Antireflection microstructures on ZnSe for mid- and far-IR fabricated by femtosecond laser ablation assisted with wet chemical etching

Most infrared materials used in high-power systems, such as optical parametric generators, have high values of refractive indices, which result in high Fresnel losses. The performance of conventional antireflection coatings is limited when used in high-power and ultra-broadband systems. An alternative approach is to fabricate antireflection microstructures (ARMs) that allow for a broadband increase in transmittance without reducing the damage threshold of the material. In this work, ARMs were fabricated on the surface of ZnSe crystals using the femtosecond laser ablation assisted with wet chemical etching method. This allowed to produce high aspect ratio microstructures that increase the transmittance up to 98% in the mid- and far- infrared regions.

Flash heating process for efficient meat preservation

Maintaining food safety and quality is critical for public health and food security. Conventional food preservation methods, such as pasteurization and dehydration, often change the overall organoleptic quality of the food products. Herein, we demonstrate a method that affects only a thin surface layer of the food, using beef as a model. In this method, Joule heating is generated by applying high electric power to a carbon substrate in <1 s, which causes a transient increase of the substrate temperature to > ~2000 K. The beef surface in direct contact with the heating substrate is subjected to ultra-high temperature flash heating, leading to the formation of a microbe-inactivated, dehydrated layer of ~100 µm in thickness. Aerobic mesophilic bacteria, Enterobacteriaceae, yeast and mold on the treated samples are inactivated to a level below the detection limit and remained low during room temperature storage of 5 days. Meanwhile, the product quality, including visual appearance, texture, and nutrient level of the beef, remains mostly unchanged. In contrast, microorganisms grow rapidly on the untreated control samples, along with a rapid deterioration of the meat quality. This method might serve as a promising preservation technology for securing food safety and quality.

A filtering reconfigurable intelligent surface for interference-free wireless communications

The powerful capability of reconfigurable intelligent surfaces (RISs) in tailoring electromagnetic waves and fields has put them under the spotlight in wireless communications. However, the current designs are criticized due to their poor frequency selectivity, which hinders their applications in real-world scenarios where the spectrum is becoming increasingly congested. Here we propose a filtering RIS to feature sharp frequency-selecting and 2-bit phase-shifting properties. It permits the signals in a narrow bandwidth to transmit but rejects the out-of-band ones; meanwhile, the phase of the transmitted signals can be digitally controlled, enabling flexible manipulations of signal propagations. A prototype is designed, fabricated, and measured, and its high quality factor and phase-shifting characteristics are validated by scattering parameters and beam-steering phenomena. Further, we conduct a wireless communication experiment to illustrate the intriguing functions of the RIS. The filtering behavior enables the RIS to perform wireless signal manipulations with anti-interference ability, thus showing big potential to advance the development of next-generation wireless communications.

3D printing with a 3D printed digital material filament for programming functional gradients

Additive manufacturing, or 3D printing attracts growing attention as a promising method for creating functionally graded materials. Fused deposition modeling (FDM) is widely available, but due to its simple process, creating spatial gradation of diverse properties using FDM is challenging. Here, we present a 3D printed digital material filament that is structured towards 3D printing of functional gradients, utilizing only a readily available FDM printer and filaments. The DM filament consists of multiple base materials combined with specific concentrations and distributions, which are FDM printed. When the DM filament is supplied to the same printer, its constituent materials are homogeneously blended during extrusion, resulting in the desired properties in the final structure. This enables spatial programming of material properties in extreme variations, including mechanical strength, electrical conductivity, and color, which are otherwise impossible to achieve with traditional FDMs. Our approach can be readily adopted to any standard FDM printer, enabling low-cost production of functional gradients.

Semantic integration of diverse data in materials science: Assessing Orowan strengthening

This study applies Semantic Web technologies to advance Materials Science and Engineering (MSE) through the integration of diverse datasets. Focusing on a 2000 series age-hardenable aluminum alloy, we correlate mechanical and microstructural properties derived from tensile tests and dark-field transmission electron microscopy across varied aging times. An expandable knowledge graph, constructed using the Tensile Test and Precipitate Geometry Ontologies aligned with the PMD Core Ontology, facilitates this integration. This approach adheres to FAIR principles and enables sophisticated analysis via SPARQL queries, revealing correlations consistent with the Orowan mechanism. The study highlights the potential of semantic data integration in MSE, offering a new approach for data-centric research and enhanced analytical capabilities.

Automatic brain-tumor diagnosis using cascaded deep convolutional neural networks with symmetric U-Net and asymmetric residual-blocks

The use of various kinds of magnetic resonance imaging (MRI) techniques for examining brain tissue has increased significantly in recent years, and manual investigation of each of the resulting images can be a time-consuming task. This paper presents an automatic brain-tumor diagnosis system that uses a CNN for detection, classification, and segmentation of glioblastomas; the latter stage seeks to segment tumors inside glioma MRI images. The structure of the developed multi-unit system consists of two stages. The first stage is responsible for tumor detection and classification by categorizing brain MRI images into normal, high-grade glioma (glioblastoma), and low-grade glioma. The uniqueness of the proposed network lies in its use of different levels of features, including local and global paths. The second stage is responsible for tumor segmentation, and skip connections and residual units are used during this step. Using 1800 images extracted from the BraTS 2017 dataset, the detection and classification stage was found to achieve a maximum accuracy of 99%. The segmentation stage was then evaluated using the Dice score, specificity, and sensitivity. The results showed that the suggested deep-learning-based system ranks highest among a variety of different strategies reported in the literature.

3D printable strong and tough composite organo-hydrogels inspired by natural hierarchical composite design principles

Fabrication of composite hydrogels can effectively enhance the mechanical and functional properties of conventional hydrogels. While ceramic reinforcement is common in many hard biological tissues, ceramic-reinforced hydrogels lack a similar natural prototype for bioinspiration. This raises a key question: How can we still attain bioinspired mechanical mechanisms in composite hydrogels without mimicking a specific composition and structure? Abstracting the hierarchical composite design principles of natural materials, this study proposes a hierarchical fabrication strategy for ceramic-reinforced organo-hydrogels, featuring (1) aligned ceramic platelets through direct-ink-write printing, (2) poly(vinyl alcohol) organo-hydrogel matrix reinforced by solution substitution, and (3) silane-treated platelet-matrix interfaces. Unit filaments are further printed into a selection of bioinspired macro-architectures, leading to high stiffness, strength, and toughness (fracture energy up to 31.1 kJ/m2), achieved through synergistic multi-scale energy dissipation. The materials also exhibit wide operation tolerance and electrical conductivity for flexible electronics in mechanically demanding conditions. Hence, this study demonstrates a model strategy that extends the fundamental design principles of natural materials to fabricate composite hydrogels with synergistic mechanical and functional enhancement.

