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At least 757 records · Page 42

Using SWMM for emergency response planning: A case study evaluating biological agent transport under various rainfall scenarios and urban surfaces

To assist in emergency preparedness for a biological agent terrorist attack or accidental pathogen release, potential contaminant levels and migration pathways of spores spread by urban stormwater were evaluated using a Storm Water Management Model (SWMM) of U.S. Coast Guard Base Elizabeth City, North Carolina. The high temporal-spatial resolution SWMM model was built using spore concentrations in stormwater runoff from asphalt, grass, and concrete collected from a point-scale field study. The subsequent modeled contamination scenarios included a notional plume release and point releases mimicking the field study under three rainfall conditions. The rainfall scenarios included a 6-hour natural rainfall event on Dec. 8, 2021 and two design storms (2-year and 100-year events). The observed spore concentrations from asphalt and concrete from the actual field experiment were applied to calibrate the washoff parameters in the SWMM model, using an exponential washoff function. The calibrated washoff coefficient (c 1 ) and exponent (c 2 ) were 0.01 and 1.00 for asphalt, 0.05 and 1.45 for grass, and 2.45 and 1.00 for concrete, respectively. The calibrated SWMM model simulated spore concentrations in runoff at times and magnitudes similar to the field study data. In the point release modeled scenario, the concrete surface generated 55.6% higher average spore concentrations than asphalt. Similarly, in the field experiment, a 175% (p < 0.05) higher average spore concentration in surface runoff was observed from concrete than from asphalt. Here, this study demonstrates how SWMM may be used to evaluate spore washoff from urban surfaces under different precipitation amounts, intensities, and durations, and how visualized spatial migration pathways in stormwater runoff may be used for emergency planning and remediation.

54 ENVIRONMENTAL SCIENCES↗

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Oil-Pressure Based Apparatus for In-Situ High-Energy Synchrotron X-Ray Diffraction Studies During Biaxial Deformation

Background: Understanding biaxial loading response at the microstructural level is crucial in helping better design sheet manufacturing processes and calibrate/validate material deformation models. Objective: The objective of this work was to develop a low-cost testing apparatus to probe, with sufficient spatial resolution, the micro-mechanical response of a sheet material in-situ under biaxial loading conditions. Methods: The testing apparatus fabricated as a part of this study operates in a similar fashion to a standard bulge test and uses oil pressure to generate biaxial loading conditions. This biaxial testing apparatus was operated within a synchrotron beamline to characterize the mechanical response of a flash-processed steel sheet using in-situ high-energy X-ray diffraction (XRD) measurements. Further, the GSAS-II package was utilized to develop a workflow for the analysis of the large volume of diffraction data acquired. The workflow was then used to extract the peak position, width, and integrated intensity of the XRD peaks corresponding to the major body-centered cubic phase. Results: The equi-biaxial nature of the loading in the measured area was independently corroborated using experimental (XRD) and simulation (finite element analysis) methods. Furthermore, we discuss the evolution of elastic strain in the major body-centered cubic phase as a function of applied oil pressure and location on the steel sheet. Conclusions: A key advantage of the biaxial apparatus fabricated in this synchrotron study is demonstrated using the results obtained for the flash-processed steel sheet – i.e., mapping the lattice plane-dependent response to biaxial loading for a relatively large sample area in a spatially resolved manner.

36 MATERIALS SCIENCE↗

Spot size measurement of a deuterium–tritium dense plasma focus using neutron radiography

