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Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow.

Abstract: Superconducting magnets of future fusion reactors are expected to rely on composite high-temperature superconductor (HTS) cable conductors. In presently used HTS cables, current sharing between components is limited due to poorly defined contact resistances between superconducting tapes or by design. The interplay between contact and termination resistances is the defining factor for power dissipation in these cables and ultimately defines their safe operational margins. However, the current distribution between components along the composite conductor and inside its terminations is a priori unknown, and presently, no means are available to actively tune current flow distribution in real-time to improve margins of quench protection. Also, the lack of ability to electrically probe individual components makes it impossible to identify conductor damage locations within the cable. In this work, we address both problems by introducing active current control of current distribution between components using cryogenically operated metal-oxide-semiconductor-field-effect transistors (MOSFETs). We demonstrate through simulation and experiments how real-time current controls can help to drastically reduce heat dissipation in a developing hot spot in a two-conductor model system and help identify critical current degradation of individual cable components. Prospects of other potential uses of MOSFET devices for improved voltage detection, AC loss-driven active quench protection, and remnant magnetization reduction in HTS magnets are also discussed.

The applications of hyperspectral imaging across disciplines such as healthcare, automobiles, forensics, and astronomy are constrained by the requirement for intricate filters and dispersion lenses. By utilization of devices with engineered spectral responses and advanced signal processing techniques, the spectral imaging process can be made more approachable across various fields. We propose a spectral response design method employing photon-trapping surface textures (PTSTs), which eliminates the necessity for external diffraction optics and facilitates system miniaturization. We have developed an analytical model to calculate electromagnetic wave coupling using the effective refractive index of silicon in the presence of PTST. We have extensively validated the model against simulations and experimental data, ensuring the accuracy of our predictions. We observe a strong linear relationship between the peak coupling wavelength and the PTST period along with a moderate proportional relation to the PTST diameters. Additionally, we identify a significant correlation between inter-PTST spacing and wave propagation modes. The experimental validation of the model is conducted using PTST-equipped photodiodes fabricated through complementary metal-oxide-semiconductor-compatible processes. Further, we demonstrate the electrical and optical performance of these PTST-equipped photodiodes to show high speed (response time: 27 ps), high gain (multiplication gain, M: 90), and a low operating voltage (breakdown voltage: ∼ 8.0 V). Last, we utilize the distinctive response of the fabricated PTST-equipped photodiode to simulate hyperspectral imaging, providing a proof of principle. These findings are crucial for the progression of on-chip integration of high-performance spectrometers, guaranteeing real-time data manipulation, and cost-effective production of hyperspectral imaging systems.

Recently, the use of uncrewed aerial vehicles (UAVs) in joint sensing and communication applications has received a lot of attention. However, integrating UAVs in current cellular systems presents major challenges related to trajectory optimization and interference management among others. This paper considers a multi-cell network including a UAV, which senses and forwards the sensory data from different events to the central base station. Particularly, the current manuscript covers how to design the UAV's ({i} ) 3D trajectory, (ii) power allocation, and (iii) sensing scheduling such that (a) a set of events are sensed, (b) interference to neighboring cells is kept at bay, and (c) the amount of energy required by the UAV is minimized. The resulting nonconvex optimization problem is tackled through a combination of ({i} ) low-complexity binary optimization, (ii) successive convex approximation, and (iii) the Lagrangian method. Simulation results over a range of various key parameters have shown the merits of our approach, which consumes 33%-200% less energy compared to different benchmarks.

The effects of optical feedback on a terahertz (THz) quantum-cascade metasurface vertical-external-cavity surface-emitting laser (QC-VECSEL) are investigated via self-mixing. A single-mode 2.80 THz QC-VECSEL operating in continuous-wave is subjected to various optical feedback conditions (i.e., feedback strength, round-trip time, and angular misalignment) while variations in its terminal voltage associated with self-mixing are monitored. Due to its large radiating aperture and near-Gaussian beam shape, we find that the QC-VECSEL is strongly susceptible to optical feedback, which is robust against misalignment of external optics. This, in addition to the use of a high-reflectance flat output coupler, results in high feedback levels associated with multiple round-trips within the external cavity-a phenomenon not typically observed for ridge-waveguide QC-lasers. Thus, a new theoretical model is established to describe self-mixing in the QC-VECSEL. The stability of the device under variable optical feedback conditions is also studied. Any mechanical instabilities of the external cavity (such as vibrations of the output coupler), are enhanced due to feedback and result in low-frequency oscillations of the terminal voltage. The work reveals how the self-mixing response differs for the QC-VECSEL architecture, informs other systems in which optical feedback is unavoidable, and paves the way for QC-VECSEL self-mixing applications.

