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ObjectiveDevelop a multi-functional imaging system that combines 1.7μm optical coherence tomography/angiography (OCT/OCTA) to accurately interrogate Hereditary Hemorrhagic Telangiectasia (HHT) skin lesions.MethodsThe study involved imaging HHT skin lesions on five subjects including lips, hands, and chest. We assessed the attributes of both HHT lesions and the healthy vasculature around them in these individuals, employing quantifiable measures such as vascular density and diameter. Additionally, we performed scans on an HHT patient who had undergone anti-angiogenic therapy, allowing us to observe changes in vasculature before and after treatment.ResultsThe results from this pilot study demonstrate the feasibility of evaluating the HHT lesion using this novel methodology and suggest the potential of OCTA to noninvasively track HHT lesions over time. The average percentage change in density between HHT patients' lesions and control was 37%. The percentage increase in vessel diameter between lesion and control vessels in HHT patients was 23.21%.ConclusionIn this study, we demonstrated that OCTA, as a functional extension of OCT, can non-invasively scan HHT lesions in vivo. We scanned five subjects with HHT lesions in various areas (lip, ear, finger, and palm) and quantified vascular density and diameter in both the lesions and adjacent healthy tissue. This non-invasive method will permit a more comprehensive examination of HHT lesions.SignificanceThis method of non-invasive imaging could offer new insights into the physiology, management, and therapeutics of HHT-associated lesion development and bleeding.

HfO2– and ZrO2–based ferroelectric thin films have emerged as promising candidates for the gate oxides of next-generation electronic devices. Recent work has experimentally demonstrated that a tetragonal/orthorhombic (t/o-) phase mixture with partially in-plane polarization can lead to negative capacitance (NC) stabilization. However, there is a discrepancy between experiments and the theoretical understanding of domain formation and domain wall motion in these multi-phase, polycrystalline materials. Furthermore, the effect of anisotropic domain wall coupling on NC has not been studied so far. Here, 3D phase field simulations of HfO2– and ZrO2–based mixed-phase ultra-thin films on silicon are applied to understand the necessary and beneficial conditions for NC stabilization. It is found that smaller ferroelectric grains and a larger angle of the polar axis with respect to the out-of-plane direction enhances the NC effect. Furthermore, it is shown that theoretically predicted negative domain wall coupling even along only one axis prevents NC stabilization. Therefore, it is concluded that topological domain walls play a critical role in experimentally observed NC phenomena in HfO2– and ZrO2–based ferroelectrics.

Examining coupled renewable-battery power plants (“hybrids”) in congested areas provides insights into a future of increased wind and solar penetration. Our study focuses on two types of congested regions, Variable Renewable Energy (VRE)-rich Areas and Load Centers, and explores likely plant configuration choices for developers and transmission network planners. This paper examines how hybrid value, comprising energy and capacity value, varies by plant configuration and congested region type considering factors such as storage duration, battery degradation, and ability to charge from the grid. We select plant locations from across the seven main U.S. independent system operators (ISOs). Hybrid value for each configuration is computed based on profit-maximizing plant operation given perfect foresight, according to observed wholesale power market real time prices from 2018 to 2021. In VRE-rich Areas, the median increase in energy value from extending storage duration from one to 4 h is 29.4 % for solar and 26.8 % for wind, assuming low battery degradation costs and storage sized to 100 % of the plant's nameplate generation capacity. Increasing storage duration beyond 4 h does not substantially increase its value from energy markets, even in VRE-rich Areas. We find that solar hybrids reach a 90 % capacity credit with 4 h of storage, while wind hybrids require 8 h of storage, based on the capacity factor of each hybrid during the top 100 net load hours.

Efficiently shaping femtosecond, transverse Gaussian laser beams to flat-top beams with flat wavefronts is critical for large-scale material processing and manufacturing. Existing beam shaping devices fall short either in final beam homogeneity or efficiency. We present an approach that uses refractive optics to perform the majority of the beam shaping and then uses a fine-tune device (spatial light modulator) to refine the intensity profile. For the beam that we selected, circularly asymmetric with intensity fluctuations, our method achieved a uniformity of 0.055 within 90% of the beam area at 92% efficiency. The optimization involved an iterative beam shaping process that converged to optimum within 10 iterations.

