BINA

Topological insulators are materials characterized by an insulating bulk and high mobility topologically protected surface states, making them promising candidates for future optoelectronic and quantum devices. Although their electronic properties have been extensively studied, their mid-infrared (MIR) properties and prospective photonic capabilities have not been fully uncovered. Here, we use a combination of far-field and near-field nanoscale imaging and spectroscopy to study chemical vapor deposition-grown Bi2Se3 nanobeams (NBs). We extract the MIR optical constants of Bi2Se3, revealing refractive index values as high as n ∼ 6.4, and demonstrate that the NBs support Mie resonances across the MIR. Local near-field reflection phase mapping reveals domains of various phase shifts, providing information on the local optical properties of the NBs. We experimentally measure up to 2π phase-shift across the …

Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time monitoring. With fiber optics recently becoming a commodity, along with the sound advances in computing power and its miniaturization, multipurpose sensors relying on these technologies have gradually become common. In this study, we explore the development and testing of a multimode optic-fiber-based pipe monitoring and leakage detector based on statistical and machine learning analyses of speckle patterns captured from the fiber’s outlet by a defocused camera. The sensor was placed inside or over a PVC pipe with covered and exposed core configurations, while 2 to 8 mm diameter pipe leaks were simulated under varied water flow and pressure. We found an overall leak size determination accuracy of 75.8% for a 400 µm covered fiber and of 68.3% for a 400 µm exposed fiber and demonstrated that our sensor detected pipe bursts, outside interventions, and shocks. This result was consistent for the sensors fixed inside and outside the pipe with both covered and exposed fibers.

When exposed to specific light wavelengths, carbon dots (CDs), which tend to be fluorescent, can emit colorful light. It provides them with a lot of adaptability for different applications including bioimaging, optoelectronics, and even environmental sensing. Poly(ethylenimine) (PEI) coated carbon dots (PEI-CDs) with a long emission wavelength were synthesized via the hydrothermal method. The resultant CDs show strong fluorescence with quantum yield up to 20.2%. The PEI-CDs exist with distinct pH-sensitive features with pH values in the range of 2–14. The optical characteristics of CDs are pH-responsive due to the presence of different amine groups on PEI, which is a functional polycationic polymer. One of the most widely employed nanoparticles for improving the fluorescence plasmonic characteristics of a nanocomposite is gold. Gold nanoparticles were coupled with PEI-CDs in this assay by using the EDC …

Nanocomposites are constructed from a matrix material combined with dispersed nanosized filler particles. Such a combination yields a powerful ability to tailor the desired mechanical, optical, electrical, thermodynamic, and antimicrobial material properties. Colloidal semiconductor nanocrystals (SCNCs) are exciting potential fillers, as they display size-, shape-, and composition-controlled properties and are easily embedded in diverse matrices. Here we present their role as quantum photoinitiators (QPIs) in acrylate-based polymer, where they act as a catalytic radical initiator and endow the system with mechanical, photocatalytic, and antimicrobial properties. By utilizing ZnO nanorods (NRs) as QPIs, we were able to increase the tensile strength and elongation at break of poly(ethylene glycol) diacrylate (PEGDA) hydrogels by up to 85%, unlike the use of the same ZnO NRs acting merely as fillers. Simultaneously …

A critical current challenge in the development of all-solid-state lithium batteries (ASSLBs) is reducing the cost of fabrication without compromising the performance. Here we report a sulfide ASSLB based on a high-energy, Co-free LiNiO2 cathode with a robust outside-in structure. This promising cathode is enabled by the high-pressure O2 synthesis and subsequent atomic layer deposition of a unique ultrathin LixAlyZnzOδ protective layer comprising a LixAlyZnzOδ surface coating region and an Al and Zn near-surface doping region. This high-quality artificial interphase enhances the structural stability and interfacial dynamics of the cathode as it mitigates the contact loss and continuous side reactions at the cathode/solid electrolyte interface. As a result, our ASSLBs exhibit a high areal capacity (4.65 mAh cm−2), a high specific cathode capacity (203 mAh g−1), superior cycling stability (92% capacity retention …

The disorder induced feedback makes random lasers very susceptible to any changes in the scattering medium. The sensitivity of the lasing modes to perturbations in the disordered systems have been utilized to map the regions of perturbation. A tracking parameter, that takes into account the cumulative effect of changes in the spatial distribution of the lasing modes of the system has been defined to locate the region in which a scatterer is displaced by a few nanometers. We show numerically that the precision of the method increases with the number of modes. The proposed method opens up the possibility of application of random lasers as a tool for monitoring locations of nanoscale displacement which can be useful for single particle detection and monitoring.

