Titanium (Ti) alloys are widely used in high-tech fields like aerospace and biomedical engineering. Laser additive manufacturing (LAM), as an innovative technology, is the key driver for the development of Ti alloys. Despite the significant advancements in LAM of Ti alloys, there remain challenges that need further research and development efforts. To recap the potential of LAM high-performance Ti alloy, this article systematically reviews LAM Ti alloys with up-to-date information on process, materials, and properties. Several feasible solutions to advance LAM Ti alloys are reviewed, including intelligent process parameters optimization, LAM process innovation with auxiliary fields and novel Ti alloys customization for LAM. The auxiliary energy fields (e.g. thermal, acoustic, mechanical deformation and magnetic fields) can affect the melt pool dynamics and solidification behaviour during LAM of Ti alloys, altering microstructures and mechanical performances. Different kinds of novel Ti alloys customized for LAM, like peritectic α-Ti, eutectoid (α + β)-Ti, hybrid (α + β)-Ti, isomorphous β-Ti and eutectic β-Ti alloys are reviewed in detail. Furthermore, machine learning in accelerating the LAM process optimization and new materials development is also outlooked. This review summarizes the material properties and performance envelops and benchmarks the research achievements in LAM of Ti alloys. In addition, the perspectives and further trends in LAM of Ti alloys are also highlighted.

Difficult-to-machine materials (DMMs) are extensively applied in critical fields such as aviation, semiconductor, biomedicine, and other key fields due to their excellent material properties. However, traditional machining technologies often struggle to achieve ultra-precision with DMMs resulting from poor surface quality and low processing efficiency. In recent years, field-assisted machining (FAM) technology has emerged as a new generation of machining technology based on innovative principles such as laser heating, tool vibration, magnetic magnetization, and plasma modification, providing a new solution for improving the machinability of DMMs. This technology not only addresses these limitations of traditional machining methods, but also has become a hot topic of research in the domain of ultra-precision machining of DMMs. Many new methods and principles have been introduced and investigated one after another, yet few studies have presented a comprehensive analysis and summarization. To fill this gap and understand the development trend of FAM, this study provides an important overview of FAM, covering different assisted machining methods, application effects, mechanism analysis, and equipment design. The current deficiencies and future challenges of FAM are summarized to lay the foundation for the further development of multi-field hybrid assisted and intelligent FAM technologies.

Neuromorphic computing systems, which mimic the operation of neurons and synapses in the human brain, are seen as an appealing next-generation computing method due to their strong and efficient computing abilities. Two-dimensional (2D) materials with dangling bond-free surfaces and atomic-level thicknesses have emerged as promising candidates for neuromorphic computing hardware. As a result, 2D neuromorphic devices may provide an ideal platform for developing multifunctional neuromorphic applications. Here, we review the recent neuromorphic devices based on 2D material and their multifunctional applications. The synthesis and next micro-nano fabrication methods of 2D materials and their heterostructures are first introduced. The recent advances of neuromorphic 2D devices are discussed in detail using different operating principles. More importantly, we present a review of emerging multifunctional neuromorphic applications, including neuromorphic visual, auditory, tactile, and nociceptive systems based on 2D devices. In the end, we discuss the problems and methods for 2D neuromorphic device developments in the future. This paper will give insights into designing 2D neuromorphic devices and applying them to the future neuromorphic systems.

As the manufacturing process of silicon-based integrated circuits (ICs) approaches its physical limit, the quantum effect of silicon-based field-effect transistors (FETs) has become increasingly evident. And the burgeoning carbon-based semiconductor technology has become one of the most disruptive technologies in the post-Moore era. As one-dimensional nanomaterials, carbon nanotubes (CNTs) are far superior to silicon at the same technology nodes of FETs because of their excellent electrical transport and scaling properties, rendering them the most competitive material in the next-generation ICs technology. However, certain challenges impede the industrialization of CNTs, particularly in terms of material preparation, which significantly hinders the development of CNT-based ICs. Focusing on CNT-based ICs technology, this review summarizes its main technical status, development trends, existing challenges, and future development directions.

Microfluidic devices are composed of microchannels with a diameter ranging from ten to a few hundred micrometers. Thus, quite a small (10^-9–10^-18 l) amount of liquid can be manipulated by such a precise system. In the past three decades, significant progress in materials science, microfabrication, and various applications has boosted the development of promising functional microfluidic devices. In this review, the recent progress on novel microfluidic devices with various functions and applications is presented. First, the theory and numerical methods for studying the performance of microfluidic devices are briefly introduced. Then, materials and fabrication methods of functional microfluidic devices are summarized. Next, the recent significant advances in applications of microfluidic devices are highlighted, including heat sinks, clean water production, chemical reactions, sensors, biomedicine, capillaric circuits, wearable electronic devices, and microrobotics. Finally, perspectives on the challenges and future developments of functional microfluidic devices are presented. This review aims to inspire researchers from various fields—engineering, materials, chemistry, mathematics, physics, and more—to collaborate and drive forward the development and applications of functional microfluidic devices, specifically for achieving carbon neutrality.

