bluuebunny/crossref_metadata_2025 huggingface dataset:
Switching field distribution of ultradense arrays of single-crystalline magnetic nanowires
Authors: Pierrot A. , Yi D. , Peres L. , Soulantica K. , Cours R. , Warot-Fonrose B. , Marcelot C. , Respaud M. , Béron F. , Blon T.
Published: June 2023

Ultradense arrays of magnetic nanoelements present considerable interest for extending areal densities in magnetic recording media, provided that they display high switching fields and corresponding low standard deviations. Here, we report the switching field distribution of bottom–up synthesized single-crystalline vertical Co nanowires self-organized in 2D hexagonal superlattices. The combined shape and Co hexagonal compact magnetocrystalline anisotropies in individual nanowires of diameter as small as 6 nm define a robust perpendicular magnetic anisotropy despite important interactions in superlattices of 10 × 1012 NWs/in2. Using quantitative analysis of temperature-dependent first-order reversal curves, we capture the switching field distribution in this dipolar-coupled perpendicularly magnetized nanomagnets. First, the interwire dipolar interactions are treated separately and show a dominant mean field character with temperature independent amplitudes that scale with the nanowire packing fraction. Then, the intrinsic switching field distribution, namely, independent of interwire interactions, is determined as a function of temperature in the 5–300 K range. The mean value and deviation are both found to be driven by the intrawire dipolar interaction and the temperature-dependent uniaxial magnetocrystalline anisotropy, but of smaller amplitudes than those expected from bulk behavior. With coercive fields ranging between 0.3 and 0.8 T, the switching field deviations relative to coercivity reach 20%, which is a moderate value regarding pitch arrays as small as 8 nm.
Revisiting the Van Vleck second moment for characterizing molecular motion in organic solids
Authors: Sturniolo Simone , Wickins Helen M. , Hodgkinson Paul
Published: June 2023

Van Vleck’s classic theory of the second moment of lineshapes in 1H nuclear magnetic resonance (NMR) is reworked in a form that allows the effect of rapid molecular motion on second moments to be calculated in a semi-analytical fashion. This is much more efficient than existing approaches and also extends previous analyses of (non-dynamic) dipolar networks in terms of site-specific root-sum-square dipolar couplings. The non-local nature of the second moment means that it can discriminate between overall motions that are difficult to discriminate using alternative approaches, such as measurements of NMR relaxation. The value of reviving second moment studies is illustrated on the plastic solids diamantane and triamantane. In the case of triamantane, straightforward measurements of 1H lineshapes on milligram samples show that the molecules in the higher temperature phase undergo multi-axis jumps, information that is not accessible either to diffraction studies or to alternative NMR approaches. The efficiency of the computational methods means that the second moments can be calculated using a readily extensible and open-source Python code.
Asymmetric magnetic-field-induced phase transformation in Fe48Mn24Ga28 Heusler alloy
Authors: Li Weike , Zhang Yajiu , Song Linxuan , Xi Xuekui , Lau Yong-Chang , Wang Wenhong , Wu Guangheng
Published: June 2023

We report on the conceptual design and experimental realization of a ternary Heusler-based ferromagnetic martensitic phase transformation alloy Fe48Mn24Ga28 that exhibits asymmetric magnetostructural coupling between the forward austenite-to-martensite and the reverse martensite-to-austenite phase transformations. By tuning the Curie temperature of the high-temperature austenite to be within the thermal hysteresis of the first-order phase transformation, dissimilar change in magnetization can be associated with the forward and reverse phase transformations, respectively. We show that such an asymmetry leads to enlargement of the thermal hysteresis with an applied external magnetic field. Furthermore, partly due to the field-enhanced thermal hysteresis, the magnetic-field-induced martensitic phase transformation is irreversible in such a system. This work suggests the intricate correlation between magnetostructural coupling, thermal hysteresis, and magnetic-field-induced phase transformation, which can be exploited for designing magnetic phase transformation alloys that show extended functionalities.
Organic–inorganic hybrid cathode interlayer for efficient flexible inverted organic solar modules
Authors: Zhang Lin , Yang Fang , Deng Wen , Guo Xueliang , He Yuxin , Zhou Jixuan , Li Haojie , Zhang Yong , Zhou Ke , Zhou Conghua , Zou Yingping , Yang Junliang , Hu Xiaotian , Ma Wei , Yuan Yongbo
Published: June 2023

Organic solar cells (OSC) have great potential for flexible and wearable electronics due to their significant energy supply. However, the brittleness of inorganic electron transport layers (ETL) and their large-area production make it difficult to use them in flexible inverted OSCs. Herein, an organic–inorganic hybrid cathode interlayer of incorporating poly(4-vinylphenol) (P4VP) into the ZnO precursor solution was developed. The addition of P4VP improves the conductibility of ETL and facilitates the favorable vertical component distribution of active layer on the ZnO:P4VP substrate. Thus, the blade-coated OSC based on ZnO:P4VP performs better than the ZnO-based OSC in terms of photovoltaic performance and thickness insensitivity. The P4VP acts as an adhesive in ZnO grain boundaries and eliminates cracks in the bent ETL, leading to a significantly improved mechanical flexibility. Consequently, the ZnO:P4VP-based large-area flexible OSC achieves a power conversion efficiency of 14.05% and retains 80% of its initial efficiency after 1000 bending cycles, which is much better than that based on pristine ZnO (12.26%, 44%). Furthermore, flexible inverted organic solar modules were fabricated and achieved a considerable efficiency of 12.01%. These findings provide a general approach for using inorganic materials in flexible and wearable electronics.
Measurement of surface chirality at near-normal incidence
Authors: Baishya Upasana , Viswanathan Nirmal K.
Published: June 2023