Neutron radiography is a technique uniquely suited to applications in nuclear diagnostics, non-destructive testing, and subcritical experiments. The spatial resolution of neutron radiographs is degraded by optical blur in the imaging system and the neutron source size, where the ideal source is point-like to optimize the point-spread function. A potential neutron source for radiography is the dense plasma focus (DPF), a coaxial Z-pinch that produces thermonuclear and beam-target neutrons. To assess if the source size is suitable for radiography, a neutron imaging system was used to measure the source size of the 4 MA Sodium DPF at the Nevada National Security Site operating with deuterium–tritium gas-fill. The source size was measured using the edge-spread function of tungsten objects, each having a rolled (convex) edge. The spot size was found to be 7–12 mm full-width at half-max (FWHM) assuming a Gaussian source, though comparison is presented for Lorentzian and Bennett distributions. The average FWHM was found to be 8.6 ± 1.2 mm vertically and 10.8 ± 1.2 mm horizontally with respect to the image plane, averaging over varied edges and alignments. The results were sensitive to source alignment and edge metrology, which introduced notable uncertainties. These results are consistent with separate experimental measurements as well as magnetohydrodynamics simulations of this DPF, which suggest that neutron production can originate from pinches ∼5–7 mm off-axis. These results suggest that the DPF should be used for radiography at low magnification (M < 1) where spot size does not dominate spatial blur.

47 OTHER INSTRUMENTATION↗

Observation of [VCu1–Ini2+VCu1–] Defect Triplets in Cu-Deficient CuInS2

Copper indium disulfide (CuInS2) is a semiconductor with a direct energy band gap of 1.53 eV, an optimal value for highly efficient thin-film solar cells. But it has reached only ~ 11 % power conversion efficiency, far less than the theoretically achievable value of ~ 30 %. The cause of this low performance is not understood. A single crystal grown from 1 mol% Cu-deficient melt was studied, using atomic resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) and electron dispersive spectroscopy (EDS). While the bulk crystal is exactly stoichiometric CuInS2, it contains nanometer-thick, structurally coherent, Cu-deficient interphases that form along rotational twin boundaries in the {112} plane. Transition zones from bulk crystal to interphase are observed, where In is seen to move from its normal site InIn in the chalcopyrite structure to a tetrahedral interstitial site Ini, while Cu remains in its normal CuCu position. Two InIn rows of the bulk crystal merge into one row of Ini, causing excess Ini in the interphase. The concentrations of CuCu and Ini reflect a ratio of Cu vacancies, VCu, to excess Ini of ~ 2. Their relative lattice positions, and the high electrical resistivity of the crystal, suggests that VCu and excess Ini ‘precipitate’ as self-compensating, electrically neutral, [VCu1- Ini2+ VCu1-] defect triplets. This is the first atomic-level observation of the ordered defect that has been invoked as the basic structural modifier in chalcopyrite compound homologs. The interphases introduce an optical gap of 1.47 eV. Electron trapping in band tail states, evident from a photoconductivity exponent of 0.54, is the likely cause of an unusually low electron mobility of 0.1 cm2V-1s-1. The overall result is that making CuInS2 slightly copper-poor inserts nanometer-thick layers of the interphase into the bulk crystal. This study shows that apparently conflicting results of the effect of Cu deficiency on CuInS2 thin-film solar cells may be resolved by analyzing structure and composition at nanometer spatial resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accounting for Training Data Error in Machine Learning Applied to Earth Observations

Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system dynamics and create continuous and categorical maps of biophysical properties and land cover, especially based on recent advances in machine learning (ML). ML models typically require large, spatially explicit training datasets to make accurate predictions. Training data (TD) are typically generated by digitizing polygons on high spatial-resolution imagery, by collecting in situ data, or by using pre-existing datasets. TD are often assumed to accurately represent the truth, but in practice almost always have error, stemming from (1) sample design, and (2) sample collection errors. The latter is particularly relevant for image-interpreted TD, an increasingly commonly used method due to its practicality and the increasing training sample size requirements of modern ML algorithms. TD errors can cause substantial errors in the maps created using ML algorithms, which may impact map use and interpretation. Despite these potential errors and their real-world consequences for map-based decisions, TD error is often not accounted for or reported in EO research. Here we review the current practices for collecting and handling TD. We identify the sources of TD error, and illustrate their impacts using several case studies representing different EO applications (infrastructure mapping, global surface flux estimates, and agricultural monitoring), and provide guidelines for minimizing and accounting for TD errors. To harmonize terminology, we distinguish TD from three other classes of data that should be used to create and assess ML models: training reference data, used to assess the quality of TD during data generation; validation data, used to iteratively improve models; and map reference data, used only for final accuracy assessment. We focus primarily on TD, but our advice is generally applicable to all four classes, and we ground our review in established best practices for map accuracy assessment literature. EO researchers should start by determining the tolerable levels of map error and appropriate error metrics. Next, TD error should be minimized during sample design by choosing a representative spatio-temporal collection strategy, by using spatially and temporally relevant imagery and ancillary data sources during TD creation, and by selecting a set of legend definitions supported by the data. Furthermore, TD error can be minimized during the collection of individual samples by using consensus-based collection strategies, by directly comparing interpreted training observations against expert-generated training reference data to derive TD error metrics, and by providing image interpreters with thorough application-specific training. We strongly advise that TD error is incorporated in model outputs, either directly in bias and variance estimates or, at a minimum, by documenting the sources and implications of error. TD should be fully documented and made available via an open TD repository, allowing others to replicate and assess its use. To guide researchers in this process, we propose three tiers of TD error accounting standards. Finally, we advise researchers to clearly communicate the magnitude and impacts of TD error on map outputs, with specific consideration given to the likely map audience.