This paper presents a single-chip bits-to-antenna transmitter (TX) for >100 Gbps in 45nm CMOS SOI. The construction of the 64QAM constellation is achieved directly in the RF domain by utilizing three QPSK sub-TXs with weighted amplitude. This method significantly reduces the need to address power amplifier nonlinear effects in high-order modulation, thereby creating room for TX enhancements in both bandwidth and output power. To further improve TX performance, multi-step phase alignment strategies, and a local oscillator leakage suppression technique have been incorporated. With 40-GHz RF bandwidth, the RF-64QAM TX prototype is able to achieve a measured data rate of 120 Gbps with 15dBm effective isotropic radiated power (EIRP).

Infrared scattering-type near-field optical microscopy, IR s-SNOM, and its broadband variant, nano-FTIR, are pioneering, flagship techniques for their ability to provide molecular identification and material optical property information at a spatial resolution well below the far-field diffraction limit, typically less than 25 nm. While s-SNOM and nano-FTIR instrumentation and data analysis have been discussed previously, there is a lack of information regarding experimental parameters for the practitioner, especially in the context of previously developed frameworks. Like conventional FTIR spectroscopy, the critical component of a nano-FTIR instrument is an interferometer. However, unlike FTIR spectroscopy, the resulting interference patterns or interferograms are typically asymmetric. Here, we unambiguously describe the origins of asymmetric interferograms recorded with nano-FTIR instruments, give a detailed analysis of potential artifacts, and recommend optimal instrument settings as well as data analysis parameters.

Design strategies for improving terahertz (THz) quantum cascade lasers (QCLs) in the 5-6 THz range are investigated numerically and experimentally, with the goal of overcoming the degradation in performance that occurs as the laser frequency approaches the Reststrahlen band. Two designs aimed at 5.4 THz were selected: one optimized for lower power dissipation and one optimized for better temperature performance. The active regions exhibited broadband gain, with the strongest modes lasing in the 5.3-5.6 THz range, but with other various modes observed ranging from 4.76 to 6.03 THz. Pulsed and continuous-wave (cw) operation is observed up to temperatures of 117 K and 68 K, respectively. In cw mode, the ridge laser has modes up to 5.71 THz - the highest reported frequency for a THz QCL in cw mode. The waveguide loss associated with the doped contact layers and metallization is identified as a critical limitation to performance above 5 THz.

There is an increasing desire to utilize complex functional electronic materials such as ferroelectrics in next-generation microelectronics. As new materials are considered or introduced in this capacity, an understanding of how we can process these materials into those devices must be developed. Here, the effect of different fabrication processes on the ferroelectric and related properties of prototypical metal oxide (SrRuO3)/ferroelectric (BaTiO3)/metal oxide (SrRuO3) heterostructures is explored. Two different types of etching processes are studied, namely, wet etching of the top SrRuO3 using a NaIO4 solution and dry etching using an Ar+-ion beam (i.e., ion milling). Polarization-electric-field hysteresis loops for capacitors produced using both methods are compared. For the ion-milling process, it is found that the Ar+ beam can introduce defects into the SrRuO3/BaTiO3/SrRuO3 devices and that the milling depth strongly influences the defect level and can induce a voltage imprint on the function. Realizing that such processing approaches may be necessary, work is performed to ameliorate the imprint of the hysteresis loops via ex situ “healing” of the process-induced defects by annealing the ferroelectric material in a barium-and-oxygen-rich environment via a chemical-vapor-deposition-style process. This work provides a pathway for the nanoscale fabrication of these candidate materials for next-generation memory and logic applications.

Mechanobiology helps us to decipher cell and tissue functions by looking at changes in their mechanical properties that contribute to development, cell differentiation, physiology, and disease. Mechanobiology sits at the interface of biology, physics and engineering. One of the key technologies that enables characterization of properties of cells and tissue is microscopy. Combining microscopy with other quantitative measurement techniques such as optical tweezers and scissors, gives a very powerful tool for unraveling the intricacies of mechanobiology enabling measurement of forces, torques and displacements at play. We review the field of some light based studies of mechanobiology and optical detection of signal transduction ranging from optical micromanipulation─optical tweezers and scissors, advanced fluorescence techniques and optogenentics. In the current perspective paper, we concentrate our efforts on elucidating interesting measurements of forces, torques, positions, viscoelastic properties, and optogenetics inside and outside a cell attained when using structured light in combination with optical tweezers and scissors. We give perspective on the field concentrating on the use of structured light in imaging in combination with tweezers and scissors pointing out how novel developments in quantum imaging in combination with tweezers and scissors can bring to this fast growing field.

