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Metals with kagome lattice provide bulk materials to host both the flat-band and Dirac electronic dispersions. A new family of kagome metals is recently discovered inAV₆Sn₆. The Dirac electronic structures of this material needs more experimental evidence to confirm. In the manuscript, we investigate this problem by resolving the quantum oscillations in both electrical transport and magnetization in ScV₆Sn₆. The revealed orbits are consistent with the electronic band structure models. Furthermore, the Berry phase of a dominating orbit is revealed to be aroundπ, providing direct evidence for the topological band structure, which is consistent with calculations. Our results demonstrate a rich physics and shed light on the correlated topological ground state of this kagome metal.

 

Interband cascade lasers (ICLs) are efficient and compact mid-infrared (3-5 µm) light sources with many applications. By enhancing the coupling coefficient and using a type-I ICL wafer, single-mode ICLs were demonstrated based on V-coupled cavity with significantly extended tuning range and with a side mode suppression ratio (SMSR) exceeding 35 dB in continuous wave operation near 3 µm. A V-coupled cavity ICL exhibited a wavelength tuning up to 67 nm at a fixed temperature, and the total tuning range exceeds 210 nm when the heat sink temperature is adjusted from 80 to 180 K. The realization of single-mode in such a wide temperature range with a tuning range exceeding 210 nm verified the advantage of V-coupled cavity ICLs for effective detection of multiple gas species. This is very different from the conventional distributed feedback (DFB) laser where the single-mode operation is restricted to a narrow temperature range, in which the match between the gain peak and the DFB grating period determined wavelength is required. Another V-coupled cavity ICL is tuned over 120 nm from 2997.56 nm to 3117.50 nm with the heat-sink temperature varied from 210 K to 240 K, over 100 K higher than the previously reported maximum operating temperature for V-coupled cavity ICLs.

 

Because of the increasing demand, high-power, high-rate energy storage devices based on electrode materials have attracted immense attention. However, challenges remain to be addressed to improve the concentration-dependent kinetics of ionic diffusion and understand phase transformation, interfacial reactions, and capacitive behaviors that vary with particle morphology and scanning rates. It is valuable to understand the microscopic origins of ion transport in electrode materials. In this review, we discuss the microscopic transport phenomena and their dependence on ion concentration in the cathode materials, by comparing dozens of well-studied transition metal oxides, sulfides, and phosphates, and in the anode materials, including several carbon species and carbides. We generalize the kinetic effects on the microscopic ionic transport processes from the phenomenological points of view based on the well-studied systems. The dominant kinetic effects on ion diffusion varied with ion concentration, and the pathway- and morphology-dependent diffusion and capacitive behaviors affected by the sizes and boundaries of particles are demonstrated. The important kinetic effects on ion transport by phase transformation, transferred electrons, and water molecules are discussed. The results are expected to shed light on the microscopic limiting factors of charging/discharging rates for developing new intercalation and conversion reaction systems. 

In the recently discovered kagome metal CsV₃Sb₅, an intriguing proposal invoking a doped Chern insulator state suggests the presence of small Chern Fermi pockets hosting spontaneous orbital-currents and large orbital magnetic moments. While the net thermodynamic magnetization is nearly insensitive to these moments, due to their antiferromagnetic alignment, their presence can be revealed by the Zeeman effect, which shifts electron energies in magnetic fields with a proportionality given by the effectiveg−factor. Here, we determine theg-factor using the spin-zero effect in magnetic quantum oscillations. A largeg-factor enhancement is visible only in magnetic breakdown orbits between conventional and concentrated Berry curvature Fermi pockets that host large orbital moments. Such Berry-curvature-generated large orbital moments are almost always concealed by other effects. In this system, however, magnetic breakdown orbits due to the proximity to a conventional Fermi-surface section allow them to be visibly manifested in magnetic quantum oscillations. Our results provide a remarkable example of the interplay between electronic correlations and more conventional electronic bands in quantum materials.

 

An increasing number of studies have demonstrated the significant roles of the interplay between microenvironmental mechanics in tissues and biochemical-genetic activities in resident tumor cells at different stages of tumor progression. Mediated by molecular mechano-sensors or -transducers, biomechanical cues in tissue microenvironments are transmitted into the tumor cells and regulate biochemical responses and gene expression through mechanotransduction processes. However, the molecular interplay between the mechanotransduction processes and intracellular biochemical signaling pathways remains elusive. This paper reviews the recent advances in understanding the crosstalk between biomechanical cues and three critical biochemical effectors during tumor progression: calcium ions (Ca 2+ ), yes-associated protein (YAP), and microRNAs (miRNAs). We address the molecular mechanisms underpinning the interplay between the mechanotransduction pathways and each of the three effectors. Furthermore, we discuss the functional interactions among the three effectors in the context of soft matter and mechanobiology. We conclude by proposing future directions on studying the tumor mechanobiology that can employ Ca 2+ , YAP, and miRNAs as novel strategies for cancer mechanotheraputics. This framework has the potential to bring insights into the development of novel next-generation cancer therapies to suppress and treat tumors. 

Cycle representatives of persistent homology classes can be used to provide descriptions of topological features in data. However, the non-uniqueness of these representatives creates ambiguity and can lead to many different interpretations of the same set of classes. One approach to solving this problem is to optimize the choice of representative against some measure that is meaningful in the context of the data. In this work, we provide a study of the effectiveness and computational cost of several ℓ 1 minimization optimization procedures for constructing homological cycle bases for persistent homology with rational coefficients in dimension one, including uniform-weighted and length-weighted edge-loss algorithms as well as uniform-weighted and area-weighted triangle-loss algorithms. We conduct these optimizations via standard linear programming methods, applying general-purpose solvers to optimize over column bases of simplicial boundary matrices. Our key findings are: 1) optimization is effective in reducing the size of cycle representatives, though the extent of the reduction varies according to the dimension and distribution of the underlying data, 2) the computational cost of optimizing a basis of cycle representatives exceeds the cost of computing such a basis, in most data sets we consider, 3) the choice of linear solvers matters a lot to the computation time of optimizing cycles, 4) the computation time of solving an integer program is not significantly longer than the computation time of solving a linear program for most of the cycle representatives, using the Gurobi linear solver, 5) strikingly, whether requiring integer solutions or not, we almost always obtain a solution with the same cost and almost all solutions found have entries in { ‐ 1,0,1 } and therefore, are also solutions to a restricted ℓ 0 optimization problem, and 6) we obtain qualitatively different results for generators in Erdős-Rényi random clique complexes than in real-world and synthetic point cloud data.