Immunoglobulins (IGs), critical components of the human immune system, are composed of heavy and light protein chains encoded at three genomic loci. The IG Kappa (IGK) chain locus consists of two large, inverted segmental duplications. The complexity of IG loci has hindered effective use of standard high-throughput methods for characterizing genetic variation within these regions. To overcome these limitations, we leverage long-read sequencing to create haplotype-resolved IGK assemblies in an ancestrally diverse cohort (n=36), representing the first comprehensive description of IGK haplotype variation at population-scale. We identify extensive locus polymorphism, including novel single nucleotide variants (SNVs) and a common novel ~24.7 Kbp structural variant harboring a functional IGKV gene. Among 47 functional IGKV genes, we identify 141 alleles, 64 (45.4%) of which were not previously curated. We report inter-population differences in allele frequencies for 14 of the IGKV genes, including alleles unique to specific populations within this dataset. Finally, we identify haplotypes carrying signatures of gene conversion that associate with enrichment of SNVs in the IGK distal region. These data provide a critical resource of curated genomic reference information from diverse ancestries, laying a foundation for advancing our understanding of population-level genetic variation in the IGK locus.

Silicate mineral powders (SMP) from weathered granite soil from Kazakhstan are proposed for the desalination of potash brines containing sodium, potassium and chloride ions. Batch adsorption experiments using acid-treated silicate (AS) achieved a Na+/K+/Cl− recovery of ~13/28/6 mg/g. An isothermal study best fitted the Freundlich and Dubinin–Radushkevich models for Na+ and K+/Cl−. The kinetic data were best modeled by pseudo-second-order kinetics for Na+/K+ and pseudo-first-order for Cl−. Thermodynamic calculations showed spontaneity under natural conditions. For Na+/K+, physisorption is accompanied by ion exchange. To study the possibility of sorbent reuse, several cycles of K+/Na+ adsorption–desorption were carried out under optimal conditions. AS selectively adsorbed potassium ions, maintaining a high effectiveness during five cycles providing K-form silicate fertilizers. Leachates of spent AS contain high concentrations of K/Na/Ca/Mg and other microelements essential for plants. Thus, SMP resolve two issues: the desalination of brine and the provision of fertilizer.

Label‐free super‐resolution (LFSR) imaging relies on light‐scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super‐resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state‐of‐the‐art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label‐free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction‐limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super‐resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near‐field scanning, and nonlinear optics approaches, and on designing superlenses based …

Ni-rich, Co-free layered oxide cathode materials are promising candidates for next-generation Li-ion batteries due to their high energy density. However, these cathode materials suffer from rapid capacity fading during electrochemical cycling. To overcome this shortcoming, so-called high-entropy (HE) materials, which are obtained by incorporating multiple dopants, have been suggested. Recent experimental work has shown that HE Ni-rich cathode materials can offer excellent capacity retention on cycling, although a thorough rationale for this has yet to be provided. Here, we present classical and first-principles calculations to elucidate the salient features of HE layered oxides as cathode materials in Li-ion batteries. We suggest that a combination of five prime factors may be responsible for the enhanced performance of HE Ni-rich layered oxide cathode materials over other Ni-rich cathodes: (1) low crystal lattice …

Machine-learning methods (ML) have shown great potential in the adaptive immune receptor repertoire (AIRR) field. However, there is a lack of large-scale ground-truth experimental AIRR data suitable for AIRR-ML-based disease diagnostics and therapeutics discovery. Simulated ground-truth AIRR data are required to complement the development and benchmarking of robust and interpretable AIRR-ML approaches where experimental data is inaccessible or insufficient as of yet. The challenge for simulated data to be useful is the ability to incorporate key features observed in experimental repertoires. These features, such as complex antigen or disease-associated immune information, cause AIRR-ML problems to be challenging. Here, we introduce LIgO, a modular software suite, which simulates AIRR data for the development and benchmarking of AIRR-based machine learning. LIgO incorporates different types of immune information both on the receptor and the repertoire level and preserves native-like generation probability distribution. Additionally, LIgO assists users in determining the computational feasibility of their simulations. We show two examples where LIgO simulation supports the development and validation of AIRR-ML methods: (1) how individuals carrying out-of-distribution immune information impacts receptor-level prediction performance and (2) how immune information co-occurring in the same AIRs have an impact on the performance of conventional receptor-level encoding and repertoire-level classification approaches. The LIgO software guides the advancement and assessment of interpretable AIRR-ML methods.