The chirality of a medium is typically measured either by transmitting a beam of light through it or by single or multiple interface reflection at large and/or special angles of incidence. We propose and demonstrate here the experimental measurement of surface chirality of z-cut quartz crystal by reflecting a focused beam of light at a near-normal angle of incidence. A small difference in the reflection coefficients between orthogonal elliptically polarized incident beam of  10−4 is measured in the dark-field region of the reflected light via the weak measurement method, taking advantage of the significant transverse spin-shift (TSS) that arises due to the interaction. The TSS behavior is simulated for different chiral parameters (±γ) of the material. The experimental results match well with the theoretically simulated behavior to quantify γ of quartz crystal used as an example interface. The significance of our method can be of interest for a wide variety of fundamental and applied investigations.
Top-down integration of an hBN quantum emitter in a monolithic photonic waveguide
Authors: Gérard Domitille , Rosticher Michael , Watanabe Kenji , Taniguchi Takashi , Barjon Julien , Buil Stéphanie , Hermier Jean-Pierre , Delteil Aymeric
Published: June 2023

Integrated quantum photonics, with potential applications in quantum information processing, relies on the integration of quantum emitters into on-chip photonic circuits. Hexagonal boron nitride (hBN) is recognized as a material that is compatible with such implementations, owing to its relatively high refractive index and low losses in the visible range, together with advantageous fabrication techniques. Here, we combine hBN waveguide nanofabrication with the recently demonstrated local generation of quantum emitters using electron irradiation to realize a fully top-down elementary quantum photonic circuit in this material, operating at room temperature. This proof of principle constitutes a first step toward deterministic quantum photonic circuits in hBN.
Experimental and theoretical studies into longitudinal spatial hole burning as a power limit in high-power diode lasers at 975 nm
Authors: Arslan S. , Wenzel H. , Fricke J. , Thies A. , Ginolas A. , Eppich B. , Tränkle G. , Crump P.
Published: June 2023

Spatial-hole-burning as a limit to the continuous-wave (CW) output power of GaAs-based diode lasers is experimentally studied. For 90 μm stripe lasers with 6 mm resonator length and 0.8% front facet reflectivity, spontaneous emission (SE) intensity data show that the carrier density in the device center rises rapidly at the rear facet with bias and falls at the front, consistent with simulation. At the front, the carrier density at the edge of the laser stripe also rises rapidly with bias (lateral carrier accumulation, LCA), consistent with previous observations of increased local current flow. Devices with 20% front facet reflectivity for a flat longitudinal optical field profile show smaller variation in the local carrier density. Weak variation is seen in the carrier density outside the stripe; hence, current spreading is not a power limit. SE wavelength data show higher temperatures at the front with a twofold higher increase in temperature for 0.8% than for 20% front facet. The increased front temperature likely triggers lateral spatial-hole-burning and LCA in this region, limiting power. Finally, pulsed threshold current is more strongly temperature dependent for devices with 0.8% than 20% front facets, attributed to the higher rear facet carrier density. The temperature dependence of slope in pulsed is comparable for both devices at low bias but is more rapid for 0.8% at 20 A, likely due to non-clamping at the back. The temperature dependence of slope for CW is strong with 0.8% facets, likely due to the high temperature and LCA at the front but reduced for 20% facets.
Surface properties of alkali silicate glasses: Influence of the modifiers
Authors: Zhang Zhen , Ispas Simona , Kob Walter
Published: June 2023

Using large-scale molecular dynamics simulations, we investigate the surface properties of lithium, sodium, and potassium silicate glasses containing 25 mol % of alkali oxide. The comparison of two types of surfaces, a melt-formed surface (MS) and a fracture surface (FS), demonstrates that the influence of the alkali modifier on the surface properties depends strongly on the nature of the surface. The FS exhibits a monotonic increase of modifier concentration with increasing alkali size while the MS shows a saturation of alkali concentration when going from Na to K glasses, indicating the presence of competing mechanisms that influence the properties of a MS. For the FS, we find that larger alkali ions reduce the concentration of under-coordinated Si atoms and increase the fraction of two-membered rings, implying an enhanced chemical reactivity of the surface. For both types of surfaces, the roughness is found to increase with alkali size, with the effect being more pronounced for the FS than for the MS. The height–height correlation functions of the surfaces show a scaling behavior that is independent of the alkali species considered: The ones for the MS are compatible with the prediction of the frozen capillary wave theory while the ones for the FS show a logarithmic growth, i.e., on the nanoscale these surfaces are not self-affine fractals. The influence of the modifier on the surface properties are rationalized in terms of the interplay between multiple factors involving the size of the ions, bond strength, and charge balance on the surface.
Toward a practical method for measuring glass transition in polymers with low-frequency Raman spectroscopy
Authors: Chimenti Robert V. , Carriere James T. , D'Ascoli Danielle M. , Engelhardt Jamison D. , Sepcic Alyssa M. , Bensley Kayla A. , Lehman-Chong Alexandra M. , Stanzione Joseph F. , Lofland Samuel E.
Published: June 2023