Photo-mediated ultrasound therapy (PUT) is a novel antivascular therapeutic modality based on cavitation-induced bioeffects. During PUT, synergistic combinations of laser pulses and ultrasound bursts are used to remove the targeted microvessels selectively and precisely without harming nearby tissue. In the current study, an integrated system combining PUT and spectral domain optical coherence tomography (SD-OCT) was developed, where the SD-OCT system was used to guide PUT by detecting cavitation in real time in the retina of the eye.MethodWe first examined the capability of SD-OCT in detecting cavitation on a vascular-mimicking phantom and compared the results with those from a passive cavitation detector. The performance of the integrated system in treatment of choroidal microvessels was then evaluated in rabbit eyes in vivo.ResultsDuring the in vivo PUT experiments, several biomarkers at the subretinal layer in the rabbit eye were identified on OCT images. The findings indicate that, by evaluating biomarkers of treatment effect, real-time SD-OCT monitoring could help to avoid micro-hemorrhage, which is a potential major side effect.ConclusionReal-time OCT monitoring can thus improve the safety and efficiency of PUT in removing the retinal and choroidal microvasculature.

An ultra-broadband beam splitter arrangement, with a spectral amplitude response that is over seven orders-of-magnitude more uniform than broadband, multi-layer dielectric beam splitters, can be created by the combination of multiple Fresnel events on an uncoated, optical flat when used at a specific angle-of-incidence. This beam splitter arrangement produces three, spectral copies of the original, two of which have identical spectral phase. In this manuscript we derive the precise angle at which this maximally flat spectral amplitude response occurs for any material and present this angle’s material and polarization dependence.

The use of uncrewed aerial vehicles (UAVs) in cell-free networks is poised to unleash a number of new opportunities to further improve wireless networks. However, cell-free UAV networks present major challenges related to the wireless nature of access and fronthaul links. This manuscript studies the uplink of cell-free systems where users connect to UAVs, the latter devices forwarding the information to a processing point through imperfect wireless fronthaul links. Three multiple access alternatives are considered for the fronthaul, namely frequency division multiples access, spatial division multiple access, and combinations thereof. Deterministic equivalent expressions for the spectral efficiency under these fronthaul schemes and minimum mean-square error reception are derived. Then, the optimization subproblems of (a) the 3D deployment of the UAVs, (b) the user transmit powers, and (c) the UAV transmit powers, are investigated. The joint optimization of these subproblems yields superior performance, with the 3D deployment being the main source of improvement.

Predictive high-fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch-control, stall/vortex-induced vibrations, and aftermarket add-ons. The biggest challenge with high-fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high-performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU-enabled open-source incompressible-flow hybrid-computational fluid dynamics framework, comprising the near-body unstructured grid solver Nalu-Wind, and the off-body block-structured-grid solver AMR-Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds-averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds-averaged Navier–Stokes is used for near-body flow and large eddy simulation is used for off-body flow. Being two-way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry-resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt-scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

Coupling of power-to-gas processes with underground gas storage could effectively allow surplus electricity to be stored for later use. Depleted hydrocarbon reservoirs could be used as stores, but practical experience of hydrogen storage in such sites is limited. Here we present data from a field trial that stored 119,353 m3 of hydrogen admixed to natural gas in a depleted hydrocarbon reservoir. After 285 days, hydrogen recovery was 84.3%, indicating the process’s technical feasibility. Additionally, we report that microbes mediated hydrogen conversion to methane. In laboratory experiments studying mesocosms that mimic real reservoirs, hydrogen and carbon dioxide were converted to methane (0.26 mmol l−1 h−1 evolution rate) reproducibly over 14 cycles in 357 days. This rate theoretically allows 114,648 m3 of methane per year to be produced in the test reservoir (equivalent to ~1.08 GWh). Our research demonstrates the efficiency of hydrogen storage and the importance of geo-methanation in depleted hydrocarbon reservoirs.

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. In this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

We study a heterogeneous Rayleigh fading wireless sensor network (WSN) in which sensor nodes surveil a field of interest and communicate their sensory data with base stations with the aid of access points as relays. With the goal of improving the energy efficiency of the network, we consider both large-scale and small-scale signal propagation effects in our system model and aim to optimize the node deployment as an effective measure to reduce the wireless communication power consumption of the WSN. We propose a new framework, in which hard deterministic connectivity constraints on communication links are replaced with realistic limitations on outage due to severe stochastic fading. We also consider a radio energy model that reflects the exponential dependence of the transmission power on the rate. We derive the necessary conditions for the optimal deployment that not only minimize the power consumption, but also guarantee all wireless links to have an outage probability below the given threshold. Our theoretical findings are accompanied by simulations that indicate significant performance gains compared to existing node deployment algorithms in the literature.