58 GEOSCIENCES↗

Metal Halide Scintillators with Fast and Self‐Absorption‐Free Defect‐Bound Excitonic Radioluminescence for Dynamic X‐Ray Imaging

Abstract Scintillators for radiation detection are of great significance in medical imaging, security, and nondestructive inspection. The current challenge for scintillators is to simultaneously achieve high scintillation light yield, fast radioluminescence, simple film fabrication, large X‐ray attenuation efficiency as well as stable and nontoxic compositions; no previous scintillators fulfill all the above requirements. Here, metal halide Rb 2 AgBr 3 , possessing defect‐bound excitonic radioluminescence, is shown as efficient and fast scintillators. This nontoxic and stable scintillator emits from excitons bound to neutral bromine vacancies, enjoying an efficient and spin‐allowed fast emission with minimized self‐absorption. Rb 2 AgBr 3 thus has a high light yield (25 600 photons MeV −1 ), fast scintillation decay time (5.31 ns), and a record value of light yield versus decay time (4821 photons MeV −1 ns −1 ). The close‐space sublimation method is developed for fast and scalable fabrication of oriented Rb 2 AgBr 3 films. The scintillator film is further integrated with commercial flat‐panel imagers, and the spatial resolution reaches 10.2 line pairs per millimeter at the modulation transfer function of 0.2, doubling the resolution of conventional CsI:Tl flat‐panel detectors. The dynamic X‐ray imaging and its use to real‐time monitoring of bone movement without ghosting effect is also demonstrated.

Zhang, Muyi↗

In Situ Observation of Domain Wall Lateral Creeping in a Ferroelectric Capacitor

As a promising candidate for next-generation nonvolatile memory devices, ferroelectric oxide films exhibit many emergent phenomena with functional applications, making understanding polarization switching and domain evolution behaviors of fundamental importance. However, tracking domain wall motion in ferroelectric oxide films with high spatial resolution remains challenging. Here, in this study, an in situ biasing approach for direct atomic-scale observations of domain nucleation and sideways motion is presented. By accurately controlling the applied electric field, the lateral translational speed of the domain wall can decrease to less than 2.2 Å s −1 , which is observable with atomic resolution STEM imaging. In situ observations on a capacitor structured PbZr 0.1 Ti 0.9 O 3 /La 0.7 Sr 0.3 MnO 3 heterojunction demonstrate the unique creeping behavior of a domain wall under a critical electric field, with the atomic structure of the creeping domain wall revealed. Moreover, the evolution of the metastable domain wall forms an elongated morphology, which contains a large proportion of charged segments. Phase-field simulations unveil the competition between gradient, elastic, and electrostatic energies that decide this unique domain wall creeping and morphology variation. This work paves the way toward a complete fundamental understanding of domain wall physics and potential modulations of domain wall properties in real devices.