Glass transition temperature is one of the most important characteristics to describe the behavior of polymeric materials. When a material goes through glass transition, conformational entropy increases, which affects the phonon density of states. Amorphous materials invariably display low-frequency Raman features related to the phonon density of states resulting in a broad disorder band below 100 cm−1. This band includes the Boson peak and a shoulder, which is dominated by the van Hove peak, and quasi-elastic Rayleigh scattering also contributes to the signal. The temperature dependence of the ratio of the integrated intensity in proximity of the Boson peak to that of the van Hove peak shows a kink near the glass transition temperature as determined by differential scanning calorimetry. Careful analysis of the Raman spectra confirms that this is related to a change in the phonon density of states at the transition temperature. This makes low-frequency Raman a promising technique for thermal characterization of polymers because not only is this technique chemically agnostic and contactless but also it requires neither intensity calibration nor deconvolution nor chemometric analysis.
Epsilon-near-zero surface waves enhance infrared vibrational spectroscopy
Authors: Smaali Rafik , Moreau Antoine , Centeno Emmanuel
Published: June 2023

Thin film epsilon-near-zero (ENZ) supports guided modes analogous to surface plasmon modes in the infrared, where surface plasmons are difficult to excite. Leveraging these modes can enhance the signal of surface-enhanced infrared absorption (SIERA) sensors by a factor of three, enabling the detection of minute amounts of materials. However, material losses can significantly impact sensor performance. To address this issue, we establish a condition that limits the impact of losses while still preserving the advantage of ENZ-surface waves. Our findings may pave the way for the identification and exploration of particularly suitable materials for highly efficient photonic SIERA sensors.
Machine learning-assisted investigation of the impact of lithium-ion de-embedding on the thermal conductivity of LiFePO4
Authors: Li Shi-Yi , Wu Cheng-Wei , Liu Long-Ting , Kuang Hui-Ling , Zeng Yu-Jia , Wu Dan , Xie Guofeng , Zhou Wu-Xing
Published: June 2023

In this study, we employ a machine-learning potential approach based on first-principles calculations combined with the Boltzmann transport theory to investigate the impact of lithium-ion de-embedding on the thermal conductivity of LiFePO4, with the aim of enhancing heat dissipation in lithium-ion batteries. The findings reveal a significant decrease in thermal conductivity with increasing lithium-ion concentration due to the decrease in phonon lifetime. Moreover, removal of lithium ions from different sites at a given lithium-ion concentration leads to distinct thermal conductivities, attributed to varying anharmonicity arising from differences in bond lengths and bond strengths of the Fe-O bonds. Our work contributes to a fundamental understanding of the thermal transport properties of lithium iron phosphate batteries, emphasizing the pivotal role of lithium-ion detachment and intercalation in the thermal management of electrochemical energy storage devices.
Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation
Authors: McCaughan Adam N. , Oripov Bakhrom G. , Ganesh Natesh , Nam Sae Woo , Dienstfrey Andrew , Buckley Sonia M.
Published: June 2023

We present multiplexed gradient descent (MGD), a gradient descent framework designed to easily train analog or digital neural networks in hardware. MGD utilizes zero-order optimization techniques for online training of hardware neural networks. We demonstrate its ability to train neural networks on modern machine learning datasets, including CIFAR-10 and Fashion-MNIST, and compare its performance to backpropagation. Assuming realistic timescales and hardware parameters, our results indicate that these optimization techniques can train a network on emerging hardware platforms orders of magnitude faster than the wall-clock time of training via backpropagation on a standard GPU, even in the presence of imperfect weight updates or device-to-device variations in the hardware. We additionally describe how it can be applied to existing hardware as part of chip-in-the-loop training or integrated directly at the hardware level. Crucially, because the MGD framework is model-free it can be applied to nearly any hardware platform with tunable parameters, and its gradient descent process can be optimized to compensate for specific hardware limitations, such as slow parameter-update speeds or limited input bandwidth.
Bias-free very low frequency magnetoelectric antenna
Authors: Fu Shifeng , Cheng Jiawei , Jiang Tao , Wu Hanzhou , Fang Ze , Jiao Jie , Sokolov Oleg , Ivanov Sergey , Bichurin Mirza , Wang Yaojin
Published: June 2023