We present a new framework based on quantization theory to design cellular networks optimized for both legacy ground users and uncrewed aerial vehicle (UAV) corridors, dedicated aerial highways for safe UAV flights. Our framework leverages antenna tilts and transmit power at each base station to enhance coverage and quality of service among users. We develop a comprehensive mathematical analysis and optimization algorithms for multiple system-level performance metrics, including received signal strength and signal-to-interference-plus-noise ratio. Realistic antenna radiation patterns and propagation channel models are considered, alongside a generic 3D user distribution that allows for performance prioritization on the ground, along UAV corridors, or a desired tradeoff between the two. We demonstrate the efficacy of the proposed framework through case studies, showcasing the non-trivial combinations of antenna tilts and power levels that improve coverage and signal quality along UAV corridors while incurring only a marginal impact on the ground user performance compared to scenarios without UAVs.

Uncrewed Aerial Vehicles (UAVs) provide a compelling solution for data collection in Internet of Things (IoT) networks due to their mobility and adaptability. However, the line-of-sight dominance in their channels may result in severe interference to ground users during UAV operations. To address this, we present an optimization framework that concurrently optimizes UAV trajectories and transmit powers. Our approach efficiently results in the collection of data from a variety of IoT sensors while (a) minimizing the UAVs flying time and (b) mitigating interference with terrestrial networks. Given the complex nature of such an optimization problem, this paper leverages reinforcement learning, specifically the twin delayed deep deterministic policy gradient algorithm, where a distributed learning algorithm is presented. Experimental results validate the efficacy of our proposed approach, demonstrating its capability to significantly enhance data collection in IoT networks while minimizing UAV flight time and interference with ground user links.

The complexity of information processing in the brain requires the development of technologies that can provide spatial and temporal resolution by means of dense electrode arrays paired with high-channel-count signal acquisition electronics. In this work, we present an ultra-low noise modular 512-channel neural recording circuit that is scalable to up to 4096 simultaneously recording channels. The neural readout application-specific integrated circuit (ASIC) uses a dense 8.2 mm × 6.8 mm 2D layout to enable high-channel count, creating an ultra-light 350 mg flexible module. The module can be deployed on headstages for small animals like rodents and songbirds, and it can be integrated with a variety of electrode arrays. The chip was fabricated in a TSMC 0.18 µm 1.8 V CMOS technology and dissipates a total of 125 mW. Each DC-coupled channel features a gain and bandwidth programmable analog front-end along with 14 b analog-to-digital conversion at speeds up to 30 kS/s. Additionally, each front-end includes programmable electrode plating and electrode impedance measurement capability. We present both standalone and in vivo measurements results, demonstrating the readout of spikes and field potentials that are modulated by a sensory input.

Community solar, a business model where multiple customers buy output from shared solar systems, has expanded solar access among multifamily housing occupants, renters, and low-income households. Policies to enable community solar could be expanded and benefits of access augmented through targeted measures to support community solar adoption in underserved communities.

Correction to: Nature Energyhttps://doi.org/10.1038/s41560-024-01546-2, published online 3 June 2024 In the version of the article initially published, data in Fig. 5b–d were displayed incorrectly and have now been amended in the HTML and PDF versions of the article. The original and corrected figures can be seen below in Fig. 1. (Figure presented.)

Abstract: The introduction of chiral organic spacers in low‐dimensional metal‐halide perovskites triggers chiroptical activity, which is appealing for spintronic applications. However, a comprehensive understanding of structure formation and the ability to control phase purity in such materials have yet to be developed. Herein, the impact of processing conditions on the phase purity, microstructure, and chiroptical properties of chiral 2D perovskites is explored. The anisotropic emergence of a 1D perovskite inside the 2D matrix and its dependence on the organic cation chirality, solvent, and thermal annealing conditions are shown. By controlling these parameters, the in‐plane conductivity of the films is nearly doubled. Furthermore, it is demonstrated, for the first time, that solvent choice and the spatial configuration of the organic cation can have an impact on the residual lattice strain and the energetic disorder of the system. The fundamentals presented here can help to improve the film deposition methods for low‐dimensional chiral perovskites, offering strategies to control phase purity.

Rooftop and community solar are alternative product classes for residential solar in the United States. Community solar, where multiple households buy solar from shared systems, could make solar more accessible by reducing initial costs and removing adoption barriers for renters and multifamily building occupants. Here we test whether community solar has expanded solar access in the United States. On the basis of a sample of 11 states, we find that community solar adopters are about 6.1 times more likely to live in multifamily buildings than rooftop solar adopters, 4.4 times more likely to rent and earn 23% less annual income. We do not find that community solar expands access in terms of race. These differences are driven, roughly evenly, by inherent differences between the two solar products and by policies to promote low-income community solar adoption. The results suggest that alternative solar products can expand solar access and that policy could augment such benefits.