Vapor-induced phase-separation-enabled versatile direct ink writing

Versatile printing of polymers, metals, and composites always calls for simple, economic approaches. Here we present an approach to three-dimensional (3D) printing of polymeric, metallic, and composite materials at room conditions, based on the polymeric vapor-induced phase separation (VIPS) process. During VIPS 3D printing (VIPS-3DP), a dissolved polymer-based ink is deposited in an environment where nebulized non-solvent is present, inducing the low-volatility solvent to be extracted from the filament in a controllable manner due to its higher chemical affinity with the non-solvent used. The polymeric phase is hardened in situ as a result of the induced phase separation process. The low volatility of the solvent enables its reclamation after the printing process, significantly reducing its environmental footprint. We first demonstrate the use of VIPS-3DP for polymer printing, showcasing its potential in printing intricate structures. We further extend VIPS-3DP to the deposition of polymer-based metallic inks or composite powder-laden polymeric inks, which become metallic parts or composites after a thermal cycle is applied. Furthermore, spatially tunable porous structures and functionally graded parts are printed by using the printing path to set the inter-filament porosity as well as an inorganic space-holder as an intra-filament porogen.

The first absolute gravity and height reference network in Sicily

The purpose of this work is to provide the methodological and instrumental framework for the establishment of a new absolute gravity and height reference network in Sicily. The aim of the network is to contribute to the new reference systems in the Italian area, useful for the scientific and technological activities related to the gravity field and to the proper definition of a modern height system in this region. The network is composed of 5 stations, evenly distributed to form a large mesh, which roughly covers the entire Sicily. Since four of the five selected stations were measured also in the 1990s, it was also possible to evaluate whether long-term gravity changes occurred at these sites (basic requirement for a reference network) and check the long-term ground deformation patterns, using data from the closest GPS/GNSS stations. The observed gravity changes over a time interval of about 30 years at the absolute stations and in the surrounding areas, confirm the long-term stability of the selected areas/sites.

3D nanofabricated soft microrobots with super-compliant picoforce springs as onboard sensors and actuators

Microscale organisms and specialized motile cells use protein-based spring-like responsive structures to sense, grasp and move. Rendering this biomechanical transduction functionality in an artificial micromachine for applications in single-cell manipulations is challenging due to the need for a bio-applicable nanoscale spring system with a large and programmable strain response to piconewton-scale forces. Here we present three-dimensional nanofabrication and monolithic integration, based on an acrylic elastomer photoresist, of a magnetic spring system with quantifiable compliance sensitive to 0.5 pN, constructed with customized elasticity and magnetization distributions at the nanoscale. We demonstrate the effective design programmability of these 'picospring' ensembles as energy transduction mechanisms for the integrated construction of customized soft micromachines, with onboard sensing and actuation functions at the single-cell scale for microrobotic grasping and locomotion. The integration of active soft springs into three-dimensional nanofabrication offers an avenue to create biocompatible soft microrobots for non-disruptive interactions with biological entities.

3D printing by stereolithography using thermal initiators

Additive manufacturing technologies based on stereolithography rely on initiating spatial photopolymerization by using photoinitiators activated by UV-visible light. Many applications requiring printing in water are limited since water-soluble photoinitiators are scarce, and their price is skyrocketing. On the contrary, thermal initiators are widely used in the chemical industry for polymerization processes due to their low cost and simplicity of initiation by heat at low temperatures. However, such initiators were never used in 3D printing technologies, such as vat photopolymerization stereolithography, since localizing the heat at specific printing voxels is impossible. Here we propose using a thermal initiator for 3D printing for localized polymerization processes by near-infrared and visible light irradiation without conventional photoinitiators. This is enabled by using gold nanorods or silver nanoparticles at very low concentrations as photothermal converters in aqueous and non-aqueous mediums. Our proof of concept demonstrates the fabrication of hydrogel and polymeric objects using stereolithography-based 3D printers, vat photopolymerization, and two-photon printing.

The first demonstration of entirely roll-to-roll fabricated perovskite solar cell modules under ambient room conditions

The rapid development of organic-inorganic hybrid perovskite solar cells has resulted in laboratory-scale devices having power conversion efficiencies that are competitive with commercialised technologies. However, hybrid perovskite solar cells are yet to make an impact beyond the research community, with translation to large-area devices fabricated by industry-relevant manufacturing methods remaining a critical challenge. Here we report the first demonstration of hybrid perovskite solar cell modules, comprising serially-interconnected cells, produced entirely using industrial roll-to-roll printing tools under ambient room conditions. As part of this development, costly vacuum-deposited metal electrodes are replaced with printed carbon electrodes. A high-throughput experiment involving the analysis of batches of 1600 cells produced using 20 parameter combinations enabled rapid optimisation over a large parameter space. The optimised roll-to-roll fabricated hybrid perovskite solar cells show power conversion efficiencies of up to 15.5% for individual small-area cells and 11.0% for serially-interconnected cells in large-area modules. Based on the devices produced in this work, a cost of ~0.7 USD W-1 is predicted for a production rate of 1,000,000 m² per year in Australia, with potential for further significant cost reductions.

Bi-stability in femtosecond laser ablation by MHz bursts

In this work, a bi-stable behavior of laser ablation efficiency and quality was controlled by fluence and burst length. The plasma shielding of incoming laser radiation caused sudden jumps with a significant decrease in ablation efficiency for every even number of pulses in the burst. The attenuation of incoming laser radiation by plasma created by the previous pulse was incorporated into the toy model of burst ablation efficiency. The mathematical recurrence relation has been derived for the first time, binding ablation efficiency for the next pulse with the efficiency of the previous pulse, which predicts bi-stability, as well as sudden jumps occurring in ablation efficiency depending on the number of pulses in burst with the response to changes of the control parameter of peak laser fluence in the pulse. The modeling results using new recurrence relation showed stable and bi-stable ablation efficiency depending on burst fluence and the number of pulses, which agreed well with experimental data. The extremely efficient laser ablation has been achieved by optimizing the shielding effect using three pulses in the burst.