A rapid surge in the research on very low frequency (VLF) antennas is occurring due to the demand for radio navigation and special environment communications such as underwater and underground applications. Among them, magnetoelectric (ME) antennas have recently proven to be a prospective solution for miniaturization of VLF communication systems. However, the essential magnetic bias fields (Hdc) lead to challenges of miniaturization, electromagnetic interference, and noise sources for ME antenna application. Here, a bias-free VLF ME antenna based on the magneto-gradient ME composite (i.e., annealed Metglas/Metglas/PZT/Metglas/annealed Metglas) has been designed. Owing to the interaction effect between multi-unannealed/annealed Metglas, the magneto-gradient ME composite exhibits a large direct and converse ME response (αDME = 107 V/cm Oe and αCME = 9 Gs/V at resonance) at bias-free, which is about 63% and 33% of the maximum value under optimal magnetic bias for unannealed ME composites. Moreover, a digital amplitude shift keying (ASK) modulation method is proved suitable for the as-made bias-free VLF ME antenna. Such a bias-free ME antenna provides a practicable strategy for miniaturization of VLF communication.
Glacial changes in sea level modulated millennial-scale variability of Southeast Asian autumn monsoon rainfall
Authors: Patterson Elizabeth W. , Johnson Kathleen R. , Griffiths Michael L. , Kinsley Christopher W. , McGee David , Du Xiaojing , Pico Tamara , Wolf Annabel , Ersek Vasile , Mortlock Richard A. , Yamoah Kweku A. , Bùi Thành N. , Trần Mùi X. , Đỗ-Trọng Quốc , Võ Trí V. , Đinh Trí H.
Published: June 2023

Most paleoclimate studies of Mainland Southeast Asia hydroclimate focus on the summer monsoon, with few studies investigating rainfall in other seasons. Here, we present a multiproxy stalagmite record (45,000 to 4,000 years) from central Vietnam, a region that receives most of its annual rainfall in autumn (September-November). We find evidence of a prolonged dry period spanning the last glacial maximum that is punctuated by an abrupt shift to wetter conditions during the deglaciation at ~14 ka. Paired with climate model simulations, we show that sea-level change drives autumn monsoon rainfall variability on glacial-orbital timescales. Consistent with the dry signal in the stalagmite record, climate model simulations reveal that lower glacial sea level exposes land in the Gulf of Tonkin and along the South China Shelf, reducing convection and moisture delivery to central Vietnam. When sea level rises and these landmasses flood at ~14 ka, moisture delivery to central Vietnam increases, causing an abrupt shift from dry to wet conditions. On millennial timescales, we find signatures of well-known Heinrich Stadials (HS) (dry conditions) and Dansgaard–Oeschger Events (wet conditions). Model simulations show that during the dry HS, changes in sea surface temperature related to meltwater forcing cause the formation of an anomalous anticyclone in the Western Pacific, which advects dry air across central Vietnam, decreasing autumn rainfall. Notably, sea level modulates the magnitude of millennial-scale dry and wet phases by muting dry events and enhancing wet events during periods of low sea level, highlighting the importance of this mechanism to autumn monsoon variability.
Inhibition of AIM2 inflammasome activation by SOX/ORF37 promotes lytic replication of Kaposi's sarcoma-associated herpesvirus
Authors: Zhang Xiaolin , Lan Qingping , Zhang Mingyu , Wang Fan , Shi Keyi , Li Xiaojuan , Kuang Ersheng
Published: June 2023

Inflammasomes are one kind of important innate immune defense against viral and bacterial infections. Several inflammasome-forming sensors detect molecular patterns of invading pathogens and then trigger inflammasome activation and/or pyroptosis in infected cells, and viruses employ unique strategies to hijack or subvert inflammasome activation. Infection with herpesviruses induces the activation of diverse inflammasomes, including AIM2 and IFI16 inflammasomes; however, how Kaposi's sarcoma-associated herpesvirus (KSHV) counteracts inflammasome activation largely remains unclear. Here, we reveal that the KSHV ORF37-encoded SOX protein suppresses AIM2 inflammasome activation independent of its viral DNA exonuclease activity and host mRNA turnover. SOX interacts with the AIM2 HIN domain through the C-terminal Motif VII region and disrupts AIM2:dsDNA polymerization and ASC recruitment and oligomerization. The Y443A or F444A mutation of SOX abolishes the inhibition of AIM2 inflammasome without disrupting SOX nuclease activity, and a short SOX peptide is capable of inhibiting AIM2 inflammasome activation; consequently, infection with SOX-null, Y443A, or F444A Bac16 recombinant viruses results in robust inflammasome activation, suppressed lytic replication, and increased pyroptosis in human lymphatic endothelial cells in an AIM2-dependent manner. These results reveal that KSHV SOX suppresses AIM2 inflammasome activation to promote KSHV lytic replication and inhibit pyroptosis, representing a unique mechanism for evasion of inflammasome activation during KSHV lytic cycle.
Bottlenose dolphin mothers modify signature whistles in the presence of their own calves
Authors: Sayigh Laela S. , El Haddad Nicole , Tyack Peter L. , Janik Vincent M. , Wells Randall S. , Jensen Frants H.
Published: June 2023