In this paper, we consider the advantages of an alternative design concept for HTS accelerator magnets operating at 20 K or above. The idea is primarily built on using REBCO tape as the main conductor, but may be applicable to other HTS. The key concepts are to align REBCO tapes in the most favourable field orientation and to make joints for every turn such that the tapes will not have to be wound over the saddle ends. We argue that such a concept involving resistive joints is viable at 20 K or above due to an increased cryogenic efficiency, and has multiple advantages that would more than compensate for the resistive heating cost penalty. First, the favourable tape orientation can allow a much higher current carrying capability. Second, the short unit length of tapes equal to the length of the magnet will be much more economical and can be specified at a higher performance than a long continuous piece equal to the number of turns multiplied by the length of the magnet. Third, any defective conductor can be replaced easily and at a much lower cost than an entire coil. Fourth, with each tape separately sourced and connected, efficient grading with stress management can be achieved. Fifth, the straight section of the magnet would be modular and easily scalable for production in industry. Correspondingly, the most challenging part is the end cap design and joint technology, whose geometrical constraints are well within national laboratories' capabilities, making the R&D and prototyping phases much more affordable, with a turnover time much quicker than testing full size magnets. Additional attractive potentials include conductor development (e.g., double-sided extra thick REBCO), novel diagnostics (e.g., individual tape quench detection and protection), synergy with fusion devices research (e.g., demountable joints), and other possibilities.

The problem of maintaining power system stability and performance after the failure of any single line in a power system (an “$N-1$ contingency”) is investigated. Due to the large number of possible $N-1$ contingencies for a power network, it is impractical to optimize controller parameters for each possible contingency a priori. A method to partition a set of contingencies into groups of contingencies that are similar to each other from a control perspective is presented. Design of a single controller for each group, rather than for each contingency, provides a computationally tractable method for maintaining stability and performance after element failures. The choice of number of groups tunes a trade-off between computation time and controller performance for a given set of contingencies. Results are simulated on the IEEE 39-bus and 68-bus systems, illustrating that, with controllers designed for a relatively small number of groups, power system stability may be significantly improved after an $N-1$ contingency compared to continued use of the nominal controller. Furthermore, performance is comparable to that of controllers designed for each contingency individually.

This paper introduces an innovative approach to 3D environmental mapping through the integration of a compact, handheld sensor package with a two-stage sensor fusion pipeline. The sensor package, incorporating LiDAR, IMU, RGB, and thermal cameras, enables comprehensive and robust 3D mapping of various environments. By leveraging Simultaneous Localization and Mapping (SLAM) and thermal imaging, our solution offers good performance in conditions where global positioning is unavailable and in visually degraded environments. The sensor package runs a real-time LiDAR-Inertial SLAM algorithm, generating a dense point cloud map that accurately reconstructs the geometric features of the environment. Following the acquisition of that point cloud, we post-process these data by fusing them with images from the RGB and thermal cameras and produce a detailed, color-enriched 3D map that is useful and adaptable to different mission requirements. We demonstrated our system in a variety of scenarios, from indoor to outdoor conditions, and the results showcased the effectiveness and applicability of our sensor package and fusion pipeline. This system can be applied in a wide range of applications, ranging from autonomous navigation to smart agriculture, and has the potential to make a substantial benefit across diverse fields.

All-optical tunability of semiconductor metasurfaces offers unique opportunities for novel time-varying effects, including frequency conversion and light trapping. However, the all-optical processes often induce optical absorption that fundamentally limits the possible dynamic increase of their quality factor (Q-boosting). Here, we propose and numerically demonstrate the concept of large Q-boosting in a single-material metasurface by dynamically reducing its structural anisotropy on a femtosecond timescale. This balance is achieved by excitation with a structured pump and takes advantage of the band-filling effect in a GaAs direct-bandgap semiconductor to eliminate the free-carrier-induced loss. We show that this approach allows a dynamic boosting of the resonance quality factor over orders of magnitude, only limited by the free-carrier relaxation processes. The proposed approach offers complete dynamic control over the resonance bandwidth and opens applications in frequency conversion and light trapping.

