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13
Date Added: Sep 3, 2021
Date Added: Sep 3, 2021
Nature controls the assembly of complex architectures through self-limiting processes; however, few artificial strategies to mimic these processes have been reported to date. Here we demonstrate a system comprising two types of nanocrystal (NC), where the self-limiting assembly of one NC component controls the aggregation of the other. Our strategy uses semiconducting InP/ZnS core–shell NCs (3 nm) as effective assembly modulators and functional nanoparticle surfactants in cucurbit[n]uril-triggered aggregation of AuNCs (5–60 nm), allowing the rapid formation (within seconds) of colloidally stable hybrid aggregates. The resultant assemblies efficiently harvest light within the semiconductor substructures, inducing out-of-equilibrium electron transfer processes, which can now be simultaneously monitored through the incorporated surface-enhanced Raman spectroscopy–active plasmonic compartments. Spatial confinement of electron mediators (for example, methyl viologen (MV2+)) within the hybrids enables the direct observation of photogenerated radical species as well as molecular recognition in real time, providing experimental evidence for the formation of elusive σ–(MV+)2 dimeric species. This approach paves the way for widespread use of analogous hybrids for the long-term real-time tracking of interfacial charge transfer processes, such as the light-driven generation of radicals and catalysis with operando spectroscopies under irreversible conditions.
14
Date Added: Oct 21, 2021
Date Added: Oct 21, 2021
Einstein's theory of general relativity states that clocks at different gravitational potentials tick at different rates - an effect known as the gravitational redshift. As fundamental probes of space and time, atomic clocks have long served to test this prediction at distance scales from 30 centimeters to thousands of kilometers. Ultimately, clocks will study the union of general relativity and quantum mechanics once they become sensitive to the finite wavefunction of quantum objects oscillating in curved spacetime. Towards this regime, we measure a linear frequency gradient consistent with the gravitational redshift within a single millimeter scale sample of ultracold strontium. Our result is enabled by improving the fractional frequency measurement uncertainty by more than a factor of 10, now reaching 7.6×1021\times 10^{-21}. This heralds a new regime of clock operation necessitating intra-sample corrections for gravitational perturbations.
13
Date Added: Jul 30, 2021
Date Added: Jul 30, 2021
Voltage control of magnetic order is desirable for spintronic device applications, but 180° magnetization switching is not straightforward because electric fields do not break time-reversal symmetry. Ferrimagnets are promising candidates for 180° switching owing to a multi-sublattice configuration with opposing magnetic moments of different magnitudes. In this study we used solid-state hydrogen gating to control the ferrimagnetic order in rare earth–transition metal thin films dynamically. Electric field-induced hydrogen loading/unloading in GdCo can shift the magnetic compensation temperature by more than 100 K, which enables control of the dominant magnetic sublattice. X-ray magnetic circular dichroism measurements and ab initio calculations indicate that the magnetization control originates from the weakening of antiferromagnetic exchange coupling that reduces the magnetization of Gd more than that of Co upon hydrogenation. We observed reversible, gate voltage-induced net magnetization switching and full 180° Néel vector reversal in the absence of external magnetic fields. Furthermore, we generated ferrimagnetic spin textures, such as chiral domain walls and skyrmions, in racetrack devices through hydrogen gating. With gating times as short as 50 μs and endurance of more than 10,000 cycles, our method provides a powerful means to tune ferrimagnetic spin textures and dynamics, with broad applicability in the rapidly emerging field of ferrimagnetic spintronics.
20
Date Added: Jul 20, 2021
Date Added: Jul 20, 2021
Evaluated nuclear structure and decay data for all nuclei with mass number A=201 (201Os, 201Ir, 201Pt, 201Au, 201Hg, 201Tl, 201Pb, 201Bi, 201Po, 201At, 201Rn, 201Fr, 201Ra) are presented. All available experimental data are compiled and evaluated, and best values for level and gamma-ray energies, quantum numbers, lifetimes, gamma-ray intensities and transition probabilities, as well as other nuclear properties, are recommended. Inconsistencies and discrepancies that exist in the literature are discussed. A number of computer codes (https://wwwnds. iaea.org/public/ensdf pgm/index.htm) developed by members of the NSDD network were used during the evaluation process. For example, the reported absolute gamma-ray emission probabilities and their uncertainties in various decay data sets were determined using the GABS code. The gamma-ray transition probabilities were determined using the RULER code and the corresponding uncertainties were determined using a Monte-Carlo approach. This work supersedes the earlier evaluation by F.G. Kondev (2007Ko06), published in Nuclear Data Sheets 108, 365 (2007).
4
Date Added: Aug 2, 2021
Date Added: Aug 2, 2021
Thermoelectric materials generate electric energy from waste heat, with conversion efficiency governed by the dimensionless figure of merit, ZT. Single-crystal tin selenide (SnSe) was discovered to exhibit a high ZT of roughly 2.2–2.6 at 913 K, but more practical and deployable polycrystal versions of the same compound suffer from much poorer overall ZT, thereby thwarting prospects for cost-effective lead-free thermoelectrics. The poor polycrystal bulk performance is attributed to traces of tin oxides covering the surface of SnSe powders, which increases thermal conductivity, reduces electrical conductivity and thereby reduces ZT. Here, we report that hole-doped SnSe polycrystalline samples with reagents carefully purified and tin oxides removed exhibit an ZT of roughly 3.1 at 783 K. Its lattice thermal conductivity is ultralow at roughly 0.07 W m–1 K–1 at 783 K, lower than the single crystals. The path to ultrahigh thermoelectric performance in polycrystalline samples is the proper removal of the deleterious thermally conductive oxides from the surface of SnSe grains. These results could open an era of high-performance practical thermoelectrics from this high-performance material.