A novel portable anechoic chamber using ultra-thin 2D microwave absorber for industrial 5.0

In this paper, the authors, for the first time, have shown the use of 2D conformal microwave absorbing material (MAM) in the design and fabrication of a portable Anechoic chamber (AC). The MAM is fabricated on the transparent and conductive metal oxide layer named indium-tin-oxide (ITO) with Polyethylene terephthalate as the substrate and the ground plane for zero transmission having overall thickness of 0.012 λ where λ is calculated at 0.7 GHz. The MAM is characterized for 0.7 to 18 GHz for both TE- and TM-polarisation and oblique incidence. High sheet resistance, dipole-like resonance structure patterned on the ITO, and the air-spacing between the layers is optimized to achieve broadband absorption. The MAM is used to line the six sides of the rectangular anechoic chamber having inner dimensions of: (L × W × H: 850 × 650 × 720 mm3). The return loss (RL), gain, and radiation pattern of three antenna working at 1.56, 2.43, and 4.93 GHz are analyzed inside the AC. The measurement results for all frequencies very well match with the simulation studies, thus validating and opening the door for the future use of ultra-thin and planar MAM in the AC.

Revealing process and material parameter effects on densification via phase-field studies

Sintering is an important processing step in both ceramics and metals processing. The microstructure resulting from this process determines many materials properties of interest. Hence the accurate prediction of the microstructure, depending on processing and materials parameters, is of great importance. The phase-field method offers a way of predicting this microstructural evolution on a mesoscopic scale. The present paper employs this method to investigate concurrent densification and grain growth and the influence of stress on densification. Furthermore, the method is applied to simulate the entire freeze-casting process chain for the first time ever by simulating the freezing and sintering processes separately and passing the frozen microstructure to the present sintering model.

Roll-to-roll, high-resolution 3D printing of shape-specific particles

Particle fabrication has attracted recent attention owing to its diverse applications in bioengineering1,2, drug and vaccine delivery3-5, microfluidics6,7, granular systems8,9, self-assembly5,10,11, microelectronics12,13 and abrasives14. Herein we introduce a scalable, high-resolution, 3D printing technique for the fabrication of shape-specific particles based on roll-to-roll continuous liquid interface production (r2rCLIP). We demonstrate r2rCLIP using single-digit, micron-resolution optics in combination with a continuous roll of film (in lieu of a static platform), enabling the rapidly permutable fabrication and harvesting of shape-specific particles from a variety of materials and with complex geometries, including geometries not possible to achieve with advanced mould-based techniques. We demonstrate r2rCLIP production of mouldable and non-mouldable shapes with voxel sizes as small as 2.0 × 2.0 µm2 in the print plane and 1.1 ± 0.3 µm unsupported thickness, at speeds of up to 1,000,000 particles per day. Such microscopic particles with permutable, intricate designs enable direct integration within biomedical, analytical and advanced materials applications.

Scalable production of structurally colored composite films by shearing supramolecular composites of polymers and colloids

Structurally colored composite films, composed of orderly arranged colloids in polymeric matrix, are emerging flexible optical materials, but their production is bottlenecked by time-consuming procedures and limited material choices. Here, we present a mild approach to producing large-scale structurally colored composite films by shearing supramolecular composites composed of polymers and colloids with supramolecular interactions. Leveraging dynamic connection and dissociation of supramolecular interactions, shearing force stretches the polymer chains and drags colloids to migrate directionally within the polymeric matrix with reduced viscous resistance. We show that meter-scale structurally colored composite films with iridescence color can be produced within several minutes at room temperature. Significantly, the tunability and diversity of supramolecular interactions allow this shearing approach extendable to various commonly-used polymers. This study overcomes the traditional material limitations of manufacturing structurally colored composite films by shearing method and opens an avenue for mildly producing ordered composites with commonly-available materials via supramolecular strategies.

High-strength and crack-free welding of 2024 aluminium alloy via Zr-core-Al-shell wire

The 2000 series aluminium alloys are qualified for widespread use in lightweight structures, but solidification cracking during fusion welding has been a long-standing issue. Here, we create a zirconium (Zr)-core-aluminium (Al)-shell wire (ZCASW) and employ the oscillating laser-arc hybrid welding technique to control solidification during welding, and ultimately achieve reliable and crack-free welding of 2024 aluminium alloy. We select Zr wires with an ideal lattice match to Al based on crystallographic information and wind them by the Al wires with similar chemical components to the parent material. Crack-free, equiaxed (where the length, width and height of the grains are roughly equal), fine-grained microstructures are acquired, thereby considerably increasing the tensile strength over that of conventional fusion welding joints, and even comparable to that of friction stir welding joints. This work has important engineering application value in welding of high-strength aluminum alloys.

MatKG: An autonomously generated knowledge graph in Material Science

In this paper, we present MatKG, a knowledge graph in materials science that offers a repository of entities and relationships extracted from scientific literature. Using advanced natural language processing techniques, MatKG includes an array of entities, including materials, properties, applications, characterization and synthesis methods, descriptors, and symmetry phase labels. The graph is formulated based on statistical metrics, encompassing over 70,000 entities and 5.4 million unique triples. To enhance accessibility and utility, we have serialized MatKG in both CSV and RDF formats and made these, along with the code base, available to the research community. As the largest knowledge graph in materials science to date, MatKG provides structured organization of domain-specific data. Its deployment holds promise for various applications, including material discovery, recommendation systems, and advanced analytics.

Development of multifunctional membranes via plasma-assisted nonsolvent induced phase separation

Demands on superhydrophobic, self-cleaning and piezoelectric membranes have gained significantly due to their potential to overcome global shortages in clean water and energy. In this study, we have discovered a novel plasma-assisted nonsolvent induced phase separation (PANIPS) method to prepare superhydrophobic, self-cleaning and piezoelectric poly(vinylidene difluoride) (PVDF) membranes without additional chemical modifications or post-treatments. The PANIPS membranes exhibit water contact angles ranging from 151.2° to 166.4° and sliding angles between 6.7° and 29.7°. They also show a high piezoelectric coefficient (d33) of 10.5 pC N-1 and can generate a high output voltage of 10 Vpp. The PANIPS membranes can effectively recover pure water from various waste solutions containing Rose Bengal dye, humic acid, or sodium dodecyl sulfate via direct contact membrane distillation (DCMD). This study may provide valuable insights to fabricate PANIPS membranes and open up new avenues to molecularly design advanced superhydrophobic, self-cleaning, and piezoelectric membranes in the fields of clean water production, motion sensor, and piezoelectric nanogenerator.

