Local Tuning Research Articles

The approaches for localized surface plasmon resonance wavelength position tuning. Short review

A unique feature of nanoparticles made from highly conductive materials (plasmonic nanoparticles) is that their localized surface plasmon resonance (LSPR) wavelength position can be tuned by changing the shape, size, composition and environment in accordance with the purpose of the application. In this paper, the main mechanisms of LSPR tuning that are available at the present time are reviewed. In particular, a widely used method for tuning the LSPR wavelength position is based on selecting the type of a plasmonic nanoparticle material such as gold, silver, copper, aluminum and gold-silver alloy. The examples of changing the resonance absorption position by using nanoparticles with different shapes and dimensions have been аlso demonstrated. Furthermore, works with less used LSPR tuning methods, such as controlled regulation of the distance between nanoparticles in one and two dimensions have been considered. The number of works is given, where the LSPR wavelength position can be also controlled by changing the environment in the vicinity of plasmonic nanoparticle: the substrate thickness, the thickness and dielectric parameters of the layer on the surface of the nanoparticle. Examples of active influence on the change in the wave position of LSPR by applying an electric potential and regulating plasma modes have been also discussed.

Intrinsic ORR Activity Enhancement of Pt Atomic Sites by Engineering the d-Band Center via Local Coordination Tuning.

A considerable amount of platinum (Pt) is required to ensure an adequate rate for the oxygen reduction reaction (ORR) in fuel cells and metal-air batteries. Thus, the implementation of atomic Pt catalysts holds promise for minimizing the Pt content. In this contribution, atomic Pt sites with nitrogen (N) and phosphorus (P) co-coordination on a carbon matrix (PtNPC) are conceptually predicted and experimentally developed to alter the d-band center of Pt, thereby promoting the intrinsic ORR activity. PtNPC with a record-low Pt content (≈0.026 wt %) consequently shows a benchmark-comparable activity for ORR with an onset of 1.0 VRHE and half-wave potential of 0.85 VRHE . It also features a high stability in 15 000-cycle tests and a superior turnover frequency of 6.80 s-1 at 0.9 VRHE . Damjanovic kinetics analysis reveals a tuned ORR kinetics of PtNPC from a mixed 2/4-electron to a predominately 4-electron route. It is discovered that coordinated P species significantly shifts d-band center of Pt atoms, accounting for the exceptional performance of PtNPC.

Parallel Global Search Algorithm with Local Tuning for Solving Mixed-Integer Global Optimization Problems

Parallel Global Search Algorithm with Local Tuning for Solving Mixed-Integer Global Optimization Problems

Global EM-driven optimization of multi-band antennas using knowledge-based inverse response-feature surrogates

Electromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven design procedures, and may be troublesome even for local tuning of geometry parameters, let alone global optimization. On the one hand, globalized search is often necessary because the design problem might be multimodal (i.e., the objective function features multiple local optima) or a reasonably good initial design may not be available. On the other hand, the computational efficiency of popular algorithmic approaches, primarily, nature-inspired population-based algorithms, is generally poor. Combining metaheuristics procedures with surrogate modelling techniques and sequential sampling methods alleviates the problem to a certain extent but modelling of nonlinear antenna responses over broad frequency ranges is extremely challenging, and the aforementioned solutions are normally limited to rather simple structures described by a few parameters. This paper proposes a novel approach to global optimization of multi-band antennas. The major component of the presented framework is the knowledge-based inverse surrogate constructed at the level of response features (e.g., frequency and level locations of the antenna resonances). The surrogate facilitates decision-making process of inexpensive identification of the most promising regions of the parameter space, and a rendition of the good-quality initial design for further local tuning. Our methodology is validated using three examples of dual- and triple-band antennas. The average optimization cost is only 150 full-wave antenna analyses while ensuring precise allocation of the antenna resonances at the target frequencies. This performance is demonstrated superior over both local optimizers and population-based metaheuristics.