Abstract: Nanostructured plasmonic surfaces allow for precise tailoring of electromagnetic modes within sub-diffraction mode volumes, boosting light–matter interactions. This study explores vibrational strong coupling (VSC) between molecular ensembles and subradiant “dark” cavities that support infrared quadrupolar plasmonic resonances (QPLs). The QPL mode exhibits a dispersion characteristic of bound states in the continuum (BIC). That is, the mode is subradiant or evanescent at normal incidence and acquires increasing “bright” dipole character with larger in-plane wavevectors. We deposited polymethyl methacrylate (PMMA) thin films on QPL substrates to induce VSC with the carbonyl stretch in PMMA and measured the resulting infrared (IR) spectra. Our computational analysis predicts the presence of “dark” subradiant polariton states within the near-field of the QPL mode, and “bright” collective molecular states. This finding is consistent with classical and quantum mechanical descriptions of VSC that predict hybrid polariton states with cavity-like modal character and N−1 collective molecular states with minimal cavity character. However, the behaviour is opposite of what is standardly observed in VSC experiments that use “bright” cavities, which results in “bright” polariton states that can be spectrally resolved as well as N−1 collective molecular states that are spectrally absent. Our experiments confirm a reduction of molecular absorption and other spectral signatures of VSC with the QPL mode. In comparison, our experiments promoting VSC with dipolar plasmonic resonances (DPLs) reproduce the conventional behavior. Our results highlight the significance of cavity mode symmetry in modifying the properties of the resultant states from VSC, while offering prospects for direct experimental probing of the N−1 molecule-like states that are usually spectrally “dark”.

Abstract: One of the most significant and surprising recent developments in nanocrystal studies was the observation of superfluorescence from a system of self-assembled, colloidal perovskite nanocrystals [G. Rainò, M. A. Becker, M. I. Bodnarchuk, R. F. Mahrt, M. V. Kovalenko, and T. Stöferle, “Superfluorescence from lead halide perovskite quantum dot superlattices,” Nature, vol. 563, no. 7733, pp. 671–675, 2018]. Superfluorescence is a quantum-light property in which many dipoles spontaneously synchronize in phase to create a collective, synergistic photon emission with a much faster lifetime. Thus, it is surprising to observe this in more inhomogenous systems as solution-processed and colloidal structures typically suffer from high optical decoherence and non-homogeneous size distributions. Here we outline recent developments in the demonstration of superfluorescence in colloidal and solution-processed systems and explore the chemical and materials science opportunities allowed by such systems. The ability to create bright and tunable superfluorescent sources could enable transformative developments in quantum information applications and advance our understanding of quantum phenomena.

Inertial measurement units (IMUs) provide exciting opportunities to collect large volumes of running biomechanics data in the real world. IMU signals may, however, be affected by variation in the initial IMU placement or movement of the IMU during use. To quantify the effect that changing an IMU's location has on running data, a reference IMU was 'correctly' placed on the shank, pelvis, or sacrum of 74 participants. A second IMU was 'misplaced' 0.05 m away, simulating a 'worst-case' misplacement or movement. Participants ran over-ground while data were simultaneously recorded from the reference and misplaced IMUs. Differences were captured as root mean square errors (RMSEs) and differences in the absolute peak magnitudes and timings. RMSEs were ≤1 g and ~1 rad/s for all axes and misplacement conditions while mean differences in the peak magnitude and timing reached up to 2.45 g, 2.48 rad/s, and 9.68 ms (depending on the axis and direction of misplacement). To quantify the downstream effects of these differences, initial and terminal contact times and vertical ground reaction forces were derived from both the reference and misplaced IMU. Mean differences reached up to -10.08 ms for contact times and 95.06 N for forces. Finally, the behavior in the frequency domain revealed high coherence between the reference and misplaced IMUs (particularly at frequencies ≤~10 Hz). All differences tended to be exaggerated when data were analyzed using a wearable coordinate system instead of a segment coordinate system. Overall, these results highlight the potential errors that IMU placement and movement can introduce to running biomechanics data.

Distribution grid reliability and resilience has become a major topic of concern for utilities and their regulators. In particular, with the increase in severity of extreme events, utilities are considering major investments in distribution grid assets to mitigate the damage of highly impactful outages. Communicating the overall economic and risk-mitigation benefits of these investments to regulators is an important element of the approval process. Today, industry reliability and resilience planning practices are based largely on methods that do not take explicit account of risk. This paper proposes a practical method for identifying optimal combinations of investments in new line segments and storage devices while considering the balance between the risk associated with high impact and low probability (HILP) events and the reliability related to routine failures. We show that this method can be scaled to address large scale networks and demonstrate its benefits using a Target Feeder from the Commonwealth Edison Reliability Program.

Histological staining of tissue biopsies, especially hematoxylin and eosin (H&E) staining, serves as the benchmark for disease diagnosis and comprehensive clinical assessment of tissue. However, the process is laborious and time-consuming, often limiting its usage in crucial applications such as surgical margin assessment. To address these challenges, we combine an emerging 3D quantitative phase imaging technology, termed quantitative oblique back illumination microscopy (qOBM), with an unsupervised generative adversarial network pipeline to map qOBM phase images of unaltered thick tissues (i.e., label- and slide-free) to virtually stained H&E-like (vH&E) images. We demonstrate that the approach achieves high-fidelity conversions to H&E with subcellular detail using fresh tissue specimens from mouse liver, rat gliosarcoma, and human gliomas. We also show that the framework directly enables additional capabilities such as H&E-like contrast for volumetric imaging. The quality and fidelity of the vH&E images are validated using both a neural network classifier trained on real H&E images and tested on virtual H&E images, and a user study with neuropathologists. Given its simple and low-cost embodiment and ability to provide real-time feedback in vivo, this deep learning-enabled qOBM approach could enable new workflows for histopathology with the potential to significantly save time, labor, and costs in cancer screening, detection, treatment guidance, and more.