Accurate additive manufacturing of lightweight and elastic carbons using plastic precursors

Despite groundbreaking advances in the additive manufacturing of polymers, metals, and ceramics, scaled and accurate production of structured carbons remains largely underdeveloped. This work reports a simple method to produce complex carbon materials with very low dimensional shrinkage from printed to carbonized state (less than 4%), using commercially available polypropylene precursors and a fused filament fabrication-based process. The control of macrostructural retention is enabled by the inclusion of fiber fillers regardless of the crosslinking degree of the polypropylene matrix, providing a significant advantage to directly control the density, porosity, and mechanical properties of 3D printed carbons. Using the same printed plastic precursors, different mechanical responses of derived carbons can be obtained, notably from stiff to highly compressible. This report harnesses the power of additive manufacturing for producing carbons with accurately controlled structure and properties, while enabling great opportunities for various applications.

Self-poled piezoelectric polymer composites via melt-state energy implantation

Lightweight flexible piezoelectric polymers are demanded for various applications. However, the low instinctively piezoelectric coefficient (i.e. d33) and complex poling process greatly resist their applications. Herein, we show that introducing dynamic pressure during fabrication is capable for poling polyvinylidene difluoride/barium titanate (PVDF/BTO) composites with d33 of ~51.20 pC/N at low density of ~0.64 g/cm3. The melt-state dynamic pressure driven energy implantation induces structure evolutions of both PVDF and BTO are demonstrated as reasons for self-poling. Then, the porous material is employed as pressure sensor with a high output of ~20.0 V and sensitivity of ~132.87 mV/kPa. Besides, the energy harvesting experiment suggests power density of ~58.7 mW/m2 can be achieved for 10 N pressure with a long-term durability. In summary, we not only provide a high performance lightweight, flexible piezoelectric polymer composite towards sustainable self-powered sensing and energy harvesting, but also pave an avenue for electrical-free fabrication of piezoelectric polymers.

Using millimeter-wave radar to evaluate the performance of dummy models for advanced driving assistance systems test

With the rapid development of intelligent and connected vehicles, the experimental road test for the advanced driving assistance system (ADAS) is dramatically increasing around the world. Considering its high cost and hazardous situations, simulation test based on a dummy model is becoming a promising way for ADAS road test practice to reduce the experiment expanses. This study proposed a methodology for the evaluation of the performance of human and dummies with distinct designed materials based on the data extracted from the Doppler effect of millimeter-wave radar. Echo data of 8 different angles from 0 to 360 degrees, with the an interval of 45 degrees, at the same distance between the test object and the signal source is collected. Meanwhile, the echo energy is collected for correlation modeling and analysis among groups. By evaluating the performance of humans and dummies via statistical analysis, a close correlation was found which results verified the substitutability of the dummy for the ADAS experiment test. The correlation coefficient between human and dummies ranges from 0.75 to 0.93. The support vector machine (SVM) model was developed and fitted to predict the echo energy in diverse environments. The mean average error (MAE) is 5.42-11.42 in the training and testing datasets while root mean square error (RMSE) is 0.43-0.90. The methods developed in the study can simulate the real ADAS road test environment and support future experimental research.

Accelerating process development for 3D printing of new metal alloys

Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently produce acceptable printing quality. Process mapping is typically performed by conventional methods and is used for the design of experiments and ex situ characterization of printed parts. On the other hand, in situ approaches are limited because their observable features are limited and they require complex high-cost setups to obtain temperature measurements to boost accuracy. Our method relaxes these limitations by incorporating the temporal features of molten metal dynamics during laser-metal interactions using video vision transformers and high-speed imaging. Our approach can be used in existing commercial machines and can provide in situ process maps for efficient defect and variability quantification. The generalizability of the approach is demonstrated by performing cross-dataset evaluations on alloys with different compositions and intrinsic thermofluid properties.

Assessment of refining efficiency during the refining cycle in a foundry degassing unit in industrial conditions

The article focuses on the issue of improving the efficiency of a Foundry Degassing Unit (FDU) via operational testing of aluminium alloys during casting at MOTOR JIKOV Slévárna a.s.. As part of the research, the efficiency of the refining process in the FDU was assessed. The main emphasis was placed on determining the moment of the greatest decrease in the hydrogen content in the melt and whether it is possible to shorten the refining cycle. The values of the Dichte Index were determined, on the basis of which the degassing curve was plotted and the progress of the melt degassing was assessed. To ensure the required quality of castings, the maximum allowable value of the Dichte Index ranged from 3 to 4%. During the process, the temperature drop during the refining cycle was also determined. The total temperature drop from pouring the melt into the ladle to the end of refining ranged from 26 to 32 °C, which is within the acceptable limits of the foundry. Based on the knowledge resulting from the operational experiments, recommendations were formulated to optimize the refining technology at the FDU for the MOTOR JIKOV Slévárna a.s. foundry.

Crack reduction in laser powder bed fusion of MnAl(C) using graphene oxide coated powders

MnAl(C) is a promising candidate as a rare earth free magnet. When processing MnAl(C) in laser powder bed fusion (L-PBF) the high cooling rates can retain the high temperature ε-phase which can then be annealed at low temperatures to yield the ferromagnetic τ-phase. However, MnAl(C) has been shown to be difficult to print using L-PBF and the material is prone to severe cracking. In this study, we have investigated how the addition of a graphene oxide (GO) coating on the powders can affect the processability of MnAl(C) and properties of the printed parts. MnAl(C) powders were coated with 0.2 wt.% GO using a wet-chemical process. The addition of GO reduced crack formation in the printed parts, and also influenced the degree of [Formula: see text] texture along the build direction. After printing, densities of 93% and 87% could be achieved for the reference and 0.2 wt.% GO, respectively. Furthermore, a 35% reduction of cracking was calculated from image analysis, comparing printed samples produced from coated and non-coated powders. Both powders formed mostly the ε-phase but some two-phase regions with a mix of γ- and ε-phase could be observed in the as-printed parts, but seemed to be more prominent in the uncoated reference samples and could also be linked to cracks. The τ-phase together with smaller amounts of secondary phases was obtained after heat treatment at 560 °C for 5 min for both samples. Vibrating sample magnetometry was used to measure the magnetic properties, the reference had a remanence of 33 Am2/kg and a coercivity of 139 kA/m, and the 0.2 wt.% GO sample showed a similar remanence of 30 Am2/kg and coercivity of 130 kA/m. These results show that GO coating is a viable method to reduce detrimental cracking in L-PBF MnAl without reducing the magnetic performance of the material.