36 MATERIALS SCIENCE↗

Detection and Signal Processing for Near-Field Nanoscale Fourier Transform Infrared Spectroscopy

Researchers from a broad spectrum of scientific and engineering disciplines are increasingly using scattering-type near-field infrared spectroscopic techniques to characterize materials non-destructively with nanoscale spatial resolution. However, a sub-optimal understanding of a technique's implementation can complicate data interpretation and act as a barrier to entering the field. Here the key detection and processing steps involved in producing scattering-type near-field nanoscale Fourier transform infrared spectra (nano-FTIR) are outlined. The self-contained mathematical and experimental work derives and explains: i) how normalized complex-valued nano-FTIR spectra are generated, ii) why the real and imaginary components of spectra qualitatively relate to dispersion and absorption respectively, iii) a new and generally valid equation for spectra which can be used as a springboard for additional modeling of the scattering processes, and iv) an algebraic expression that can be used to extract an approximation to the sample's local extinction coefficient from nano-FTIR. The algebraic model for weak oscillators is validated with nano-FTIR and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra on samples of polystyrene and Kapton and further provides a pedagogical pathway to cementing some of the technique's key qualitative attributes.

36 MATERIALS SCIENCE↗

Probing the Nanoscale Excitonic Landscape and Confinement of Excitons in Gated Monolayer Semiconductors

Engineering and probing excitonic properties at the nanoscale remains a central challenge in quantum photonics and optoelectronics. While exciton confinement via electrical control and strain engineering has been demonstrated in 2D semiconductors, substantial nanoscale heterogeneity limits the scalability of 2D quantum photonic device architectures. Here, in this work, we use cathodoluminescence spectroscopy to probe the excitonic landscape of monolayer WS 2 under electrostatic gating. Exploiting the high spatial resolution of the converged electron beam, we resolve a homojunction arising between gated and ungated regions. Moreover, we reveal an exciton confinement channel arising from an unconventional doping mechanism driven by the interplay between the electron beam and the applied gate fields. These findings offer new insights into the optoelectronic behavior of monolayer semiconductors under the combined influence of electron-beam excitation and electrostatic gating. Our approach provides a pathway for exciton manipulation at the nanoscale and opens opportunities for controlling quantum-confined exciton transport in 2D materials.

2D materials↗

Cathodoluminescence of Ultrathin Twisted Ge 1–x Sn x S van der Waals Nanoribbon Waveguides

Ultrathin van der Waals semiconductors have shown extraordinary optoelectronic and photonic properties. Propagating photonic modes make layered crystal waveguides attractive for photonic circuitry and for studying hybrid light-matter states. Accessing guided modes by conventional optics is challenging due to limited spatial resolution and poor out-of-plane far field coupling. Scanning near-field optical microscopy (SNOM) can overcome these issues and can characterize waveguide modes down to tens of nm resolution, albeit for planar samples or nanostructures with moderate height variations. Electron microscopy provides atomic-scale localization also for more complex geometries, and recent advances extended the accessible excitations from interband transitions to phonons. In this work, bottom-up synthesized layered semiconductor (Ge 1-x Sn x S) nanoribbons with axial twist and deep sub-wavelength thickness are demonstrated as a platform for realizing waveguide modes, and cathodoluminescence (CL) spectroscopy is introduced as a tool to characterize them. Combined experiments and simulations show the excitation of guided modes by the electron beam and their efficient detection via photons emitted in the ribbon plane, which enables measuring key properties such as the evanescent field into the vacuum cladding with nanometer resolution. The results identify van der Waals waveguides operating in the infrared and highlight an electron microscopy-based approach for probing complex-shaped nanophotonic structures.