Human caregivers interacting with children typically modify their speech in ways that promote attention, bonding, and language acquisition. Although this “motherese,” or child-directed communication (CDC), occurs in a variety of human cultures, evidence among nonhuman species is very rare. We looked for its occurrence in a nonhuman mammalian species with long-term mother–offspring bonds that is capable of vocal production learning, the bottlenose dolphin (
Tursiops truncatus
). Dolphin signature whistles provide a unique opportunity to test for CDC in nonhuman animals, because we are able to quantify changes in the same vocalizations produced in the presence or absence of calves. We analyzed recordings made during brief catch-and-release events of wild bottlenose dolphins in waters near Sarasota Bay, Florida, United States, and found that females produced signature whistles with significantly higher maximum frequencies and wider frequency ranges when they were recorded with their own dependent calves vs. not with them. These differences align with the higher fundamental frequencies and wider pitch ranges seen in human CDC. Our results provide evidence in a nonhuman mammal for changes in the same vocalizations when produced in the presence vs. absence of offspring, and thus strongly support convergent evolution of motherese, or CDC, in bottlenose dolphins. CDC may function to enhance attention, bonding, and vocal learning in dolphin calves, as it does in human children. Our data add to the growing body of evidence that dolphins provide a powerful animal model for studying the evolution of vocal learning and language.
Ru-P pair sites boost charge transport in hematite photoanodes for exceeding 1% efficient solar water splitting
Authors: Gao Rui-Ting , Liu Lijia , Li Yanbo , Yang Yang , He Jinlu , Liu Xianhu , Zhang Xueyuan , Wang Lei , Wu Limin
Published: June 2023

Fast transport of charge carriers in semiconductor photoelectrodes are a major determinant of the solar-to-hydrogen efficiency for photoelectrochemical (PEC) water slitting. While doping metal ions as single atoms/clusters in photoelectrodes has been popularly used to regulate their charge transport, PEC performances are often low due to the limited charge mobility and severe charge recombination. Here, we disperse Ru and P diatomic sites onto hematite (DASs Ru-P:Fe
2
O
3
) to construct an efficient photoelectrode inspired by the concept of correlated single-atom engineering. The resultant photoanode shows superior photocurrent densities of 4.55 and 6.5 mA cm
−2
at 1.23 and 1.50 V
RHE
, a low-onset potential of 0.58 V
RHE
, and a high applied bias photon-to-current conversion efficiency of 1.00% under one sun illumination, which are much better than the pristine Fe
2
O
3
. A detailed dynamic analysis reveals that a remarkable synergetic ineraction of the reduced recombination by a low Ru doping concentration with substitution of Fe site as well as the construction of Ru-P bonds in the material increases the carrier separation and fast charge transportation dynamics. A systematic simulation study further proves the superiority of the Ru-P bonds compared to the Ru-O bonds, which allows more long-lived carriers to participate in the water oxidation reaction. This work offers an effective strategy for enhancing charge carrier transportation dynamics by constructing pair sites into semiconductors, which may be extended to other photoelectrodes for solar water splitting.
Lipid nanoparticle topology regulates endosomal escape and delivery of RNA to the cytoplasm
Authors: Zheng Lining , Bandara Sarith R. , Tan Zhengzhong , Leal Cecilia
Published: June 2023

RNA therapeutics have the potential to resolve a myriad of genetic diseases. Lipid nanoparticles (LNPs) are among the most successful RNA delivery systems. Expanding their use for the treatment of more genetic diseases hinges on our ability to continuously evolve the design of LNPs with high potency, cellular-specific targeting, and low side effects. Overcoming the difficulty of releasing cargo from endocytosed LNPs remains a significant hurdle. Here, we investigate the fundamental properties of nonviral RNA nanoparticles pertaining to the activation of topological transformations of endosomal membranes and RNA translocation into the cytosol. We show that, beyond composition, LNP fusogenicity can be prescribed by designing LNP nanostructures that lower the energetic cost of fusion and fusion–pore formation with a target membrane. The inclusion of structurally active lipids leads to enhanced LNP endosomal fusion, fast evasion of endosomal entrapment, and efficacious RNA delivery. For example, conserving the lipid make-up, RNA–LNPs having
cuboplex
nanostructures are significantly more efficacious at endosomal escape than traditional
lipoplex
constructs.
Activated alkyne-enabled turn-on click bioconjugation with cascade signal amplification for ultrafast and high-throughput antibiotic screening
Authors: Lv Shuyi , Wang Chao , Xue Ke , Wang Jiaxin , Xiao Minghui , Sun Zhencheng , Han Lei , Shi Linqi , Zhu Chunlei
Published: June 2023

Antimicrobial susceptibility testing plays a pivotal role in the discovery of new antibiotics. However, the development of simple, sensitive, and rapid assessment approaches remains challenging. Herein, we report an activated alkyne-based cascade signal amplification strategy for ultrafast and high-throughput antibiotic screening. First of all, a novel water-soluble aggregation-induced emission (AIE) luminogen is synthesized, which contains an activated alkyne group to enable fluorescence turn-on and metal-free click bioconjugation under physiological conditions. Taking advantage of the in-house established method for bacterial lysis, a number of clickable biological substances (i.e., bacterial solutes and debris) are released from the bacterial bodies, which remarkably increases the quantity of analytes. By means of the activated alkyne-mediated turn-on click bioconjugation, the system fluorescence signal is significantly amplified due to the increased labeling sites as well as the AIE effect. Such a cascade signal amplification strategy efficiently improves the detection sensitivity and thus enables ultrafast antimicrobial susceptibility assessment. By integration with a microplate reader, this approach is further applied to high-throughput antibiotic screening.
Formulation of the cosmic ray–driven electron-induced reaction mechanism for quantitative understanding of global ozone depletion
Authors: Lu Qing-Bin
Published: June 2023