Tuning of a shunted electromagnetic vibration absorber based on the maximisation of the electrical power dissipated

This paper investigates a local tuning approach for a shunted electromagnetic vibration absorber, which is based on the maximisation of the electrical power dissipated by the coil and shunt components. The study considers a simplified problem with a single-degree-of-freedom mechanical hosting system, which is excited by a white noise stochastic force. The hosting system is equipped with a coil-magnet seismic transducer, which is connected to a resistive-inductive shunt. The study examines the effectiveness of the shunted electromagnetic vibration absorber with respect to the following cost functions. Firstly, the reference cost function, which is based on the minimisation of the time-averaged kinetic energy of the hosting system. Secondly, the local cost functions, which are based on: the maximisation of the time-averaged vibration power absorbed by the shunted electromagnetic vibration absorber; the maximisation of the time-averaged mechanical power dissipated by the electromagnetic transducer and the maximisation of the time-averaged electrical power dissipated by the coil and the shunt. The study shows that, provided the transducer is lightly damped, the local cost function based on the maximisation of the electrical power dissipated by the coil and the shunt gives the same optimal tuning parameters than the reference cost function. Therefore, provided the electromagnetic transducer is properly designed, the shunt can be suitably tuned by maximising the time-averaged electrical power dissipated by the coil and shunt. This is a rather appealing practical solution since it can be implemented locally without the need of measuring the response of the hosting system and also it can be implemented in the shunt circuit without the need of extra sensors.

Precise control of immune modulation using DNA scaffold-mediated biomaterial functionalization

Abstract Synthetic materials displaying multi-modal ligands with exact chemiophysical properties for immune modulation are valuable research tools and a promising therapeutic platform. However, precise chemical conjugation of multiple proteins on biomaterial surfaces is challenging. Through DNA hybridization-mediated biomolecule loading, we achieved high density and precise ratiometric control of multiple ligands on nano-/micro-particles. We found increasing ratios of anti-CD3 to anti-CD28, 1:5, 1:3, 1:1, 3:1 to 5:1, on microparticles yielded a linear increase of ex vivo expansion of primary human CD4+ and CD8+ T cells until reaching a plateau at 3:1 ratio. For CD8+ T cells, the ratio of 3:1 resulted in the highest percentage of central memory cells, 51.4 ± 7.2% vs. 14.4 ± 7.6% for 1:5 ratio (n = 5 donors). Particle surface presentation of IL-2 using an anti-IL-2 antibody (in trans to CD3/28 particles) yielded ~3 fold more ex vivo expansion of CD4+ and CD8+ T cells in 14 days when compared to the equivalent dose of soluble IL-2. Using intratumoral injection of microparticles presenting a ligand for a synthetic Notch receptor, we locally induced chimeric antigen receptor (CAR) expression on systemically infused engineered T cells and observed CAR T cell killing of the injected tumors, while sparing the uninjected identical tumors in the contralateral flank. These results highlight the potential of this platform in achieving better control of therapeutic cell manufacture and local tuning of immunotherapies. Ongoing work is using DNA origami-mediated patterning to dissect spatial requirements of various T cell activating ligands to better understand critical parameters of T cell activation with the goal to improve the design of immunotherapies.

Diversity of Receptive Fields and Sideband Inhibition with Complex Thalamocortical and Intracortical Origin in L2/3 of Mouse Primary Auditory Cortex.