36 MATERIALS SCIENCE↗

Ultrathin and Ultrasensitive Direct X‐ray Detector Based on Heterojunction Phototransistors

Abstract Most contemporary X‐ray detectors adopt device structures with non/low‐gain energy conversion, such that a fairly thick X‐ray photoconductor or scintillator is required to generate sufficient X‐ray‐induced charges, and thus numerous merits for thin devices, such as mechanical flexibility and high spatial resolution, have to be compromised. This dilemma is overcome by adopting a new high‐gain device concept of a heterojunction X‐ray phototransistor. In contrast to conventional detectors, X‐ray phototransistors allow both electrical gating and photodoping for effective carrier‐density modulation, leading to high photoconductive gain and low noise. As a result, ultrahigh sensitivities of over 10 5 μC Gy air −1 cm −2 with low detection limit are achieved by just using an ≈50 nm thin photoconductor. The employment of ultrathin photoconductors also endows the detectors with superior flexibility and high imaging resolution. This concept offers great promise in realizing well‐balanced detection performance, mechanical flexibility, integration, and cost for next‐generation X‐ray detectors.

Gao, Yuanhong↗

Electro-Thermal Characterization of Dynamical VO 2 Memristors via Local Activity Modeling

We report translating the surging interest in neuromorphic electronic components, such as those based on nonlinearities near Mott transitions, into large-scale commercial deployment faces steep challenges in the current lack of means to identify and design key material parameters. These issues are exemplified by the difficulties in connecting measurable material properties to device behavior via circuit element models. Here, the principle of local activity is used to build a model of VO 2 /SiN Mott threshold switches by sequentially accounting for constraints from a minimal set of quasistatic and dynamic electrical and high-spatial-resolution thermal data obtained via in situ thermoreflectance mapping. By combining independent data sets for devices with varying dimensions, the model is distilled to measurable material properties, and device scaling laws are established. The model can accurately predict electrical and thermal conductivities and capacitances and locally active dynamics (especially persistent spiking self-oscillations). The systematic procedure by which this model is developed has been a missing link in predictively connecting neuromorphic device behavior with their underlying material properties, and should enable rapid screening of material candidates before employing expensive manufacturing processes and testing procedures.

36 MATERIALS SCIENCE↗

Aerosol‐Jet‐Printable Covalent Organic Framework Colloidal Inks and Temperature‐Sensitive Nanocomposite Films

Abstract With molecularly well‐defined and tailorable 2D structures, covalent organic frameworks (COFs) have emerged as leading material candidates for chemical sensing, storage, separation, and catalysis. In these contexts, the ability to directly and deterministically print COFs into arbitrary geometries will enable rapid optimization and deployment. However, previous attempts to print COFs have been restricted by low spatial resolution and/or post‐deposition polymerization that limits the range of compatible COFs. Here, these limitations are overcome with a pre‐synthesized, solution‐processable colloidal ink that enables aerosol jet printing of COFs with micron‐scale resolution. The ink formulation utilizes the low‐volatility solvent benzonitrile, which is critical to obtaining homogeneous printed COF film morphologies. This ink formulation is also compatible with other colloidal nanomaterials, thus facilitating the integration of COFs into printable nanocomposite films. As a proof‐of‐concept, boronate‐ester COFs are integrated with carbon nanotubes (CNTs) to form printable COF‐CNT nanocomposite films, in which the CNTs enhance charge transport and temperature sensing performance, ultimately resulting in high‐sensitivity temperature sensors that show electrical conductivity variation by 4 orders of magnitude between room temperature and 300 °C. Overall, this work establishes a flexible platform for COF additive manufacturing that will accelerate the incorporation of COFs into technologically significant applications.

2D materials↗

Silicon-Lattice-Matched Boron-Doped Gallium Phosphide: A Scalable Acousto-Optic Platform

The compact size, scalability, and strongly confined fields in integrated photonic devices enable new functionalities in photonic networking and information processing, both classical and quantum. Gallium phosphide (GaP) is a promising material for active integrated photonics due to its high refractive index, wide bandgap, strong nonlinear properties, and large acousto-optic figure of merit. Here, this study demonstrates that silicon-lattice-matched boron-doped GaP (BGaP), grown at the 12-inch wafer scale, provides similar functionalities as GaP. BGaP optical resonators exhibit intrinsic quality factors exceeding 25,000 and 200,000 at visible and telecom wavelengths, respectively. It further demonstrates the electromechanical generation of low-loss acoustic waves and an integrated acousto-optic (AO) modulator. High-resolution spatial and compositional mapping, combined with ab initio calculations, indicate two candidates for the excess optical loss in the visible band: the silicon-GaP interface and boron dimers. These results demonstrate the promise of the BGaP material platform for the development of scalable AO technologies at telecom and provide potential pathways toward higher performance at shorter wavelengths.

