considering the fast creation of Ar2
* excimers through three-body reactions involving Ar(1s) atoms and the rapid loss of Ar2
* by vacuum ultraviolet light emission. In optically thin media for such photons, they can readily reach the dielectric barriers of the DBD electrodes and induce secondary electron emission. It is shown that Ar2
* and photoemission play a significant role not only on the Ar metastable kinetics, but also on the dominant ionization pathways and possible α–γ transition in dual frequency RF–LF discharges.
Modeling of high power impulse magnetron sputtering discharges with tungsten target
Authors: Babu Swetha Suresh , Rudolph Martin , Lundin Daniel , Shimizu Tetsuhide , Fischer Joel , Raadu Michael A , Brenning Nils , Gudmundsson Jon Tomas
Published: June 2022

The ionization region model (IRM) is applied to model a high power impulse magnetron sputtering discharge with a tungsten target. The IRM gives the temporal variation of the various species and the average electron energy, as well as internal discharge parameters such as the ionization probability and the back-attraction probability of the sputtered species. It is shown that an initial peak in the discharge current is due to argon ions bombarding the cathode target. After the initial peak, the W+ ions become the dominating ions and remain as such to the end of the pulse. We demonstrate how the contribution of the W+ ions to the total discharge current at the target surface increases with increased discharge voltage for peak discharge current densities J
D,peak in the range 0.33–0.73 A cm−2. For the sputtered tungsten the ionization probability increases, while the back-attraction probability decreases with increasing discharge voltage. Furthermore, we discuss the findings in terms of the generalized recycling model and compare to experimentally determined deposition rates and find good agreement.
All-HKMG-bounded SCR for advanced ESD protection in 14 nm FinFET technology
Authors: Du Feibo , Xie Tiantian , Wang Jun , Chang Kuan-Chang , Lin Xinnan , Hou Fei , Chen Ruibo , Han Aoran , Liu Zhiwei
Published: June 2022

In this paper, a novel all-high-K metal gate (HKMG)-bounded silicon-controlled rectifier (AHBSCR) is proposed for advanced electrostatic discharge (ESD) protection in FinFET processes. Depart from its prior arts, in AHBSCR, both the main SCR path and the triggering diode path are placed along the Fin direction, and all active areas are bounded by HKMG, thus expressing superior conduction capability under various ESD stresses and a more compact silicon footprint. Experimental results show that the proposed AHBSCR owns a suitable snapback window of 1.1 V–1.6 V, a fast turn-on speed of only 400 ps, an extreme low leakage current of less than 100 pA@-1 V as well as a figure of merit of 24.3 mA fF−1, indicating it is competent to replace the conventional FinFET diodes in rail-based ESD network to further improve the efficiency of ESD protection.
Fabrication of sheet-like ZnO/ZnS heterostructures with enhanced H2S sensing performance at low operation temperatures
Authors: Wu Xinwen , Zhao Zhen , Zhang Lei , Jiao Wanli
Published: June 2022

A sheet-like ZnO/ZnS-based sensor with a sensitive response and excellent selectivity to H2S at low operation temperatures was prepared using a hydrothermal method combined with a sulfuration process. Meanwhile, x-ray diffraction, x-ray spectroscopy, scanning electron microscopy, and transmission electron microscopy measures were carried out to characterize the crystallographic information, elemental distribution, and microstructure of the sheet-like ZnO/ZnS. Results of the gas-sensing tests show that the response value of ZnO/ZnS-6 to 10 ppm of H2S reaches 90 at 100 °C, and the effective detection limit is as low as 1 ppm. The enhanced gas-sensing performance is attributed to the sheet-like microstructure and the formation of ZnO/ZnS heterojunctions. To H2S, the prepared ZnO/ZnS sensor shows satisfactory sensitivity, selectivity, and stability, and the lower heating temperature augurs wider potential applications.
Adaptive genetic algorithm enabled tailoring of piezoelectric metamaterials for optimal vibration attenuation
Authors: Jian Yupei , Tang Lihua , Hu Guobiao , Wang Yuesheng , Aw Kean C
Published: June 2022