This paper formulates the cosmic ray–driven electron-induced reaction as a universal mechanism to provide a quantitative understanding of global ozone depletion. Based on a proposed electrostatic bonding mechanism for charge-induced adsorption of molecules on surfaces and on the measured dissociative electron transfer (DET) cross sections of ozone-depleting substances (ODSs) adsorbed on ice, an analytical equation is derived to give atmospheric chlorine atom concentration:

C
l

=

∑
i

k
i

θ
ODS
i

Φ

e
2

,

where Φ
e
is the prehydrated electron (e
pre
−
) flux produced by cosmic ray ionization on atmospheric particle surfaces,

θ

ODS

i

is the surface coverage of an ODS, and

k
i

is the ODS’s effective DET coefficient that is the product of the DET cross section, the lifetimes of surface-trapped e
pre
−
and Cl
−
, and the particle surface area density. With concentrations of ODSs as the sole variable, our calculated results of time-series ozone depletion rates in global regions in the 1960s, 1980s, and 2000s show generally good agreement with observations, particularly with ground-based ozonesonde data and satellite-measured data over Antarctica and with satellite data in a narrow altitude band at 13 to 20 km of the tropics. Good agreements with satellite data in the Arctic and midlatitudes are also found. A previously unreported effect of denitrification on ozone loss is found and expressed quantitatively. But this equation overestimates tropospheric ozone loss at northern midlatitudes and the Arctic, likely due to increased ozone production by the halogen chemistry in polluted regions. The results render confidence in applying the equation to achieve a quantitative understanding of global ozone depletion.
Scientific machine learning for modeling and simulating complex fluids
Authors: Lennon Kyle R. , McKinley Gareth H. , Swan James W.
Published: June 2023

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.
To deceive, lie and omit: developmental, contextual and educational factors (Engañar, mentir y omitir: factores evolutivos, contextuales y educativos)
Authors: Martins Maria-José D. , Veiga-Simão Ana-Margarida
Published: June 2023

This article aims to review and debate the concept of lying and the variables associated with it, such as the age of its emergence in infancy, developmental patterns in a life cycle, motives for lying, consequences on social relationships and contextual and educational factors. The paradoxical nature of this behaviour is also emphasized because it can be accompanied by either prosocial or antisocial acts. The links with cognitive abilities, moral reasoning and moral action are also discussed. An understanding of the relationship between lying and antisocial behaviour and its developmental trends is pertinent to the prevention of damage to social relationships and several contemporary threats to democracy. The study concludes with considerations about the potential links between lying and moral development, and a discussion with a view to design educational programmes to promote honesty and responsibility as part of citizenship education in democratic societies.
Morphology, mechanical property, and molten pool dynamics in spot modulated-PLBW of Ti6Al4V alloy sheets with air gap condition
Authors: Chen Jicheng , Kong Bin , Wang Qi , Qi Zhemin , Wei Yanhong
Published: June 2023

The tailor joining of thin metal sheets frequently suffers from the assembly error of air gap. Herein, an improved laser welding scheme, integrating the pulsed laser power and the modulated beam spot size is developed and applied on 1.5 mm-thick Ti6Al4V sheets with a predetermined air gap range. Weld beads of high continuity and homogeneity are obtained while the tensile property has a nonlinear decrease when increasing the air gap. During the welding, the over-gap metal bridge is obtained due to melt accumulation and periodical keyhole penetration, and the gap bridging capacity, mainly featuring bilateral metal bridges can be weakened as the air gap increases. This evaluation would provide a basis for processing optimization regarding seam appearance and property.
Disentangling the complexity of coupled vibrations by two-dimensional electronic-vibrational spectroscopy
Authors: Zhang Xuanchao , Liu Zihui , Jha Ajay , Liang Xian-Ting , Thorwart Michael , Dwayne Miller R J , Duan Hong-Guang
Published: June 2023

We employ two-dimensional electronic-vibrational (2DEV) spectroscopy to study the coherent dynamics of coupled vibrational modes in an excitonically-coupled dimer model. The advantage of separating excitation and detection in different frequency regimes allows us to directly probe the electronic and vibrational coherences in the time-evolved 2DEV spectra. The complexity of vibrational coherence of two coupled modes is directly revealed by cross peaks in the 2DEV spectra. With the help of the ensuing time traces, we can follow how the vibrational coherence changes over time in the monomer model and, subsequently, in the dimer model. We show that the complexity of two coupled vibrational modes and the interaction between electronic and vibrational coherences in molecular systems can be effectively disentangled using the 2DEV spectroscopy technique.
A new GNSS outlier mitigation method for GNSS/INS integrated system
Authors: Guo Jingwen , Zhou Yilan , Zhao Shuai , Hu Zhijian
Published: June 2023