Recent work has revealed the central role played by the Kirkwood-Dirac quasiprobability (KDQ) as a tool to properly account for non-classical features in the context of condensed matter physics (scrambling, dynamical phase transitions) metrology (standard and post-selected), thermodynamics (power output and fluctuation theorems), foundations (contextuality, anomalous weak values) and more. Given the growing relevance of the KDQ across the quantum sciences, our aim is two-fold: First, we highlight the role played by quasiprobabilities in characterizing the statistics of quantum observables and processes in the presence of measurement incompatibility. In this way, we show how the KDQ naturally underpins and unifies quantum correlators, quantum currents, Loschmidt echoes, and weak values. Second, we provide novel theoretical and experimental perspectives by discussing a wide variety of schemes to access the KDQ and its non-classicality features.

Multilayer network is a potent platform which paves a way to study the interactions among entities in various networks with multiple types of relationships. In this study, the dynamics of discrete-time quantum walk on a multilayer network are explored in detail. We derive recurrence formulae for the coefficients of the wave function of a quantum walker on an undirected graph with finite number of nodes. By extending these formulae to include extra layers, we develop a simulation model to describe the time-evolution of the quantum walker on a multilayer network. The time-averaged probability and the return probability of the quantum walker are studied in relation to Fourier and Grover walks on multilayer networks. Furthermore, we analyze the impact of decoherence on the quantum transport, shedding light on how environmental interactions may impact the behavior of quantum walkers on multilayer network structures.

Large grid energy storage devices are critical for the success of the clean and sustainable energy revolution. As Li-ion batteries are earmarked for electric vehicles and portable devices such as laptops and cellphones, other electrochemical systems should be developed that enable cost-effective, safe, and durable large-scale energy storage. Due to the low cost and non-flammability of aqueous electrolyte solutions, much effort is being put into development of 'beyond-Li' batteries and supercapacitors that can work in these environments. Here, we propose new proton batteries comprising an acetic acid electrolyte solution, NiII[FeIII(CN)6]2/3·4H2O Prussian blue analog cathodes, and Ti3C2Tx MXene anodes. Both electrodes were investigated independently to discover ideal settings for electrochemical performance and stability. Significant attention was given to the cathodes' protons storage mechanism. In-situ …

Ni-rich, Co-free layered oxide cathode materials are promising candidates for next-generation Li-ion batteries due to their high energy density. However, these cathode materials suffer from rapid capacity fading during electrochemical cycling. To overcome this shortcoming, so-called high-entropy (HE) materials, which are obtained by incorporating multiple dopants, have been suggested. Recent experimental work has shown that HE Ni-rich cathode materials can offer excellent capacity retention on cycling, although a thorough rationale for this has yet to be provided. Here, we present classical and first-principles calculations to elucidate the salient features of HE layered oxides as cathode materials in Li-ion batteries. We suggest that a combination of five prime factors may be responsible for the enhanced performance of HE Ni-rich layered oxide cathode materials over other Ni-rich cathodes: (1) low crystal lattice …

Topological insulators are materials characterized by an insulating bulk and high mobility topologically protected surface states, making them promising candidates for future optoelectronic and quantum devices. Although their electronic properties have been extensively studied, their mid-infrared (MIR) properties and prospective photonic capabilities have not been fully uncovered. Here, we use a combination of far-field and near-field nanoscale imaging and spectroscopy to study chemical vapor deposition-grown Bi2Se3 nanobeams (NBs). We extract the MIR optical constants of Bi2Se3, revealing refractive index values as high as n ∼ 6.4, and demonstrate that the NBs support Mie resonances across the MIR. Local near-field reflection phase mapping reveals domains of various phase shifts, providing information on the local optical properties of the NBs. We experimentally measure up to 2π phase-shift across the …

We study the motion of an overdamped particle connected to a thermal heat bath in the presence of an external periodic potential. When the coarse-graining is larger than the periodicity of the potential, the packet of spreading particles, all starting from a common origin, converges to a normal distribution centered at the origin with a mean-squared displacement that grows like , with an effective diffusion constant that is smaller than that of a freely diffusing particle. We examine the interplay between this coarse-grained description and the fine structure of the density, which is given by the Boltzmann-Gibbs factor , the latter being non-normalizable. We explain this result and construct a theory of observables using the Fokker-Planck equation. These observables are classified as those that are related to the BG fine structure, like the energy or occupation times, while others, like the positional moments, for long times, converge to those of the large-scale description. Entropy falls into a special category as it has a coarse-grained and a fine structure description. The basic thermodynamic formula is extended to this far from equilibrium system. The ergodic properties are also studied using tools from infinite ergodic theory.