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A growing number of two-dimensional superconductors are being discovered in the family of exfoliated van der Waals materials. Due to small sample volume, the superfluid response of these materials has not been characterized. Here, we use a local magnetic probe to directly measure this key property of the tunable, gate-induced superconducting state in MoS₂. We find that the backgate changes the transition temperature non-monotonically whereas the superfluid stiffness at low temperature and the normal state conductivity monotonically increase. In some devices, we find direct signatures in agreement with a Berezinskii-Kosterlitz-Thouless transition, whereas in others we find a broadened onset of the superfluid response. We show that the observed behavior is consistent with disorder playing an important role in determining the properties of superconducting MoS₂. Our work demonstrates that magnetic property measurements are within reach for superconducting devices based on exfoliated sheets and reveals that the superfluid response significantly deviates from simple BCS-like behavior.

Polar skyrmions are predicted to emerge from the interplay of elastic, electrostatic and gradient energies, in contrast to the key role of the anti-symmetric Dzyalozhinskii-Moriya interaction in magnetic skyrmions. Here, we explore the reversible transition from a skyrmion state (topological charge of −1) to a two-dimensional, tetratic lattice of merons (with topological charge of −1/2) upon varying the temperature and elastic boundary conditions in [(PbTiO₃)₁₆/(SrTiO₃)₁₆]₈membranes. This topological phase transition is accompanied by a change in chirality, from zero-net chirality (in meronic phase) to net-handedness (in skyrmionic phase). We show how scanning electron diffraction provides a robust measure of the local polarization simultaneously with the strain state at sub-nm resolution, while also directly mapping the chirality of each skyrmion. Using this, we demonstrate strain as a crucial order parameter to drive isotropic-to-anisotropic structural transitions of chiral polar skyrmions to non-chiral merons, validated with X-ray reciprocal space mapping and phase-field simulations.

The relationship between root, stem, and leaf hydraulic status and stomatal conductance during drought (field capacities: 100–25%) and drought recovery was studied in Helianthus annuus and five tree species (Populus×canadensis, Acer saccharum, A. saccharinum, Picea glauca, and Tsuga canadensis). Measurements of stomatal conductance (gs), organ water potential, and vessel embolism were performed and the following was observed: (i) cavitation only occurred in the petioles and not the roots or stems of tree species regardless of drought stress; (ii) in contrast, all H. annuus organs exhibited cavitation to an increasing degree from root to petiole; and (iii) all species initiated stomatal closure before cavitation events occurred or the expected turgor loss point was reached. After rewatering: (i) cavitated vessels in petioles of Acer species recovered whereas those of P. ×canadensis did not and leaves were shed; (ii) in H. annuus, cavitated xylem vessels were refilled in roots and petioles, but not in stems; and (iii) despite refilled embolisms in petioles of some species during drought recovery, gs never returned to pre-drought conditions. Conclusions are drawn with respect to the hydraulic segmentation hypothesis for above- and below-ground organs, and the timeline of embolism occurrence and repair is discussed.

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to reveal unexpected deformations that crucially affect material properties across a large sample area. Here, we demonstrate a rapid and semi-automated unsupervised machine learning approach to uncover lattice deformations in materials. Our method utilizes divisive hierarchical clustering to automatically unveil multi-scale deformations in the entire sample flake from the diffraction data using four-dimensional scanning transmission electron microscopy (4D-STEM). Our approach overcomes the current barriers of large 4D data analysis without a priori knowledge of the sample. Using this purely data-driven analysis, we have uncovered different types of material deformations, such as strain, lattice distortion, bending contour, etc., which can significantly impact the band structure and subsequent performance of nanomaterials-based devices. We envision that this data-driven procedure will provide insight into materials’ intrinsic structures and accelerate the discovery of materials.

The recently discovered spin-active boron vacancy (V$${}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$${}_B^{-}$) defect center in hexagonal boron nitride (hBN) has high contrast optically-detected magnetic resonance (ODMR) at room-temperature, with a spin-triplet ground-state that shows promise as a quantum sensor. Here we report temperature-dependent ODMR spectroscopy to probe spin within the orbital excited-state. Our experiments determine the excited-state spin Hamiltonian, including a room-temperature zero-field splitting of 2.1 GHz and a g-factor similar to that of the ground-state. We confirm that the resonance is associated with spin rotation in the excited-state using pulsed ODMR measurements, and we observe Zeeman-mediated level anti-crossings in both the orbital ground- and excited-state. Our observation of a single set of excited-state spin-triplet resonance from 10 to 300 K is suggestive of symmetry-lowering of the defect system fromD_3htoC_2v. Additionally, the excited-state ODMR has strong temperature dependence of both contrast and transverse anisotropy splitting, enabling promising avenues for quantum sensing.