3D microprinting of inorganic porous materials by chemical linking-induced solidification of nanocrystals

Three-dimensional (3D) microprinting is considered a next-generation manufacturing process for the production of microscale components; however, the narrow range of suitable materials, which include mainly polymers, is a critical issue that limits the application of this process to functional inorganic materials. Herein, we develop a generalised microscale 3D printing method for the production of purely inorganic nanocrystal-based porous materials. Our process is designed to solidify all-inorganic nanocrystals via immediate dispersibility control and surface linking-induced interconnection in the nonsolvent linker bath and thereby creates multibranched gel networks. The process works with various inorganic materials, including metals, semiconductors, magnets, oxides, and multi-materials, not requiring organic binders or stereolithographic equipment. Filaments with a diameter of sub-10 μm are printed into designed complex 3D microarchitectures, which exhibit full nanocrystal functionality and high specific surface areas as well as hierarchical porous structures. This approach provides the platform technology for designing functional inorganics-based porous materials.

3D printing of self-healing personalized liver models for surgical training and preoperative planning

3D printing can produce intuitive, precise, and personalized anatomical models, providing invaluable support for precision medicine, particularly in areas like surgical training and preoperative planning. However, conventional 3D printed models are often significantly more rigid than human organs and cannot undergo repetitive resection, which severely restricts their clinical value. Here we report the stereolithographic 3D printing of personalized liver models based on physically crosslinked self-healing elastomers with liver-like softness. Benefiting from the short printing time, the highly individualized models can be fabricated immediately following enhanced CT examination. Leveraging the high-efficiency self-healing performance, these models support repetitive resection for optimal trace through a trial-and-error approach. At the preliminary explorative clinical trial (NCT06006338), a total of 5 participants are included for preoperative planning. The primary outcomes indicate that the negative surgery margins are achieved and the unforeseen injuries of vital vascular structures are avoided. The 3D printing of liver models can enhance the safety of hepatic surgery, demonstrating promising application value in clinical practice.

Roll-to-plate 0.1-second shear-rolling process at elevated temperature for highly aligned nanopatterns

The shear-rolling process is a promising directed self-assembly method that can produce high-quality sub-10 nm block copolymer line-space patterns cost-effectively and straightforwardly over a large area. This study presents a high temperature (280 °C) and rapid (~0.1 s) shear-rolling process that can achieve a high degree of orientation in a single process while effectively preventing film delamination, that can be applied to large-area continuous processes. By minimizing adhesion, normal forces, and ultimate shear strain of the polydimethylsiloxane pad, shearing was successfully performed without peeling up to 280 °C at which the chain mobility significantly increases. This method can be utilized for various high-χ block copolymers and surface neutralization processes. It enables the creation of block copolymer patterns with a half-pitch as small as 8 nm in a unidirectional way. Moreover, the 0.1-second rapid shear-rolling was successfully performed on long, 3-inch width polyimide flexible films to validate its potential for the roll-to-roll process.

UV-curable thiol-ene system for broadband infrared transparent objects

Conventional infrared transparent materials, including inorganic ceramic, glass, and sulfur-rich organic materials, are usually processed through thermal or mechanical progress. Here, we report a photo-curable liquid material based on a specially designed thiol-ene strategy, where the multithiols and divinyl oligomers were designed to contain only C, H, and S atoms. This approach ensures transparency in a wide range spectrum from visible light to mid-wave infrared (MWIR), and to long-wave infrared (LWIR). The refractive index, thermal properties, and mechanical properties of samples prepared by this thiol-ene resin were characterized. Objects transparent to LWIR and MWIR were fabricated by molding and two-photon 3D printing techniques. We demonstrated the potential of our material in a range of applications, including the fabrication of IR optics with high imaging resolution and the construction of micro-reactors for temperature monitoring. This UV-curable thiol-ene system provides a fast and convenient alternative for the fabrication of thin IR transparent objects.

A comprehensive multimodal dataset for contactless lip reading and acoustic analysis

Small-scale motion detection using non-invasive remote sensing techniques has recently garnered significant interest in the field of speech recognition. Our dataset paper aims to facilitate the enhancement and restoration of speech information from diverse data sources for speakers. In this paper, we introduce a novel multimodal dataset based on Radio Frequency, visual, text, audio, laser and lip landmark information, also called RVTALL. Specifically, the dataset consists of 7.5 GHz Channel Impulse Response (CIR) data from ultra-wideband (UWB) radars, 77 GHz frequency modulated continuous wave (FMCW) data from millimeter wave (mmWave) radar, visual and audio information, lip landmarks and laser data, offering a unique multimodal approach to speech recognition research. Meanwhile, a depth camera is adopted to record the landmarks of the subject's lip and voice. Approximately 400 minutes of annotated speech profiles are provided, which are collected from 20 participants speaking 5 vowels, 15 words, and 16 sentences. The dataset has been validated and has potential for the investigation of lip reading and multimodal speech recognition.

Bioinspired rational design of bi-material 3D printed soft-hard interfaces

Durable interfacing of hard and soft materials is a major design challenge caused by the ensuing stress concentrations. In nature, soft-hard interfaces exhibit remarkable mechanical performance, with failures rarely happening at the interface. Here, we mimic the strategies observed in nature to design efficient soft-hard interfaces. We base our geometrical designs on triply periodic minimal surfaces (i.e., Octo, Diamond, and Gyroid), collagen-like triple helices, and randomly distributed particles. A combination of computational simulations and experimental techniques, including uniaxial tensile and quad-lap shear tests, are used to characterize the mechanical performance of the interfaces. Our analyses suggest that smooth interdigitated connections, compliant gradient transitions, and either decreasing or constraining strain concentrations lead to simultaneously strong and tough interfaces. We generate additional interfaces where the abovementioned toughening mechanisms work synergistically to create soft-hard interfaces with strengths approaching the upper achievable limit and enhancing toughness values by 50%, as compared to the control group.