Receptive fields of primary auditory cortex (A1) neurons show excitatory neuronal frequency preference and diverse inhibitory sidebands. While the frequency preferences of excitatory neurons in local A1 areas can be heterogeneous, those of inhibitory neurons are more homogeneous. To date, the diversity and the origin of inhibitory sidebands in local neuronal populations and the relation between local cellular frequency preference and inhibitory sidebands are unknown. To reveal both excitatory and inhibitory subfields, we presented two-tone and pure tone stimuli while imaging excitatory neurons (Thy1) and two types of inhibitory neurons (parvalbumin and somatostatin) in L2/3 of mice A1. We classified neurons into six classes based on frequency response area (FRA) shapes and sideband inhibition depended both on FRA shapes and cell types. Sideband inhibition showed higher local heterogeneity than frequency tuning, suggesting that sideband inhibition originates from diverse sources of local and distant neurons. Two-tone interactions depended on neuron subclasses with excitatory neurons showing the most nonlinearity. Onset and offset neurons showed dissimilar spectral integration, suggesting differing circuits processing sound onset and offset. These results suggest that excitatory neurons integrate complex and nonuniform inhibitory input. Thalamocortical terminals also exhibited sideband inhibition, but with different properties from those of cortical neurons. Thus, some components of sideband inhibition are inherited from thalamocortical inputs and are further modified by converging intracortical circuits. The combined heterogeneity of frequency tuning and diverse sideband inhibition facilitates complex spectral shape encoding and allows for rapid and extensive plasticity.SIGNIFICANCE STATEMENT Sensory systems recognize and differentiate between different stimuli through selectivity for different features. Sideband inhibition serves as an important mechanism to sharpen stimulus selectivity, but its cortical mechanisms are not entirely resolved. We imaged pyramidal neurons and two common classes of interneurons suggested to mediate sideband inhibition (parvalbumin and somatostatin positive) in the auditory cortex and inferred their inhibitory sidebands. We observed a higher degree of variability in the inhibitory sideband than in the local frequency tuning, which cannot be predicted from the relative high homogeneity of responses by inhibitory interneurons. This suggests that cortical sideband inhibition is nonuniform and likely results from a complex interplay between existing functional inhibition in the feedforward input and cortical refinement.

Highly Efficient Metasurface Quarter‐Wave Plate with Wave Front Engineering

Metasurfaces with local phase tuning by subwavelength elements promise unprecedented possibilities for ultrathin and multifunctional optical devices in which geometric phase design is widely used due to its resonant‐free and large tolerance in fabrications. By arranging the orientations of anisotropic nanoantennas, the geometric phase‐based metasurfaces can convert the incident spin light to its orthogonal state, and enable flexible wave front engineering together with the function of a half‐wave plate. Herein, by incorporating the propagation phase, another important optical device of quarter‐wave plate together with the wave front engineering as well, which is implemented by controlling both the cross‐ and copolarized light simultaneously with a singlet metasurface, is realized. Highly efficient conversion of the spin light to a variety of linearly polarized light is obtained for meta‐holograms, metalens focusing and imaging in the blue light region. This work provides a new strategy for efficient metasurfaces with both phase and polarization control, and enriches the functionalities of metasurface devices for wider application scenarios.

Semi-active vibration control unit tuned to maximise electric power dissipation

This paper proposes a local approach for the on-line tuning of a semi-active vibration control unit, which is set to reduce the resonant response of target low-order flexural modes of distributed structures subject to broadband stochastic disturbances. The idea is to have multiple self-contained units, which can be fixed on thin walled structures to reduce flexural vibration and sound radiation at low audio frequencies where the dynamics of the structures is controlled by the resonant response of low-order flexural modes. The unit is formed by an electromagnetic seismic transducer connected to a resistive-inductive shunt. The proposed local tuning criterion is based on the maximisation of the time-averaged electrical power dissipated by the shunt. Both simulation and experimental results are presented for a setup where a unit is mounted on a thin plate model wall-structure excited by a broadband random force and is set to reduce the resonant response of target flexural modes. The paper investigates the physics of four tuning criteria with reference to the resonant response of the target flexural natural modes. First, the minimisation of the time-averaged total flexural kinetic energy of the plate; second, the maximisation of the time-averaged vibration power absorbed by the unit; third, the maximisation of the time-averaged mechanical power dissipated by the transducer and fourth, the maximisation of the time-averaged electrical power dissipated by the coil and shunt. The paper shows that, for small mechanical and Eddy currents damping effects of the transducer, the maximisation of the time-averaged electric power dissipated by the coil and shunt gives similar tuning parameters, and thus comparable vibration control effects, than the reference cost function based on the minimisation of the time-averaged total flexural kinetic energy of the plate.