Adsorption plays vital roles in many processes including catalysis, sensing, and nanomaterials design. However, quantifying molecular adsorption, especially at the nanoscale, is challenging, hindering the exploration of its utilization on nanomaterials that possess heterogeneity across different length scales. Here we map the adsorption of nonfluorescent small molecule/ion and polymer ligands on gold nanoparticles of various morphologies in situ under ambient solution conditions, in which these ligands are critical for the particles’ physiochemical properties. We differentiate at nanometer resolution their adsorption affinities among different sites on the same nanoparticle and uncover positive/negative adsorption cooperativity, both essential for understanding adsorbate-surface interactions. Considering the surface density of adsorbed ligands, we further discover crossover behaviors of ligand adsorption between different particle facets, leading to a strategy and its implementation in facet-controlled synthesis of colloidal metal nanoparticles by merely tuning the concentration of a single ligand.

The self-organization of strongly interacting electrons into superlattice structures underlies the properties of many quantum materials. How these electrons arrange within the superlattice dictates what symmetries are broken and what ground states are stabilized. Here we show that cryogenic scanning transmission electron microscopy (cryo-STEM) enables direct mapping of local symmetries and order at the intra-unit-cell level in the model charge-ordered system Nd_1/2Sr_1/2MnO₃. In addition to imaging the prototypical site-centered charge order, we discover the nanoscale coexistence of an exotic intermediate state which mixes site and bond order and breaks inversion symmetry. We further show that nonlinear coupling of distinct lattice modes controls the selection between competing ground states. The results demonstrate the importance of lattice coupling for understanding and manipulating the character of electronic self-organization and that cryo-STEM can reveal local order in strongly correlated systems at the atomic scale.

Gallium nitride high-electron-mobility transistors (GaN HEMTs) are at a point of rapid growth in defense (radar, SATCOM) and commercial (5G and beyond) industries. This growth also comes at a point at which the standard GaN heterostructures remain unoptimized for maximum performance. For this reason, we propose the shift to the aluminum nitride (AlN) platform. AlN allows for smarter, highly-scaled heterostructure design that will improve the output power and thermal management of III-nitride amplifiers. Beyond improvements over the incumbent amplifier technology, AlN will allow for a level of integration previously unachievable with GaN electronics. State-of-the-art high-current p-channel FETs, mature filter technology, and advanced waveguides, all monolithically integrated with an AlN/GaN/AlN HEMT, is made possible with AlN. It is on this new AlN platform that nitride electronics may maximize their full high-power, high-speed potential for mm-wave communication and high-power logic applications.

We present a mechanism for thermal cycling that does not require electricity; instead, the device functions as a heat engine and requires only a generic heat source and a shape memory alloy (SMA) spring. The SMA spring mechanically translates to a low-temperature reservoir when heated, and the subsequent cooling of the spring causes translation back to a high-temperature reservoir. The usefulness of the mechanism is displayed by performing the quantitative polymerase chain reaction (qPCR), an important biological assay that requires thermal cycling for amplification of nucleic acids. The ability to perform qPCR with a generic heat source enables a variety of significant health diagnostic tests to be performed in resource limited settings, where electricity access may not be available or reliable. We demonstrate robust thermal cycling using a direct flame, sunlight, and electricity as heat sources, with maximum heating and cooling rates of 4.4 °C s⁻¹and −2.7 °C s⁻¹, respectively.

Both high resolution and high precision are required to quantitatively determine the atomic structure of complex nanostructured materials. However, for conventional imaging methods in scanning transmission electron microscopy (STEM), atomic resolution with picometer precision cannot usually be achieved for weakly-scattering samples or radiation-sensitive materials, such as 2D materials. Here, we demonstrate low-dose, sub-angstrom resolution imaging with picometer precision using mixed-state electron ptychography. We show that correctly accounting for the partial coherence of the electron beam is a prerequisite for high-quality structural reconstructions due to the intrinsic partial coherence of the electron beam. The mixed-state reconstruction gains importance especially when simultaneously pursuing high resolution, high precision and large field-of-view imaging. Compared with conventional atomic-resolution STEM imaging techniques, the mixed-state ptychographic approach simultaneously provides a four-times-faster acquisition, with double the information limit at the same dose, or up to a fifty-fold reduction in dose at the same resolution.