Photo-sono therapy (PST) is an innovative anti-vascular approach based on cavitation-induced spallation. Currently, passive cavitation detection (PCD) is the prevalent technique for cavitation monitoring during treatment. However, the limitations of PCD are the lack of spatial information of bubbles and the difficulty of integration with the PST system. To address this, we proposed a new, to the best of our knowledge, cavitation mapping method that integrates Doppler optical coherence tomography (OCT) with PST to visualize bubble dynamics in real time. The feasibility of the proposed system has been confirmed through experiments on vascular-mimicking phantoms and in vivo rabbit ear vessels, and the results are compared to high-speed camera observations and PCD data. The findings demonstrate that Doppler OCT effectively maps cavitation in real time and holds promise for guiding PST treatments and other cavitation-related clinical applications.

Solid phase epitaxy (SPE) has been widely employed for various thin-film materials, making it valuable for industrial applications due to its scalability. In complex oxides, SPE has been limited to a few materials because of the challenges in maintaining stoichiometric control during growth, particularly when volatile phases are present at high temperatures. Here, we investigate the impact of encapsulation layers on the SPE of complex oxides, using SrRuO3 (SRO) as a model system. An amorphous SRO layer was deposited on a SrTiO3 (STO) substrate, followed by the transfer of a single-crystalline STO membrane as an encapsulation layer in order to suppress the evaporation of volatile species (RuO2) during the SPE process. Whereas both encapsulated and unencapsulated SRO layers were successfully crystallized, the unencapsulated films suffered a substantial loss of Ru ions—exceeding 20%—compared to their encapsulated counterparts. This loss of Ru ions led to a loss of metallicity in the unencapsulated SRO layers, whereas the encapsulated layers retained their metallic ferromagnetic properties. This study demonstrates that the encapsulation provided by oxide membranes effectively suppresses stoichiometric loss during SPE, presenting a new strategy in stabilizing a broader class of functional oxides as epitaxial thin films.

Abstract: As a promising candidate for nonvolatile memory devices, the hafnia‐based ferroelectric system has recently been a hot research topic. Although significant progress has been made over the past decade, the endurance problem is still an obstacle to its final application. In perovskite‐based ferroelectrics, such as the well‐studied Pb[ZrxTi1−x]O3 (PZT) family, polarization fatigue has been discussed within the framework of the interaction of charged defects (such as oxygen vacancies) with the moving domains during the switching process, particularly at the electrode‐ferroelectric interface. Armed with this background, a hypothesis is set out to test that a similar mechanism can be in play with the hafnia‐based ferroelectrics. The conducting perovskite La‐Sr‐Mn‐O is used as the contact electrode to create La0.67Sr0.33MnO3 / Hf0.5Zr0.5O2 (HZO)/ La0.67Sr0.33MnO3 capacitor structures deposited on SrTiO3‐Si substrates. Nanoscale X‐ray diffraction is performed on single capacitors, and a structural phase transition from polar o‐phase toward non‐polar m‐phase is demonstrated during the bipolar switching process. The energy landscape of multiphase HZO has been calculated at varying oxygen vacancy concentrations. Based on both theoretical and experimental results, it is found that a polar to non‐polar phase transformation caused by oxygen vacancy redistribution during electric cycling is a likely explanation for fatigue in HZO.

Anode-free batteries possess the optimal cell architecture due to their reduced weight, volume and cost. However, their implementation has been limited by unstable anode morphological changes and anode–liquid electrolyte interface reactions. Here we show that an electrochemically stable solid electrolyte and the application of stack pressure can solve these issues by enabling the deposition of dense sodium metal. Furthermore, an aluminium current collector is found to achieve intimate solid–solid contact with the solid electrolyte, which allows highly reversible sodium plating and stripping at both high areal capacities and current densities, previously unobtainable with conventional aluminium foil. A sodium anode-free all-solid-state battery full cell is demonstrated with stable cycling for several hundred cycles. This cell architecture serves as a future direction for other battery chemistries to enable low-cost, high-energy-density and fast-charging batteries.