Evolution of atomic-scale dispersion of FeNx in hierarchically porous 3D air electrode to boost the interfacial electrocatalysis of oxygen reduction in PEMFC

Metal-nitrogen-carbon (M-N-C) materials show great advantages for catalyzing the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells (PEMFCs). However, both the low density of single atomic (SA) MNx active sites and restricted mass transfer render these M-N-C based air electrodes inferior in cell performance. In this study, a new ZIF8-derived Fe-N-C catalyst/electrode design combining local chemistry tuning and primary morphology tailoring to address the above two critical issues is shown. The introduction of nitrogen-carbon defects in ZIF8 host enables a controlled atomic-scale dispersion of FeNx moieties, increasing their content in support materials. Also, the simultaneous structural arrangement of individual ZIF8 nano-grains endows the catalyst with a unique porous micro-spheric morphology. This result in an advanced 3D air electrode featuring dense SA FeNx sites and ample, multiscale macro-sized pore channels, which can significantly increase the intrinsic catalytic activity, facilitate bulk mass transport, and generate more effective triple-phase interfaces for ORR. The present catalyst/electrode design exhibits a record large peak power density of ca. 0.60 W cm −2 under practical air conditions. This approach provides a feasible way for boosting the air cathode interfacial ORR and further enlightens electrode designs for energy devices involving multiphase electrochemical reactions. Macro-scale hierarchically porous electrode coupled with enriched atomic FeNx sites is designed to boost the triple-phase interfacial oxygen electrocatalysis. Benefiting from the enhanced intrinsic catalytic activity and improved mass transfer, this air electrode delivers superior high-power density in hydrogen-air PEMFC. • Local chemistry turning and morphology tailoring of the catalyst are simultaneously achieved by a simple strategy. • The introduction of N-C defects promotes the atomic-scale dispersion of FeNx sits and their contents in catalyst. • The structural arrangement of nanosized carbon supports leads to multiscale hierarchically porous 3D air electrode. • The dense single atomic FeNx sites and enhanced mass transfer boost the interfacial ORR at cathode. • The H 2 -air PEMFC with this air cathode delivers a record high power density of ca. 0.60 W cm −2 .

Adaptive Gene Level Mutation

Genetic Algorithms are stochastic optimization methods where solution candidates, complying to a specific problem representation, are evaluated according to a predefined fitness function. These approaches can provide solutions in various tasks even, where analytic solutions can not be or are too complex to be computed. In this paper we will show, how certain set of problems are partially solvable allowing us to grade segments of a solution individually, which results local and individual tuning of mutation parameters for genes. We will demonstrate the efficiency of our method on the N-Queens and travelling salesman problems where we can demonstrate that our approach always results faster convergence and in most cases a lower error than the traditional approach.

Using global Bayesian optimization in ensemble data assimilation: parameter estimation, tuning localization and inflation, or all of the above

Global Bayesian optimization (GBO) is a derivative-free optimization method that is used widely in the tech-industry to optimize objective functions that are expensive to evaluate, numerically or otherwise. We discuss the use of GBO in ensemble data assimilation (DA), where the goal is to update the state of a numerical model in view of noisy observations. Specifically, we consider three tasks: (i) the estimation of model parameters; (ii) the tuning of localization and inflation in ensemble DA; (iii) doing both, i.e. estimating model parameters while simultaneously tuning the localization and inflation of the ensemble DA. For all three tasks, the GBO works ‘offline’, i.e. a set of ‘training’ observations are used within GBO to determine appropriate model or localization/inflation parameters, which are subsequently deployed within an ensemble DA system. Because of the offline nature of the technique, GBO can easily be combined with existing DA systems and it can effectively decouple (nearly) linear/Gaussian aspects of a problem from highly nonlinear/non-Gaussian ones. We illustrate the use of GBO in simple numerical experiments with the classical Lorenz problems. Our main goals are to introduce GBO in the context of ensemble DA and to spark an interest in GBO and its uses for streamlining important tasks in ensemble DA.

Local spin-state tuning of cobalt–iron selenide nanoframes for the boosted oxygen evolution

Tuning local spin state of Co centres by Fe doping in cobalt–iron selenides is effective for boosting oxygen evolution.