The solid-electrolyte interphase (SEI) critically governs the performance of rechargeable batteries. An ideal SEI is expected to be electrically insulative to prevent persistently parasitic reactions between the electrode and the electrolyte and ionically conductive to facilitate Faradaic reactions of the electrode. However, the true nature of the electrical properties of the SEI remains hitherto unclear due to the lack of a direct characterization method. Here we use in situ bias transmission electron microscopy to directly measure the electrical properties of SEIs formed on copper and lithium substrates. We reveal that SEIs show a voltage-dependent differential conductance. A higher rate of differential conductance induces a thicker SEI with an intricate topographic feature, leading to an inferior Coulombic efficiency and cycling stability in Li∣∣Cu and Li∣∣LiNi0.8Mn0.1Co0.1O2 cells. Our work provides insight into the targeted design of the SEI with desired characteristics towards better battery performance.

Metal halide perovskites have witnessed great success in green, red, and near-infrared light-emitting diodes (LEDs), yet blue LEDs still lag behind. Reducing undesired energetic disorders – broad n-phases and halide segregation – is considered as the most critical strategy to further improve the performances. Here, the study reports a newly designed and synthesized di-ammonium ligand with rigid π-conjugated rings and additional methyl groups to construct Dion–Jacobson (DJ) structure. Augmented coordination from the extra ammonium site and increased effective bulkiness from methyl groups lead to better distribution control over conventional mono-ammonium ligands. This enhances the radiative recombination of blue emissions in the film with homogeneous energy landscape and improved surface morphology, as evidenced by a series of imaging and mapping techniques. As a result, it demonstrates DJ perovskite LEDs (PeLEDs) with peak external quantum efficiencies of ≈4% at 484 nm and ≈11% at 494 nm, which are among the top reported for pure DJ phase-based PeLEDs in the corresponding wavelength regions. The results deepen the understanding of regulating energetic disorders in perovskite materials via molecular engineering.

This study presents an approach for robust current and power control for a three‐phase grid‐connected inverter set up with an L‐filter that operates under an unbalanced AC grid‐voltage source. This control method consists of two paralleled current control for the positive and negative sequences to accomplish one of three selective control targets: a) supplying balanced three‐phase current; b) supplying non‐oscillated real power; and c) supplying non‐oscillated imaginary power to the AC grid for a given reference value utilizing the identical control gains. The real and imaginary power references, together with the measured grid voltages, are used in the computation of the reference current for each control target. In addition, the proposed dual‐current control system has a control law that comprises state feedback to offer stability and an integral effect to get rid of the offset error in the dq‐frame. To reduce settling time under uncertain system conditions, an optimization problem based on linear matrix inequalities is solved to determine a set of robust stabilizing gains. Simulation and experimental results using a TMS320F28377D digital signal processor validate the proposed control performance under three control targets. [ABSTRACT FROM AUTHOR]

In the process of tension wire construction of transmission lines, the key state quantities such as tension, inclination and spatial position of the traction walking plate directly affect the construction safety. At present, the construction personnel use visual observation to obtain the state quantity of traction walking plate in the process of tension wire construction. This monitoring method is not only inefficient, and there are personal subjective factors of judgment errors. For this reason, this paper develops a kind of intelligent traction walking plate for tension wire construction, based on the principle of resistance strain type and gyroscope to obtain the tension and inclination of the traction walking plate, respectively, using two front cameras and two rear cameras to obtain the spatial position of the traction walking plate, and finally completing the real‐time transmission of the monitoring data through the Lora technology. The developed intelligent traction walking plate was applied in Shandong Heze Yongfeng 220 kV transmission line project on 11 October 2020, which improved the construction efficiency by 15.71% while ensuring the construction safety. [ABSTRACT FROM AUTHOR]

Inverse design is a powerful tool in wave physics for compact, high-performance devices. To date, applications in photonics have mostly been limited to linear systems and it has rarely been investigated or demonstrated in the nonlinear regime. In addition, the “black box” nature of inverse design techniques has hindered the understanding of optimized inverse-designed structures. We propose an inverse design method with interpretable results to enhance the efficiency of on-chip photon generation rate through nonlinear processes by controlling the effective phase-matching conditions. We fabricate and characterize a compact, inverse-designed device using a silicon-on-insulator platform that allows a spontaneous four-wave mixing process to generate photon pairs at a rate of 1.1 MHz with a coincidence to accidental ratio of 162. Our design method accounts for fabrication constraints and can be used for scalable quantum light sources in large-scale communication and computing applications.