Non-fused ring electron acceptors (NFREAs) potentially have lower synthetic costs than their fused counterparts. However, the low backbone planarity and the presence of bulky substituents adversely affect the crystallinity of NFREAs, impeding charge transport and the formation of bicontinuous morphology in organic solar cells. Here we show that a binary solvent system can individually control the crystallization and phase separation of the donor polymer (for example, D18) and the NFREA (for example, 2BTh-2F-C2). We select solvents such as chloroform and o-xylene that evaporate at different temperatures and rates and have different solubility for D18. Upon evaporation of chloroform, D18 starts to assemble into fibrils. Then, the evaporation of o-xylene induces the rapid formation of a fibril network that phase segregates 2BTh-2F-C2 into pure domains and leads to a bicontinuous morphology. The well-defined interpenetrating network morphology affords an efficiency of 19.02% on small-area cells and 17.28% on 1 cm2 devices.

The ptychographic iterative engine (PIE) is a widely used algorithm that enables phase retrieval at nanometer-scale resolution over a wide range of imaging experiment configurations. By analyzing diffraction intensities from multiple scanning locations where a probing wavefield interacts with a sample, the algorithm solves a difficult optimization problem with constraints derived from the experimental geometry as well as sample properties. The effectiveness at which this optimization problem is solved is highly dependent on the ordering in which we use the measured diffraction intensities in the algorithm, and random ordering is widely used due to the limited ability to escape from stagnation in poor-quality local solutions. In this study, we introduce an extension to the PIE algorithm that uses ideas popularized in recent machine learning training methods, in this case minibatch stochastic gradient descent. Our results demonstrate that these new techniques significantly improve the convergence properties of the PIE numerical optimization problem.

It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.

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.

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.)

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 an ultrafast nonlinear optical interaction, the electric field of the emitted nonlinear signal provides direct access to the induced nonlinear transient polarization or transient currents and thus carries signatures of ultrafast dynamics in a medium. Measurement of the electric field of such signals offers sensitive observables to track ultrafast electron dynamics in various systems. In this work, we resolve the real-time phase of the electric field of a femtosecond third-order nonlinear optical signal in the molecular frame. The electric field emitted from impulsively pre-aligned gas-phase molecules at room temperature, in a degenerate four-wave mixing scheme, is measured using a spectral interferometry technique. The nonlinear signal is measured around a rotational revival to extract its molecular-frame angle dependence from pump-probe time-delay scans. By comparing these measurements for two linear molecules, carbon dioxide and nitrogen, we show that the measured second-order phase parameter (temporal chirp) of the signal is sensitive to the valence electronic symmetry of the molecules, whereas the amplitude of the signal does not show such sensitivity. We compare measurements to theoretical calculations of the chirp observable in the molecular frame. This work is an important step towards using electric field measurements in nonlinear optical spectroscopy to study ultrafast dynamics of electronically excited molecules in the molecular frame.

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.

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).

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.

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.

To enable health monitoring and fault diagnosis of PV modules using current-voltage characteristics (I–V curves), it is generally necessary to correct the I–V curves measured under different environmental conditions to the standard condition. The most common correction methods are those from IEC 60891: 2021 standard. However, these methods can introduce significant errors when dealing with degraded PV modules due to the inability to account for changes in resistance. To address this, we propose an improved I–V curve procedure, denoted Pdynamic, which considers different types of degradation by dynamically deriving the correction coefficients from the measured I–V curves. To evaluate the performance, we simulate I–V curves across a wide range of irradiance and temperature for the healthy and degraded module, where the degradation involves increased series resistance, decreased shunt resistance, or both. The results reveal that Pdynamic can produce corrected I–V curves closer to the reference ones than Procedures 1, 2, and 4 of the IEC 60891:2021 standard. Moreover, Pdynamic exhibits resilience to both seasonal fluctuations and varying levels of degradation. These results highlight Pdynamic as a promising and robust I–V curve correction method, particularly for degraded PV modules. A Python-based open-source tool for this procedure is also available at https://github.com/DuraMAT/IVcorrection.