Supercontinuum Generation Assisted by Wave Trapping in Dispersion-Managed Integrated Silicon Waveguides

Compact chip-scale comb sources are of significant interest for many practical applications. Here, we experimentally study the generation of supercontinuum (SC) in an axially varying integrated waveguide. We show that the local tuning of the dispersion enables the continuous blue shift of dispersive waves thanks to their trapping by the strongly compressed pump pulse. This mechanism provides new insight into supercontinuum generation in a dispersion varying integrated waveguide. Pumped close to 2.2 $\mu$m in the femtosecond regime and at a pulse energy of $\sim$ 4 pJ, the output spectrum extends from 1.1 $\mu$m up to 2.76 $\mu$m and shows good coherence properties. Octave-spanning SC is also observed at input energy as low as $\sim$ 0.9 pJ. We show that the supercontinuum is more robust against variations of the input pulse parameters and is also spectrally flatter in our numerically optimized waveguide than in fixed-width waveguides. This research demonstrates the potential of dispersion varying waveguides for coherent SC generation and paves the way for integrated low power applications, such as chip-scale frequency comb generation, precision spectroscopy, optical frequency metrology, and wide-band wavelength division multiplexing in the near-infrared.

Spatially compartmentalized phase regulation of a Ca2+-cAMP-PKA oscillatory circuit.

Signaling networks are spatiotemporally organized to sense diverse inputs, process information, and carry out specific cellular tasks. In β cells, Ca2+, cyclic adenosine monophosphate (cAMP), and Protein Kinase A (PKA) exist in an oscillatory circuit characterized by a high degree of feedback. Here, we describe a mode of regulation within this circuit involving a spatial dependence of the relative phase between cAMP, PKA, and Ca2+. We show that in mouse MIN6 β cells, nanodomain clustering of Ca2+-sensitive adenylyl cyclases (ACs) drives oscillations of local cAMP levels to be precisely in-phase with Ca2+ oscillations, whereas Ca2+-sensitive phosphodiesterases maintain out-of-phase oscillations outside of the nanodomain. Disruption of this precise phase relationship perturbs Ca2+ oscillations, suggesting the relative phase within an oscillatory circuit can encode specific functional information. This work unveils a novel mechanism of cAMP compartmentation utilized for localized tuning of an oscillatory circuit and has broad implications for the spatiotemporal regulation of signaling networks.

Thermomechanical Nanostraining of Two-Dimensional Materials.

Local bandgap tuning in two-dimensional (2D) materials is of significant importance for electronic and optoelectronic devices but achieving controllable and reproducible strain engineering at the nanoscale remains a challenge. Here, we report on thermomechanical nanoindentation with a scanning probe to create strain nanopatterns in 2D transition metal dichalcogenides and graphene, enabling arbitrary patterns with a modulated bandgap at a spatial resolution down to 20 nm. The 2D material is in contact via van der Waals interactions with a thin polymer layer underneath that deforms due to the heat and indentation force from the heated probe. Specifically, we demonstrate that the local bandgap of molybdenum disulfide (MoS2) is spatially modulated up to 10% and is tunable up to 180 meV in magnitude at a linear rate of about −70 meV per percent of strain. The technique provides a versatile tool for investigating the localized strain engineering of 2D materials with nanometer-scale resolution.

Inhibition of oxygen dimerization by local symmetry tuning in Li-rich layered oxides for improved stability

Li-rich layered oxide cathode materials show high capacities in lithium-ion batteries owing to the contribution of the oxygen redox reaction. However, structural accommodation of this reaction usually results in O–O dimerization, leading to oxygen release and poor electrochemical performance. In this study, we propose a new structural response mechanism inhibiting O–O dimerization for the oxygen redox reaction by tuning the local symmetry around the oxygen ions. Compared with regular Li2RuO3, the structural response of the as-prepared local-symmetry-tuned Li2RuO3 to the oxygen redox reaction involves the telescopic O–Ru–O configuration rather than O–O dimerization, which inhibits oxygen release, enabling significantly enhanced cycling stability and negligible voltage decay. This discovery of the new structural response mechanism for the oxygen redox reaction will provide a new scope for the strategy of enhancing the anionic redox stability, paving unexplored pathways toward further development of high capacity Li-rich layered oxides.