Piezoelectric metamaterials with shunt resonant circuits have been extensively investigated for their tunability in bandgaps. However, the vibration attenuation ability induced by the electromechanical coupling is generally weaker than that of mechanical metamaterials, limiting their applications in engineering practice. This research presents a non-uniform piezoelectric metamaterial beam with shunt circuit parameters optimized by an adaptive genetic algorithm (AGA) for tailoring the vibration attenuation zone. First, the non-uniform piezoelectric metamaterial beam is modeled for transmittance analysis and verified by the finite element method. By simultaneously tuning the resonance frequencies and the resistance of the shunt circuits, it is conceptually demonstrated that the attenuation zone can be broadened, and the undesired localized vibration modes can be mitigated. Subsequently, two optimization strategies are proposed respectively for two typical vibration scenarios. The inductances and the load resistance in the shunt circuits constitute the set of design variables and are optimized by the AGA. Dedicated case studies are carried out, and the results show that the objective-oriented circuitry parameters can greatly enrich the design freedom, and tailor the transmittance profile according to a given vibration spectra. As compared to the conventional uniform and the graded piezoelectric metamaterial beams, the proposed design provides superior vibration attenuation performance and demonstrates a promising approach for tailoring piezoelectric metamaterials systems.
Tunable hyperbolic out-of-plane deformation of 3D-printed auxetic PLA shape memory arrays
Authors: Li Zhenghong , Liu Yuheng , Lu Haibao , Shu Dong-Wei
Published: June 2022

Auxetic metamaterials attract wide attention due to their unusual mechanical behaviours. This work explores the tunability of the bidirectionally hyperbolic deformation of thin plates under uniaxial compression, instead of the Euler buckling deformation. Inspired by the horseshoe structures, through tuning the radius and thickness of the central circles of the horseshoes, as well as the thickness and subtending arc angles of the four branches, bidirectionally hyperbolic out of plane deformation was achieved together with auxetic behaviour. Finally, finite element simulations, theoretical analyses, and experimental verifications have been carried out to design the out of plane bidirectionally hyperbolic deformation by the tailorable temperature sensitivity and shape memory effect in unit cells.
Revisiting small-scale fluctuations in α-attractor models of inflation
Authors: Iacconi Laura , Assadullahi Hooshyar , Fasiello Matteo , Wands David
Published: June 2022

Cosmologicalα-attractors stand out as particularly compelling models to describe inflation in the very early universe, naturally meeting tight observational bounds from cosmic microwave background (CMB) experiments. We investigateα-attractor potentials in the presence of an inflection point, leading to enhanced curvature perturbations on small scales. We study both single- and multi-field models, driven by scalar fields living on a hyperbolic field space. In the single-field case, ultra-slow-roll dynamics at the inflection point is responsible for the growth of the power spectrum, while in the multi-field set-up we study the effect of geometrical destabilisation and non-geodesic motion in field space. The two mechanisms can in principle be distinguished through the spectral shape of the resulting scalar power spectrum on small scales. These enhanced scalar perturbations can lead to primordial black hole (PBH) production and second-order gravitational wave (GW) generation. Due to the existence of universal predictions inα-attractors, consistency with current CMB constraints on the large-scale spectral tilt implies that PBHs can only be produced with masses smaller than 108g and are accompanied by ultra-high frequency GWs, with a peak expected to be at frequencies of order 10 kHz or above.
Induced gravitational waves from the cosmic coincidence
Authors: Balaji Shyam , Silk Joseph , Wu Yi-Peng
Published: June 2022