4
Date Added: Aug 2, 2021
Date Added: Aug 2, 2021
Nanostructured birnessite exhibits high specific capacitance and nearly ideal capacitive behaviour in aqueous electrolytes, rendering it an important electrode material for low-cost, high-power energy storage devices. The mechanism of electrochemical capacitance in birnessite has been described as both Faradaic (involving redox) and non-Faradaic (involving only electrostatic interactions). To clarify the capacitive mechanism, we characterized birnessite’s response to applied potential using ex situ X-ray diffraction, electrochemical quartz crystal microbalance, in situ Raman spectroscopy and operando atomic force microscope dilatometry to provide a holistic understanding of its structural, gravimetric and mechanical responses. These observations are supported by atomic-scale simulations using density functional theory for the cation-intercalated structure of birnessite, ReaxFF reactive force field-based molecular dynamics and ReaxFF-based grand canonical Monte Carlo simulations on the dynamics at the birnessite–water–electrolyte interface. We show that capacitive charge storage in birnessite is governed by interlayer cation intercalation. We conclude that the intercalation appears capacitive due to the presence of nanoconfined interlayer structural water, which mediates the interaction between the intercalated cation and the birnessite host and leads to minimal structural changes.
5
Date Added: Nov 4, 2021
Date Added: Nov 4, 2021
The nuclear root-mean-square charge radius of Ni54 was determined with collinear laser spectroscopy to be R(Ni54)=3.737(3) fm. In conjunction with the known radius of the mirror nucleus Fe54, the difference of the charge radii was extracted as ΔRch=0.049(4) fm. Based on the correlation between ΔRch and the slope of the symmetry energy at nuclear saturation density (L), we deduced 21≤L≤88 MeV. The present result is consistent with the L from the binary neutron star merger GW170817, favoring a soft neutron matter EOS, and barely consistent with the PREX-2 result within 1σ error bands. Our result indicates the neutron-skin thickness of Ca48 as 0.15–0.21 fm.
3
Date Added: Aug 9, 2021
Date Added: Aug 9, 2021
As a new method to determine the resonance frequency, Rabi-oscillation spectroscopy has been developed. In contrast to the conventional spectroscopy which draws the resonance curve, Rabi-oscillation spectroscopy fits the time evolution of the Rabi oscillation. By selecting the optimized frequency, it is shown that the precision is twice as good as the conventional spectroscopy with a frequency sweep. Furthermore, the data under different conditions can be treated in a unified manner, allowing more efficient measurements for systems consisting of a limited number of short-lived particles produced by accelerators such as muons. We have developed a fitting function that takes into account the spatial distribution of muonium and the spatial distribution of the microwave intensity to apply the new method to ground-state muonium hyperfine structure measurements at zero field. This was applied to the actual measurement data and the resonance frequencies were determined under various conditions. The result of our analysis gives νHFS=4 463 301.61±0.71 kHz, which is the world's highest precision under zero field conditions.
4
Date Added: Sep 29, 2021
Date Added: Sep 29, 2021
Graphene nanoribbons are of potential use in the development of electronic and optoelectronic devices. However, the preparation of narrow and long nanoribbons with smooth edges, sizeable bandgaps and high mobilities is challenging. Here we show that sub-10-nm-wide semiconducting graphene nanoribbons with atomically smooth closed edges can be produced by squashing carbon nanotubes using a high-pressure and thermal treatment. With this approach, nanoribbons as narrow as 1.4 nm can be created, and up to 54% of single- and double-walled nanotubes in a sample can be converted into edge-closed nanoribbons. We also fabricate edge-opened nanoribbons using nitric acid as the oxidant to selectively etch the edges of the squashed nanotubes under high pressure. A field-effect transistor fabricated using a 2.8-nm-wide edge-closed nanoribbon exhibits an on/off current ratio of more than 104, from which a bandgap of around 494 meV is estimated. The device also exhibits a field-effect mobility of 2,443 cm2 V−1 s−1 and an on-state channel conductivity of 7.42 mS.
3
Date Added: Nov 4, 2021
Date Added: Nov 4, 2021
The atomistic stress state along a grain boundary can be treated as a representation of the Cauchy stress tensor for the calculation of continuum traction fields, which ultimately governs the ability of grain boundaries to generate, absorb, or transmit dislocations. Such quantitative grain boundary descriptors are mostly confined to molecular dynamics (MD) simulations, where the notion of atomistic stress can be defined through virial theorem. Here, we use artificial neural networks for machine learning (ML), fed with a limited training dataset from MD simulations, to predict the local atomistic stresses from atomic position information across a series of equilibrium symmetrical-tilt Cu grain boundary structures. Accuracy of the ML algorithm is found to depend on the type, sequence, and distortion of the grain boundary structural units. Accounting for these characteristics in the training dataset enables accurate predictions of the local atomistic stress distributions across the family of grain boundary structures. This ML-based constitutive modeling paves the way for direct interpretation of the equivalent stress state of atomistic structures beyond the MD domain, including those from high-resolution transmission electron microscopy (HRTEM) imaging and Density Functional Theory (DFT) modeling.