36 MATERIALS SCIENCE↗

A Catalyst-Like System Enables Efficient Perovskite Solar Cells

High-quality perovskite films are essential for achieving high performance of optoelectronic devices; However, solution-processed perovskite films are known to suffer from compositional and structural inhomogeneity due to lack of systematic control over the kinetics during the formation. Here, in this work, the microscopic homogeneity of perovskite films is successfully enhanced by modulating the conversion reaction kinetics using a catalyst-like system generated by a foaming agent. The chemical and structural evolution during this catalytic conversion is revealed by a multimodal synchrotron toolkit with spatial resolutions spanning many length scales. Combining these insights with computational investigations, a cyclic conversion pathway model is developed that yields exceptional perovskite homogeneity due to enhanced conversion, having a power conversion efficiency of 24.51% for photovoltaic devices. This work establishes a systematic link between processing of precursor and homogeneity of the perovskite films.

14 SOLAR ENERGY↗

Adaptive Scalpel Scanning Probe Microscopy for Enhanced Volumetric Sensing in Tomographic Analysis

Controlling nanoscale tip‐induced material removal is crucial for achieving atomic‐level precision in tomographic sensing with atomic force microscopy (AFM). While advances have enabled volumetric probing of conductive features with nanometer accuracy in solid‐state devices, materials, and photovoltaics, limitations in spatial resolution and volumetric sensitivity persist. This work identifies and addresses in‐plane and vertical tip‐sample junction leakage as sources of parasitic contrast in tomographic AFM, hindering real‐space 3D reconstructions. Novel strategies are proposed to overcome these limitations. First, the contrast mechanisms analyzing nanosized conductive features are explored when confining current collection purely to in‐plane transport, thus allowing reconstruction with a reduction in the overestimation of the lateral dimensions. Furthermore, an adaptive tip‐sample biasing scheme is demonstrated for the mitigation of a class of artefacts induced by the high electric field inside the thin oxide when volumetrically reduced. This significantly enhances vertical sensitivity by approaching the intrinsic limits set by quantum tunneling processes, allowing detailed depth analysis in thin dielectrics. The effectiveness of these methods is showcased in tomographic reconstructions of conductive filaments in valence change memory, highlighting the potential for application in nanoelectronics devices and bulk materials and unlocking new limits for tomographic AFM.

36 MATERIALS SCIENCE↗

Aerosol-Jet Printed Sensors for Environmental, Safety, and Health Monitoring: A Review

An emergent direct-write approach, aerosol-jet printing (AJP), is gaining attention for the deployment of rapid and affordable microadditively manufactured energy-efficient sensors and printed electronics. AJP enables a broad range of ink viscosities (0.001–1 Pa s) for printing diverse materials ranging from ceramics and metals to polymers and biological matter. Reproducible, high-spatial-resolution features (≈10 µm), and wide standoff distances (1–11 mm) between the nozzle and the substrate facilitate conformal printing of complex geometrical designs on nonplanar—e.g., stepped or curved—surfaces. Here this paper aims to provide a comprehensive overview of state-of-the-art AJP-based sensors (e.g., strain and temperature gauges, biosensors, photosensors, humidity and surface acoustic wave sensors, dielectric elastomer actuators, and motion, smoke, and hazardous gas detectors) and to discuss prospective applications. The drive toward cost-effective devices that are smaller, lighter, and better-performing remains a frontier challenge in the field of printed electronics. Consequently, as AJP becomes increasingly utilized in the high-volume manufacturing of miniaturized active and passive sensors, it opens a pathway for facile large-scale fabrication of devices for a wide range of consumer and industrial applications, including transportation, agriculture, infrastructure, aerospace, national defense, and healthcare.

3-dimensional↗