High-precision positioning with global navigation satellite systems (GNSS) remains a significant challenge in urban environments, due to the outliers caused by the insufficient number of accessible satellites and environmental interference. A GNSS outlier mitigation algorithm with effective fault detection and exclusion (FDE) is required for high-precision positioning. The traditional methods are designed to deal with zero-mean noise in GNSS, which leads to instabilities under biased measurements. Considering that GNSS data are typical time series data, a dynamic FDE scheme is constructed by combining a prediction-model-based method and a dissimilarity-based method. First, a hybrid prediction model which combines autoregressive integrated moving average (ARIMA) model and multilayer perceptron (MLP) model is proposed to provide pseudo-GNSS series by predicting the vehicle’s location for several future steps. Then, a dissimilarity-based method of dynamic time warping measure is utilized to analyze the pairwise dis-similarity between the pseudo-GNSS series and the received GNSS series. The performance of the different models in forecasting is evaluated, and the results show that the positioning accuracy is significantly improved by applying the ARIMA-MLP. The effectiveness of the proposed FDE method is verified through simulation experiments and real experiments based on a typical urban canyon public dataset collected in Tokyo.
A novel method to repair missing vibration data in rolling bearing vibration signals based on improved optimized measurement matrix
Authors: Wang Haiming , Liu Yongqiang , Li Qiang , Yang Shaopu , Wang Yanli
Published: June 2023

Missing data, caused by many factors such as equipment short circuits or data cleaning, affect the accuracy of condition monitoring for rotating machinery. To improve the precision of missing data recovery, a compressed sensing-based vibration data repair method is developed. First, based on the Gaussian random matrix, an improved optimized measurement matrix (OMM) is proposed to accurately sample data. Then, a sparse representation of the vibration signal, through a discrete cosine transform, is utilized to make the noisy vibration signal sparse. Finally, the orthogonal matching pursuit algorithm is employed to reconstruct the missing signal. The effectiveness of the proposed method is verified by analyzing constant and variable speed time series of rolling bearings. Compared with other data repair methods, it is shown that the OMM has a higher repair precision at different loss rates.
Embedding TiO2 microspheres into the active layer as light scatterers in a perovskite photodetector to boost light harvesting
Authors: Feng Jianwen , Cui Xiangqian , Li Bobo , Qiu Mingxia , Liu Weifeng , Liu Xuguang
Published: June 2023

Here, TiO2 microspheres with particle sizes of 200–400 nm are embedded in p–i–n perovskite photodetectors, which are used as light scatterers. This approach was implemented to change the light transfer path in the perovskite layer, which gives the device higher photon-capture ability in a specific incident wavelength range. Compared with a pristine device, the photocurrent and responsivity of the device based on such a structure are obviously enhanced in the ranges of 560–610 nm and 730–790 nm. The photocurrent under 590 nm incident light wavelength illumination (light intensity P = 31.42 μW·cm−2) increases from 1.45 μA to 1.71 μA, with an increase of 17.93%, and the responsivity reaches 0.305 A·W−1. In addition, the introduction of TiO2 has no additional negative impact on the carrier extraction and the dark current. Also, the response time of the device did not deteriorate. Finally, the role of TiO2 as light scatterers is further verified by embedding microspheres into mixed-halide perovskite devices.
Improving breast tumor segmentation via shape-wise prior-guided information on cone-beam breast CT images
Authors: Lin Tongxu , Lin Junyu , Huang Guoheng , Yuan Xiaochen , Zhong Guo , Xie Fenfang , Li Jiao
Published: June 2023

Objective. Due to the blurry edges and uneven shape of breast tumors, breast tumor segmentation can be a challenging task. Recently, deep convolution networks based approaches achieve satisfying segmentation results. However, the learned shape information of breast tumors might be lost owing to the successive convolution and down-sampling operations, resulting in limited performance. Approach. To this end, we propose a novel shape-guided segmentation (SGS) framework that guides the segmentation networks to be shape-sensitive to breast tumors by prior shape information. Different from usual segmentation networks, we guide the networks to model shape-shared representation with the assumption that shape information of breast tumors can be shared among samples. Specifically, on the one hand, we propose a shape guiding block (SGB) to provide shape guidance through a superpixel pooling-unpooling operation and attention mechanism. On the other hand, we further introduce a shared classification layer (SCL) to avoid feature inconsistency and additional computational costs. As a result, the proposed SGB and SCL can be effortlessly incorporated into mainstream segmentation networks (e.g. UNet) to compose the SGS, facilitating compact shape-friendly representation learning. Main results. Experiments conducted on a private dataset and a public dataset demonstrate the effectiveness of the SGS compared to other advanced methods. Significance. We propose a united framework to encourage existing segmentation networks to improve breast tumor segmentation by prior shape information. The source code will be made available at https://github.com/TxLin7/Shape-Seg.
Proton irradiation influence on gate-channel low-field carrier mobility of AlGaN/GaN HEMTs
Authors: Ji Qizheng , Yang Ming , Liu Jun , Ma Guilei , Xie Xining , Hu Xiaofeng , Liu Shanghe
Published: June 2023