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.

Artificial spin-ice systems are patterned arrays of magnetic nanoislands arranged into frustrated geometries and provide insight into the physics of ordering and emergence. The majority of these systems have been realized in two-dimensions, mainly due to the ease of fabrication, but with recent developments in advanced nanolithography, three-dimensional artificial spin ice (ASI) structures have become possible, providing a new paradigm in their study. Such artificially engineered 3D systems provide new opportunities in realizing tunable ground states, new domain wall topologies, monopole propagation, and advanced device concepts, such as magnetic racetrack memory. Direct imaging of 3DASI structures with magnetic force microscopy has thus far been key to probing the physics of these systems but is limited in both the depth of measurement and resolution, ultimately restricting measurement to the uppermost layers of the system. In this work, a method is developed to fabricate 3DASI lattices over an aperture using two-photon lithography, thermal evaporation, and oxygen plasma exposure, allowing the probe of element-specific structural and magnetic information using soft x-ray microscopy with x-ray magnetic circular dichroism (XMCD) as magnetic contrast. The suspended polymer-permalloy lattices are found to be stable under repeated soft x-ray exposure. Analysis of the x-ray absorption signal allows the complex cross section of the magnetic nanowires to be reconstructed and demonstrates a crescent-shaped geometry. Measurement of the XMCD images after the application of an in-plane field suggests a decrease in magnetic moment on the lattice surface due to oxidation, while a measurable signal is retained on sub-lattices below the surface.

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.

Polaritons, i.e., hybrid quasi-particles of light and matter resonances, have been extensively investigated due to their potential to enhance light-matter interactions. Although polaritonic applications thrive in the mid-infrared range, their extension to the terahertz (THz) range remains limited. Here, we present paratellurite (α-TeO2) nanowires, a versatile material acting as a platform for different types of phonon polaritons. Utilizing synchrotron infrared nanospectroscopy from 10 to 24 THz, we uncover the polaritonic properties of α-TeO2 nanowires, showcasing their dual functionality as both a Fabry-Pérot cavity and a waveguide for surface phonon polaritons. Furthermore, near-field measurements with a free-electron laser as a THz source reveal a localized optical contrast down to 5.5 THz, an indication of hyperbolic bands. Our findings complement the repertoire of polaritonic materials, with significant implications for advancing THz technologies.

Co- and Ni-free disordered rocksalt cathodes utilize oxygen redox to increase the energy density of lithium-ion batteries, but it is challenging to achieve good cycle life at high voltages >4.5 V (versus Li/Li+). Here we report a family of Li-excess Mn-rich cathodes that integrates rocksalt- and polyanion-type structures. Following design rules for cation filling and ordering, we demonstrate the bulk incorporation of polyanion groups into the rocksalt lattice. This integration bridges the two primary families of lithium-ion battery cathodes—layered/spinel and phosphate oxides—dramatically enhancing the cycling stability of disordered rocksalt cathodes with 4.8 V upper cut-off voltage. The cathode exhibits high gravimetric energy densities above 1,100 Wh kg−1 and >70% retention over 100 cycles. This study opens up a broad compositional space for developing battery cathodes using earth-abundant elements such as Mn and Fe.

The ability to discern the content of the view through a window is referred to as view clarity. It is often overlooked in the design process, and the methods of shading daylight can affect window views. We conducted a narrative review of building standards and the scientific literature to better understand how shades can be designed so as to retain the window view. View clarity was characterised by three main dimensions: (1) the shading solution, (2) the view content and (3) the observer. Each dimension and the interactions between them influence view clarity. These interactions make it difficult to predict view clarity for all the situations that can occur in buildings. Nonetheless, we highlighted the effects of different shades on the view clarity. Our insights can help designers consider these impacts within the context of overall window design.

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.

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.

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.

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.