A guidance system for robotic welding based on an improved YOLOv5 algorithm with a RealSense depth camera

Vision-based automatic welding guidance technology plays an essential role in robotic welding. A laser vision sensor (LVS) relies on manual intervention to guide the robot when near the workpiece, which reduces the autonomy of the welding robot and productivity. To solve this problem, a robot welding guidance system based on an improved YOLOv5 algorithm with a RealSense Depth Camera was proposed. A coordinate attention (CA) module was embedded in the original YOLOv5 algorithm to improve the accuracy of weld groove detection. The center of the predicted frame of the weld groove in the pixel plane was combined with the depth information acquired by a RealSense depth camera to calculate the actual position of the weld groove. Subsequently, the robot was guided to approach and move over the workpiece. Then, the LVS was used to guide the welding torch installed at the end of the robot to move along the centerline of the weld groove and complete welding tasks. The feasibility of the proposed method was verified by experiments. The maximum error was 2.9 mm in guiding experiments conducted with a distance of 300 mm between the depth camera and the workpiece. The percentage error was within 2% in guidance experiments conducted with distances from 0.3 to 2 m. The system combines the advantages of the depth camera for accurate positioning within a large field and the LVS for high accuracy. Once the position of the weld groove of the workpiece to be welded has been determined, the LVS combined with the robot can easily track the weld groove and realize the welding operation without manual intervention.

Defects detection of GMAW process based on convolutional neural network algorithm

It is significant to predict welding quality during gas metal arc welding process. The welding defect detection algorithm has been developed based on convolutional neural network (CNN). The sensing system and image processing algorithm for molten pools has been developed. It overcomes the interference caused by the arc light to obtain clear images of the molten pool's boundaries. The molten pools images are used to build up training set and test set for training and testing the CNN model. The model is designed to extract the visual features of molten pool images to predict the penetration state, the welding crater, and slags. Through optimizing the network parameters such as kernel-size, batch-size and learning rate, the prediction accuracy is higher than 95%. Moreover, the model enhances additional focus on the welding crater based on the welder experience. The mechanisms between molten pool characteristics and welding defects were analyzed based on the welder experience and the visual features of the model. It is found that the model judges the occurrence of burn-through with the black hole in the middle zone of the molten pool. When the surface pores are generated, the model exhibits a strong response to circular voids in the semi-solid region at the trailing end of the molten pool. The size and shape of fusion holes exhibit a strong correlation with the molten state. When the shape of the crater does not appear concave, it often signifies excessive penetration. It contributes to enhancing the algorithm's robustness during various welding scenarios.

Simulation study of a novel small animal FLASH irradiator (SAFI) with integrated inverse-geometry CT based on circularly distributed kV X-ray sources

Ultra-high dose rate (UHDR) radiotherapy (RT) or FLASH-RT can potentially reduce normal tissue toxicity. A small animal irradiator that can deliver FLASH-RT treatments similar to clinical RT treatments is needed for pre-clinical studies of FLASH-RT. We designed and simulated a novel small animal FLASH irradiator (SAFI) based on distributed x-ray source technology. The SAFI system comprises a distributed x-ray source with 51 focal spots equally distributed on a 20 cm diameter ring, which are used for both FLASH-RT and onboard micro-CT imaging. Monte Carlo simulation was performed to estimate the dosimetric characteristics of the SAFI treatment beams. The maximum dose rate, which is limited by the power density of the tungsten target, was estimated based on finite-element analysis (FEA). The maximum DC electron beam current density is 2.6 mA/mm2, limited by the tungsten target's linear focal spot power density. At 160 kVp, 51 focal spots, each with a dimension of [Formula: see text] mm2 and 10° anode angle, can produce up to 120 Gy/s maximum DC irradiation at the center of a cylindrical water phantom. We further demonstrate forward and inverse FLASH-RT planning, as well as inverse-geometry micro-CT with circular source array imaging via numerical simulations.

Inverted laser sintering of metal powders

We demonstrate the ability of the inverted laser sintering process to manufacture parts composed of metal powder. We fabricate a 10-layer part by depositing a layer of copper powder onto a sapphire plate, then pressing the plate against the part being built and sintering the powder onto the part by shining a 14W 445 nm laser through the glass. The process was then repeated multiple times, each time adding a new layer to the component being printed until completion. We discuss the potential applications and impacts of this process, including the ability to directly fabricate multi-material metallic parts without the use of a powder bed.

Autonomous and dynamic precursor selection for solid-state materials synthesis

Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and conditions to be tested. Here we introduce an algorithm (ARROWS3) designed to automate the selection of optimal precursors for solid-state materials synthesis. This algorithm actively learns from experimental outcomes to determine which precursors lead to unfavorable reactions that form highly stable intermediates, preventing the target material's formation. Based on this information, ARROWS3 proposes new experiments using precursors it predicts to avoid such intermediates, thereby retaining a larger thermodynamic driving force to form the target. We validate this approach on three experimental datasets, containing results from over 200 synthesis procedures. In comparison to black-box optimization, ARROWS3 identifies effective precursor sets for each target while requiring substantially fewer experimental iterations. These findings highlight the importance of domain knowledge in optimization algorithms for materials synthesis, which are critical for the development of fully autonomous research platforms.

Design of novel highly sensitive sensors for crack detection in metal surfaces: theoretical foundation and experimental validation

The application of different types of microwave resonators for sensing cracks in metallic structures has been subject of many studies. While most studies have been focused on improving the sensitivity of planar crack sensors, the theoretical foundation of the topic has not been treated in much detail. The major objective of this study is to perform an exhaustive study of the principles and theoretical foundations for crack sensing based on planar microwave resonators, especially defective ground structures (DGS) including complementary split ring resonators (CSRRs). The analysis is carried out from the equivalent circuit model as well as the electromagnetic (EM) field perspectives, and guidelines for the design of crack sensors with high sensitivity are developed. Numerical and experimental validation of the provided theoretical analysis is another aim of this article. With this aim, the developed guidelines are used to design a crack sensor based on a single-ring CSRR. It is shown that the sensitivity of the proposed sensor is almost three times higher than the sensitivity of a conventional double-ring CSRR. Moreover, it is demonstrated that folded dumbbell-shape DGS resonators can be used to achieve even higher sensitivities. The CSRR-based crack sensors presented in this study and other studies available in the literature are only sensitive to cracks with a specific orientation. To address this limitation, a modified version of the DGS is proposed to sense cracks with arbitrary orientations at the cost of lower sensitivity. The performance of all the presented sensors is validated through EM simulation, equivalent circuit model extraction, and measurement of the fabricated prototypes.