The induced gravitational wave (GW) background from enhanced primordial scalar perturbations is one of the most promising observational consequences of primordial black hole (PBH) formation from inflation. We investigate the induced GW spectrum ΩIGW from single-field inflation in the general ultra-slow-roll (USR) framework, restricting the peak frequency band to be inside 10-3-1 Hz and saturating PBH abundance to comprise all dark matter (DM) in the ultralight asteroid-mass window. By invoking successful baryogenesis driven by USR inflation, we verify the viable parameter space for the specific density ratio between baryons and PBH DM observed today, the so-called “cosmic coincidence.” We show that the cosmic coincidence requirement bounds the spectral index n
UV in the high frequency limit, ΩIGW(f ≫ 1) ∝ f
-2n
UV
, into 0 < n
UV < 1, which implies that baryogenesis triggered by USR inflation for PBHs in the mass range of 10-16-10-12 M⊙ can be tested by upcoming Advanced LIGO and Virgo data and next generation experiments such as LISA, Einstein Telescope, TianQin and DECIGO.
A note on hidden quantum discord in two- and three-qubit systems under local filtering operations
Authors: Yang Chunyan , Xiao Youwang , Wang Jing , Li Ming , Li Lei , Shen Shuqian
Published: June 2022

One of the primary goal of quantum information theory is to understand and quantify the various correlations that exist in quantum systems. Quantum correlation is broader than quantum entanglement, and quantum discord has always attracted more attention. In this paper, we investigate the hidden properties of quantum discord. In particular, for a class of two-qubit states, we prove the existence of hidden quantum discord under local filtering operations and give sufficient conditions for the absence of hidden quantum discord. For a class of three-qubit states, we investigate hidden geometric discord and analyze its dynamic behavior under several conditions. Furthermore, by comparing two- and three-qubit systems, we discover the inconsistency of hidden discord for

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Nanosecond mid-infrared pulse generation modulated by platinum ditelluride nanosheets
Authors: Hu Jianbang , Yang Lingling , Chen Longlong , Huang Jing , Zhu Hao , Miao Lili , Zhao Chujun
Published: June 2022

We demonstrated the generation of nanosecond mid-infrared (MIR) pulse from an Er3+-doped ZrF4-BaF2-LaF3-AlF3-NaF (ZBLAN) fiber laser modulated by platinum ditelluride nanosheets experimentally. The platinum ditelluride nanosheets exhibit strong nonlinear absorption with the saturation intensity 46.5 GW cm−2 and modulation depth 27.8% at 2.8 μm wavelength, respectively. With the saturable absorber mirror fabricated by depositing the platinum ditelluride nanosheets on a gold mirror, we have obtained the stable Q-switched pulses with repetition rate of 173.4 kHz and pulse duration of 600 ns at 2.8 μm wavelength under the pump power of 5.6 W. In addition, the maximum average output power and pulse energy reach 591 mW and 3.41 μJ, respectively. The experimental results confirm that the platinum ditelluride nanosheets exhibit excellent nonlinear optical behavior towards the MIR spectral range, and may make inroads towards MIR photonics with group-10 transition-metal dichalcogenides.
Predicting Supermassive Black Hole Mass with Machine Learning Methods
Authors: He Yi , Guo Qi , Shao Shi
Published: June 2022

It is crucial to measure the mass of supermassive black holes (SMBHs) in understanding the co-evolution between the SMBHs and their host galaxies. Previous methods usually require spectral data which are expensive to obtain. We use the AGN catalog from the Sloan Digital Sky Survey project Data Release 7 (DR7) to investigate the correlations between SMBH mass and their host galaxy properties. We apply the machine learning algorithms, such as Lasso regression, to establish the correlation between the SMBH mass and various photometric properties of their host galaxies. We find an empirical formula that can predict the SMBH mass according to galaxy luminosity, colors, surface brightness, and concentration. The root-mean-square error is 0.5 dex, comparable to the intrinsic scatter in SMBH mass measurements. The 1σ scatter in the relation between the SMBH mass and the combined galaxy properties relation is 0.48 dex, smaller than the scatter in the SMBH mass versus galaxy stellar mass relation. This relation could be used to study the SMBH mass function and the AGN duty cycles in the future.