Dynamic multiple light scattering (DMLS) has found numerous applications, including soft matter physics and biomedical optics. Yet biological tissues may have complex internal geometries, presenting a challenge for noninvasive measurements. Deciphering laminar dynamics is crucial to accurately interpret tissue or organ physiology. Seminal DMLS work noted that one can probe deeper layers indirectly by analyzing light fluctuations on shorter time scales. Recent technologies have enabled probing deeper layers directly by analyzing fluctuations at longer path lengths. The following question arises: are the indirect and direct approaches synergistic or redundant? Here, by adding an optical switch to path-length-filtered interferometric diffusing wave spectroscopy, we experimentally address this question in the context of a forearm occlusion study. We find that both approaches afford better distinction of light scattering dynamics in layered tissues than either approach alone. This motivates further development of methods that integrate both decorrelation time scale and light path length to probe layered tissues.

The ability to achieve highly resistive beta-phase gallium oxide (β-Ga2O3) layers and substrates is critical for β-Ga2O3 high voltage and RF devices. To date, the most common approach involves doping with iron (Fe), which generates a moderately deep acceptor-like defect state located at EC-0.8 eV in the β-Ga2O3 bandgap. Recently, there has been growing interest in alternative acceptors, such as magnesium (Mg) and nitrogen (N), due to their predicted deeper energy levels, which could avoid inadvertent charge modulation during device operation. In this work, a systematic study that makes direct correlations between the introduction of N using ion implantation and the observation of a newly observed deep level at EC-2.9 eV detected by deep-level optical spectroscopy (DLOS) is presented. The concentration of this state displayed a monotonic dependence with N concentration over a range of implant conditions, as confirmed by secondary ion mass spectrometry (SIMS). With a near 1:1 match in absolute N and EC-2.9 eV trap concentrations from SIMS and DLOS, respectively, which also matched the measured removal of free electrons from capacitance-voltage studies, this indicates that N contributes a very efficiently incorporated compensating defect. Density functional theory calculations confirm the assignment of this state to be an N (0/−1) acceptor with a configuration of N occupying the oxygen site III [NO(III)]. The near ideal efficiency for this state to compensate free electrons and its location toward the midgap region of the β-Ga2O3 bandgap demonstrates the potential of N doping as a promising approach for producing semi-insulating β-Ga2O3.

In response to the Covid-19 crisis, 186 countries implemented direct cash transfers to households, and 181 introduced in-kind programs that lowered the cost of utilities such as electricity, water, transport, and mobile money. During times of crisis, do people prefer in-kind transfers or cash, and why? In this paper, we compare electricity transfers against a benchmark of cash transfers (mobile money) among 2000 rural and urban residents of Kenya with pre-paid electricity meter connections. We offer participants an incentivized choice between electricity transfers or mobile money, totaling approximately USD 10 to 15, and then implement their choice over three months. We generate three main findings. First, participants overwhelmingly prefer cash, with three-quarters of participants opting for mobile money even when offered electricity tokens with a cash value that is 40 percent higher, possibly due to the flexibility in expenditures or credit constraints. Second, despite relatively low baseline electricity consumption, preference for cash is slightly lower in rural areas, possibly due to higher transaction costs for purchasing electricity, lower mobile money penetration, or savings constraints. Third, electricity tokens transfers generate a larger increase in electricity consumption than equivalent cash transfers, suggesting a role for mental accounting; however, we estimate no impact of either electricity or cash transfers on a broad set of socioeconomic outcomes. These patterns suggest that mobile money transfers generate larger welfare gains than electricity credit, at least in settings with high mobile money penetration.

Correction to: Nature Energy. Published online 25 May 2023. This paper was originally published under a standard Springer Nature license (© The Author(s), under exclusive licence to Springer Nature Limited). It is now available as an open-access paper under a Creative Commons Attribution 4.0 International license, © The Author(s). The error has been corrected in the online version of the article.

Individual demand for emerging technologies can be influenced by the demand of other individuals within defined peer groups. These so-called peer effects have been demonstrated in emerging clean energy technologies such as rooftop solar. To date, peer effects have disproportionately driven solar adoption among relatively affluent households. Here, we use household-level income estimates of rooftop solar adopters to explore how peer effects drive adoption for low-income households. We find evidence of peer effects for both high- and low-income households and find that peer effects are generally stronger within than across income groups. Our results indicate that peer effects translate to adoption less frequently among low-income households. These results suggest that low-income peer effects are mitigated by barriers to low-income adoption. Heterogeneous peer influence is another demand shifter that explains the inequitable adoption of emerging technologies.