Material-agnostic machine learning approach enables high relative density in powder bed fusion products

This study introduces a method that is applicable across various powder materials to predict process conditions that yield a product with a relative density greater than 98% by laser powder bed fusion. We develop an XGBoost model using a dataset comprising material properties of powder and process conditions, and its output, relative density, undergoes a transformation using a sigmoid function to increase accuracy. We deeply examine the relationships between input features and the target value using Shapley additive explanations. Experimental validation with stainless steel 316 L, AlSi10Mg, and Fe60Co15Ni15Cr10 medium entropy alloy powders verifies the method's reproducibility and transferability. This research contributes to laser powder bed fusion additive manufacturing by offering a universally applicable strategy to optimize process conditions.

In situ observation of melt pool evolution in ultrasonic vibration-assisted directed energy deposition

The presence of defects, such as pores, in materials processed using additive manufacturing represents a challenge during the manufacturing of many engineering components. Recently, ultrasonic vibration-assisted (UV-A) directed energy deposition (DED) has been shown to reduce porosity, promote grain refinement, and enhance mechanical performance in metal components. Whereas it is evident that the formation of such microstructural features is affected by the melt pool behavior, the specific mechanisms by which ultrasonic vibration (UV) influences the melt pool remain elusive. In the present investigation, UV was applied in situ to DED of 316L stainless steel single tracks and bulk parts. For the first time, high-speed video imaging and thermal imaging were implemented in situ to quantitatively correlate the application of UV to melt pool evolution in DED. Extensive imaging data were coupled with in-depth microstructural characterization to develop a statistically robust dataset describing the observed phenomena. Our findings show that UV increases the melt pool peak temperature and dimensions, while improving the wettability of injected particles with the melt pool surface and reducing particle residence time. Near the substrate, we observe that UV results in a 92% decrease in porosity, and a 54% decrease in dendritic arm spacing. The effect of UV on the melt pool is caused by the combined mechanisms of acoustic cavitation, ultrasound absorption, and acoustic streaming. Through in situ imaging we demonstrate quantitatively that these phenomena, acting simultaneously, effectively diminish with increasing build height and size due to acoustic attenuation, consequently decreasing the positive effect of implementing UV-A DED. Thus, this research provides valuable insight into the value of in situ imaging, as well as the effects of UV on DED melt pool dynamics, the stochastic interactions between the melt pool and incoming powder particles, and the limitations of build geometry on the UV-A DED technique.

Design and fabrication of 3D-printed patient-specific soft tissue and bone phantoms for CT imaging

The objective of this study is to create patient-specific phantoms for computed tomography (CT) that possess accurate densities and exhibit visually realistic image textures. These qualities are crucial for evaluating CT performance in clinical settings. The study builds upon a previously presented 3D printing method (PixelPrint) by incorporating soft tissue and bone structures. We converted patient DICOM images directly into 3D printer instructions using PixelPrint and utilized calcium-doped filament to increase the Hounsfield unit (HU) range. Density was modeled by controlling printing speed according to volumetric filament ratio to emulate attenuation profiles. We designed micro-CT phantoms to demonstrate the reproducibility, and to determine mapping between filament ratios and HU values on clinical CT systems. Patient phantoms based on clinical cervical spine and knee examinations were manufactured and scanned with a clinical spectral CT scanner. The CT images of the patient-based phantom closely resembled original CT images in visual texture and contrast. Micro-CT analysis revealed minimal variations between prints, with an overall deviation of ± 0.8% in filament line spacing and ± 0.022 mm in line width. Measured differences between patient and phantom were less than 12 HU for soft tissue and 15 HU for bone marrow, and 514 HU for cortical bone. The calcium-doped filament accurately represented bony tissue structures across different X-ray energies in spectral CT (RMSE ranging from ± 3 to ± 28 HU, compared to 400 mg/ml hydroxyapatite). In conclusion, this study demonstrated the possibility of extending 3D-printed patient-based phantoms to soft tissue and bone structures while maintaining accurate organ geometry, image texture, and attenuation profiles.

A Monte Carlo model of the Dingo thermal neutron imaging beamline

In this study, we present a validated Geant4 Monte Carlo simulation model of the Dingo thermal neutron imaging beamline at the Australian Centre for Neutron Scattering. The model, constructed using CAD drawings of the entire beam transport path and shielding structures, is designed to precisely predict the in-beam neutron field at the position at the sample irradiation stage. The model's performance was assessed by comparing simulation results to various experimental measurements, including planar thermal neutron distribution obtained in-beam using gold foil activation and [Formula: see text]B[Formula: see text]C-coated microdosimeters and the out-of-beam neutron spectra measured with Bonner spheres. The simulation results demonstrated that the predicted neutron fluence at the field's centre is within 8.1% and 2.1% of the gold foil and [Formula: see text]B[Formula: see text]C-coated microdosimeter measurements, respectively. The logarithms of the ratios of average simulated to experimental fluences in the thermal (E[Formula: see text] 0.414 eV), epithermal (0.414 eV < E[Formula: see text] 11.7 keV) and fast (E[Formula: see text] 11.7 keV) spectral regions were approximately - 0.03 to + 0.1, - 0.2 to + 0.15, and - 0.4 to + 0.2, respectively. Furthermore, the predicted thermal, epithermal and fast neutron components in-beam at the sample stage position constituted approximately 18%, 64% and 18% of the total neutron fluence.

Fully automatic transfer and measurement system for structural superlubric materials

Structural superlubricity, a state of nearly zero friction and no wear between two contact surfaces under relative sliding, holds immense potential for research and application prospects in micro-electro-mechanical systems devices, mechanical engineering, and energy resources. A critical step towards the practical application of structural superlubricity is the mass transfer and high throughput performance evaluation. Limited by the yield rate of material preparation, existing automated systems, such as roll printing or massive stamping, are inadequate for this task. In this paper, a machine learning-assisted system is proposed to realize fully automated selective transfer and tribological performance measurement for structural superlubricity materials. Specifically, the system has a judgment accuracy of over 98% for the selection of micro-scale graphite flakes with structural superlubricity properties and complete the 100 graphite flakes assembly array to form various pre-designed patterns within 100 mins, which is 15 times faster than manual operation. Besides, the system is capable of automatically measuring the tribological performance of over 100 selected flakes on Si3N4, delivering statistical results for new interface which is beyond the reach of traditional methods. With its high accuracy, efficiency, and robustness, this machine learning-assisted system promotes the fundamental research and practical application of structural superlubricity.