AlGaN/GaN high electron mobility transistors (HEMTs) with different device sizes were prepared and exposed to 0.4 MeV proton irradiation. The low-field carrier transport characteristics of the gate channel are obtained from the capacitance-voltage curves and current-voltage curves. For the device with a longer gate-drain distance (30 μm), after 0.4 MeV proton irradiation, the gate-channel low-field carrier mobility increases by 14.3% on average. For the device with a shorter gate-drain distance (15 μm), the carrier mobility decreases by 13.4% on average after proton irradiation. This phenomenon is studied with regard to the polarization scattering effect. It is found that the polarization distribution in the AlGaN/GaN HEMTs changes after proton irradiation and different gate-drain distances correspond to different polarization distributions.
A novel photodiode array structure with double-layer SiO2 isolation
Authors: Jiang Ningning , Zhang Shubin , Jiang Yanfeng
Published: June 2023

A novel photodiode array structure is proposed and implemented in the paper. Based on the silicon-on-insulator substrate, the structure adopts double SiO2 layers for isolation among PN junctions. Compared with incumbent photodiode arrays with a single isolation layer, the novel design shows less leakage current, less noise, high optical response sensitivity, and better compatible integration with other devices. The dark current of this structure is less than nanoamperes (10−9 A), with the benefits of 1000 times’ less leakage current than that of other structures, and a higher sensitivity with a response speed less than 200 ns. The device is fabricated and characterized. The doping concentration and structural profile are characterized. The fabricated device is packaged with a photo light-emitting diode and the MOS device to act as the MOS relay driver. The wavelength used in the photodiode is between 500 nm–560 nm, with peak wavelength 520 nm, which can be used to drive MOS device.
Multiparameter quantum metrology and mode entanglement with spatially split nonclassical spin ensembles
Authors: Fadel Matteo , Yadin Benjamin , Mao Yuping , Byrnes Tim , Gessner Manuel
Published: June 2023

We identify the multiparameter sensitivity of entangled spin states, such as spin-squeezed and Dicke states that are spatially distributed into several addressable spatial modes. Analytical expressions for the spin-squeezing matrix of families of states that are accessible by current atomic experiments reveal the quantum gain in multiparameter metrology, as well as the optimal strategies to maximize the sensitivity gain for the estimation of any linear combination of parameters. We further study the mode entanglement of these states by deriving a witness for genuine k-partite mode entanglement from the spin-squeezing matrix. Our results highlight the advantage of mode entanglement for distributed sensing, and outline optimal protocols for multiparameter estimation with nonclassical spatially-distributed spin ensembles. We illustrate our findings with the design of a protocol for gradient sensing with a Bose–Einstein condensate in an entangled spin state in two modes.
Hydrogen peroxide as an additive to curcumin on the photodynamic inactivation of bacteria: a preliminary study
Authors: Sammarro Silva Kamila Jessie , Lima Alessandra Ramos , Corrêa Thaila Quatrini , Dias Lucas Danilo , Bagnato Vanderlei Salvador
Published: June 2023

Photodynamic inactivation (PDI) of microorganisms has been shown as a promising alternative against the spread of resistant bacteria. It has been used not only in clinical applications, but also in the public health sector, for water and wastewater disinfection. In order to improve efficiency, recent research has focused on novel photosensitizing materials, as well as chemical additives. To our knowledge, however, hydrogen peroxide (a widely known standalone disinfectant) has not been employed combined with curcumin (a vegetal-based and environmental-friendly photosensitizer) for PDI seeking for future environmental applications. In this sense, this study aimed to assess whether there were any competitive or cooperative effects by the simultaneous use of curcumin and hydrogen peroxide on the PDI of Staphylococcus aureus, in in-vitro batch tests. Photobleaching for individual and combined factors was performed in order to compare results of inactivation with changes in chemical aspects in solution under blue light irradiation. One may think that the combination may add strength to PDI due to hydrogen peroxide being a natural supplier of oxygen. However, antagonistic effects were found in combined treatments, implying that such combination is non profitable. The results indicate that special care is necessary when considering combining techniques.
Corrigendum: High Temperature Superconducting (HTS) Cable Application to Ship Deperming Work (J. Phys.: Conf. Ser. 1559 012132)
Authors: Hirota M
Published: June 2023

Please see Article PDF for corrigendum text.
Corrigendum: Experimental study on dynamic effects of H− and D− negative ions in an ECR-plasma source (2022 Journal of Physics: Conference Series 2244 012006)
Authors: Mitrou M. , Svarnas P. , Béchu S.
Published: June 2023

Please see Article PDF for corrigendum text.
Rosa: Language Model for Landscape Text Assisted Writing
Authors: Chen Yijia , Zheng Lingna
Published: June 2023

In landscape design, the text of landscape design plays an important role. However, in practice, designers are often faced with an industry situation where they need to complete a large number of design tasks in a short period. If language models are used to assist in the writing of design texts, it will be of great help not only to designers but also to the landscape design industry. A pre-trained language model trained on collected landscape design texts and used for landscape text-assisted authoring. It is better than the existing models in terms of perplexity, readability and manual evaluation. It has great potential to be used to improve the landscape design industry.