Smart panel with piezoelectric patches connected to adaptive multi-resonant shunts for broadband vibration control

This paper presents a simulation study on the broadband control of flexural vibration of thin panels equipped with piezoelectric patches connected to adaptive multi-resonant shunts. The study considers the broadband flexural response of a thin rectangular aluminum panel exposed to a spatial and time stochastic excitation. The panel is equipped with thin square piezoelectric patches connect to shunts encompassing multiple parallel branches formed by RLC components connected in series. The capacitance C of each branch is kept fixed, whereas the inductance L and resistance R are adapted so as each branch maximizes the vibration power absorption from the resonant response of a specific flexural mode of the panel. The study proposes an on-line tuning approach, where the N-branches of each shunt are adapted sequentially to maximize the vibration absorption from the resonant responses of N neighbor flexural modes. The vibration power absorption of each branch is estimated from the electric power absorbed by the shunt. In this way a local tuning system can be implemented, which adapts on-line the shunts to control the flexural response produced by a group of flexural modes of the panel resonating in a given frequency band.

Use of Sentinel-2 MSI data to monitor crop irrigation in Mediterranean areas

The availability of accurate information on the water consumed for crop irrigation is of vital importance to support compatible and sustainable environmental policies in arid and semi-arid regions. This has promoted several studies about the use of remote sensing data to monitor irrigated croplands, which are mostly based on statistical classification and/or regression techniques. The current paper proposes a new semi-empirical approach that relies on a water balance logic and does not require local tuning. The method stems from recent investigations which demonstrated the possibility of combining standard meteorological data and Sentinel-2 (S-2) Multi Spectral Instrument (MSI) NDVI images to estimate the actual evapotranspiration (ETa) of irrigated Mediterranean croplands. This ETa estimation method is adapted to drive a simplified site water balance which, for each 10-m S-2 MSI pixel, predicts the irrigation water (IW), i.e. the water which is consumed in addition to that naturally supplied by rainfall. The new method, fed with ground and satellite data from two years (2018–2019), is tested in a Mediterranean area around the town of Grosseto (Central Italy), that is covered by a particularly complex mosaic of rainfed and irrigated crops. The results obtained are first assessed qualitatively for some fields grown with known winter, spring and summer crops. Next, the IW estimates are evaluated quantitatively versus ground measurements taken over two irrigated fields, the first grown with processing tomato in 2018 and the second with early corn in 2019. Finally, the IW estimates are statistically analyzed against various datasets informative on local agricultural practices in the two years. All these analyses indicate that the proposed method is capable of predicting both the intensity and timing of the IW supply in the study area. The method, in fact, correctly identifies rainfed and irrigated crops and, in the latter case, accurately predicts the IW actually supplied. The results of the quantitative tests performed on tomato and corn show that over 50 % and 70 % of the measured IW variance is explained on daily and weekly bases, respectively, with corresponding mean bias errors below 0.3 mm/day and 2.0 mm/week. Similar indications are produced by the qualitative tests; reasonable IW estimates are obtained for all winter, springs and summer crops grown in the study area during 2018 and 2019.

Novel local tuning techniques for speeding up one-dimensional algorithms in expensive global optimization using Lipschitz derivatives

Lipschitz global optimization is an important research field with numerous applications in engineering, electronics, machine learning, optimal decision making, etc. In many of these applications, even in the univariate case, evaluations of the objective functions and derivatives are often time consuming and the number of function evaluations executed by algorithms is extremely high due to the presence of multiple local extrema. As a result, the problem of an acceleration of the global search arises inevitably. In this paper, ideas allowing one to speed up the global search in cases where the objective function has the first derivative satisfying the Lipschitz condition are proposed. Several methods using a priori known global Lipschitz constants, their global and local dynamic estimates are presented. Two new algorithms using smooth piece-wise quadratic support functions are introduced and their convergence conditions are established. All the methods are implemented both in the traditional floating-point arithmetic and in the Infinity Computing framework allowing one to efficiently compute exact derivatives in the case where the optimized function is given as a black box. Numerical experiments executed on two classes of randomly generated test functions show a promising behavior of global optimization methods using the introduced local tuning techniques for speeding up the process of the global search.