Enhanced atmospheric water harvesting efficiency through green-synthesized MOF-801: a comparative study with solvothermal synthesis

Adsorption-based atmospheric water harvesting has emerged as a compelling solution in response to growing global water demand. In this context, Metal-organic frameworks (MOFs) have garnered considerable interest due to their unique structure and intrinsic porosity. Here, MOF 801 was synthesized using two different methods: solvothermal and green room temperature synthesis. Comprehensive characterization indicated the formation of MOF-801 with high phase purity, small crystallite size, and excellent thermal stability. Nitrogen adsorption-desorption analysis revealed that green-synthesized MOF-801 possessed an 89% higher specific surface area than its solvothermal-synthesized counterpart. Both adsorbents required activation at a minimum temperature of 90 °C for optimal adsorption performance. Additionally, green-synthesized MOF-801 demonstrated superior adsorption performance compared to solvothermal-synthesized MOF-801, attributed to its small crystal size (around 66 nm), more hydrophilic functional groups, greater specific surface area (691.05 m2/g), and the possibility of having a higher quantity of defects. The maximum water adsorption capacity in green-synthesized MOF-801 was observed at 25 °C and 80% relative humidity, with a value of 41.1 g/100 g, a 12% improvement over the solvothermal-synthesized MOF-801. Remarkably, even at a 30% humidity level, green-synthesized MOF-801 displayed a considerable adsorption capacity of 31.5 g/100 g. Importantly, MOF-801 exhibited long-term effectiveness in multiple adsorption cycles without substantial efficiency decline.

Mechanism of the noncatalytic oxidation of soot using in situ transmission electron microscopy

Soot generation is a major challenge in industries. The elimination of soot is particularly crucial to reduce pollutant emissions and boost carbon conversion. The mechanisms for soot oxidation are complex, with quantified models obtained under in situ conditions still missing. We prepare soot samples via noncatalytic partial oxidation of methane. Various oxidation models are established based on the results of in situ transmission electron microscopy experiments. A quantified maturity parameter is proposed and used to categorize the soot particles according to the nanostructure at various maturity levels, which in turn lead to different oxidation mechanisms. To tackle the challenges in the kinetic analysis of soot aggregates, a simplification model is proposed and soot oxidation rates are quantified. In addition, a special core-shell separation model is revealed through in situ analysis and kinetic studies. In this study, we obtain important quantified models for soot oxidation under in situ conditions.

Effect of microstructure refinement of pure copper on improving the performance of electrodes in electro discharge machining (EDM)

The paper presents an analysis of the impact of plastic deformation using hydrostatic extrusion (HE) on the structural, mechanical and functional properties of pure copper for use as electrodes in the process of electro discharge machining (EDM). As part of the research, copper was subjected to the HE process with the maximum cumulative true strain equal to ɛcum = 3.89 obtained in 5 stages. The result was, a refinement of the microstructure with the grains elongated in the direction of extrusion, with a cross-sectional size of d2 = 228 nm. As the obtained material can be potentially used in the process of electro discharge machining, the copper specimens after the HE process were subjected to a comprehensive analysis to determine the mechanical, physical and functional properties of the material. A significant increase in strength (UTS) and yield strength (YS) of the HE-processed copper was obtained, reaching respectively UTS = 464 MPa and YS = 456 MPa at the maximum strain of ɛ = 3.89. Despite the clear strain-induced strengthening of the material, a very high electrical conductivity of not less than 97% was obtained. The electrodes made of copper after HE process have reduced erosion wear while maintaining a comparable or better quality of the machined surface. The best results were obtained for finish machining, where the electrical discharge wear was lower by 60% compared to the electrode made of non-processed copper. In addition, an improvement in the surface quality after the EDM process by 25% was observed when using the HE-processed electrodes.

Controlling crystallites orientation and facet exposure for enhanced electrochemical properties of polycrystalline MoO3 films

This study focuses on the development and optimization of MoO3 films on commercially available FTO substrates using the pulsed laser deposition (PLD) technique. By carefully selecting deposition conditions and implementing post-treatment procedures, precise control over crystallite orientation relative to the substrate is achieved. Deposition at 450 °C in O2 atmosphere results in random crystallite arrangement, while introducing argon instead of oxygen to the PLD chamber during the initial stage of sputtering exposes the (102) and (011) facets. On the other hand, room temperature deposition leads to the formation of amorphous film, but after appropriate post-annealing treatment, the (00k) facets were exposed. The deposited films are studied using SEM and XRD techniques. Moreover, electrochemical properties of FTO/MoO3 electrodes immersed in 1 M AlCl3 aqueous solution are evaluated using cyclic voltammetry and electrochemical impedance spectroscopy. The results demonstrate that different electrochemical processes are promoted based on the orientation of crystallites. When the (102) and (011) facets are exposed, the Al3+ ions intercalation induced by polarization is facilitated, while the (00k) planes exposure leads to the diminished hydrogen evolution reaction overpotential.

A SISO FMCW radar based on inherently frequency scanning antennas for 2-D indoor tracking of multiple subjects

The contextual non-invasive monitoring and tracking of multiple human targets for health and surveillance purposes is an increasingly investigated application. Radars are good candidates, since they are able to remotely monitor people without raising privacy concerns. However, radar systems are typically based on complex architectures involving multiple channels and antennas, such as multiple-input and multiple-output (MIMO) or electronic beam scanning, resulting also in a high power consumption. In contrast with existing technologies, this paper proposes a single-input and single-output (SISO) frequency-modulated continuous wave (FMCW) radar in combination with frequency scanning antennas for tracking multiple subjects in indoor environments. A data processing method is also presented for angular separation and clutter removal. The system was successfully tested in five realistic indoor scenarios involving paired subjects, which were either static or moving along predefined paths varying their range and angular position. In all scenarios, the radar was able to track the targets, reporting a maximum mean absolute error (MAE) of 20 cm and 5.64[Formula: see text] in range and angle, respectively. Practical applications arise for ambient assisted living, telemedicine, smart building applications and surveillance.