Embedded memory, which heavily relies on the manufacturing process, has been widely adopted in various industrial applications. As the field of embedded memory continues to evolve, innovative strategies are emerging to enhance performance. Among them, resistive random access memory (RRAM) has gained significant attention due to its numerous advantages over traditional memory devices, including high speed (<1 ns), high density (4 F²·n^-1), high scalability (~nm), and low power consumption (~pJ). This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potential applications. It provides a brief introduction to the concepts and advantages of RRAM, discusses the key factors that impact its industrial manufacturing, and presents the commercial progress driven by cutting-edge nanotechnology, which has been pursued by many semiconductor giants. Additionally, it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing, with a particular emphasis on its role in neuromorphic computing. Finally, the review discusses the current challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.

Single atom catalysts (SACs) have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties. For the semiconductor-based electrical gas sensor, the core is the catalysis process of target gas molecules on the sensitive materials. In this context, the SACs offer great potential for highly sensitive and selective gas sensing, however, only some of the bubbles come to the surface. To facilitate practical applications, we present a comprehensive review of the preparation strategies for SACs, with a focus on overcoming the challenges of aggregation and low loading. Extensive research efforts have been devoted to investigating the gas sensing mechanism, exploring sensitive materials, optimizing device structures, and refining signal post-processing techniques. Finally, the challenges and future perspectives on the SACs based gas sensing are presented.

Owing to the advantages of simple structure, low power consumption and high-density integration, memristors or memristive devices are attracting increasing attention in the fields such as next generation non-volatile memories, neuromorphic computation and data encryption. However, the deposition of memristive films often requires expensive equipment, strict vacuum conditions, high energy consumption, and extended processing times. In contrast, electrochemical anodizing can produce metal oxide films quickly (e.g. 10 s) under ambient conditions. By means of the anodizing technique, oxide films, oxide nanotubes, nanowires and nanodots can be fabricated to prepare memristors. Oxide film thickness, nanostructures, defect concentrations, etc, can be varied to regulate device performances by adjusting oxidation parameters such as voltage, current and time. Thus memristors fabricated by the anodic oxidation technique can achieve high device consistency, low variation, and ultrahigh yield rate. This article provides a comprehensive review of the research progress in the field of anodic oxidation assisted fabrication of memristors. Firstly, the principle of anodic oxidation is introduced; then, different types of memristors produced by anodic oxidation and their applications are presented; finally, features and challenges of anodic oxidation for memristor production are elaborated.

Metal additive manufacturing (AM) technologies have made significant progress in the basic theoretical field since their invention in the 1970s. However, performance instability during continuous processing, such as thermal history, residual stress accumulation, and columnar grain epitaxial growth, consistently hinders their broad application in standardized industrial production. To overcome these challenges, performance-control-oriented hybrid AM (HAM) technologies have been introduced. These technologies, by leveraging external auxiliary processes, aim to regulate microstructural evolution and mechanical properties during metal AM. This paper provides a systematic and detailed review of performance-control-oriented HAM technology, which is categorized into two main groups: energy field-assisted AM (EFed AM, e.g. ultrasonic, electromagnetic, and heat) technologies and interlayer plastic deformation-assisted AM (IPDed AM, e.g. laser shock peening, rolling, ultrasonic peening, and friction stir process) technologies. This review covers the influence of external energy fields on the melting, flow, and solidification behavior of materials, and the regulatory effects of interlayer plastic deformation on grain refinement, nucleation, and recrystallization. Furthermore, the role of performance-control-oriented HAM technologies in managing residual stress conversion, metallurgical defect closure, mechanical property improvement, and anisotropy regulation is thoroughly reviewed and discussed. The review concludes with an analysis of future development trends in EFed AM and IPDed AM technologies.

In the last three decades, carbon dioxide (CO₂) emissions have shown a significant increase from various sources. To address this pressing issue, the importance of reducing CO₂ emissions has grown, leading to increased attention toward carbon capture, utilization, and storage strategies. Among these strategies, monodisperse microcapsules, produced by using droplet microfluidics, have emerged as promising tools for carbon capture, offering a potential solution to mitigate CO₂ emissions. However, the limited yield of microcapsules due to the inherent low flow rate in droplet microfluidics remains a challenge. In this comprehensive review, the high-throughput production of carbon capture microcapsules using droplet microfluidics is focused on. Specifically, the detailed insights into microfluidic chip fabrication technologies, the microfluidic generation of emulsion droplets, along with the associated hydrodynamic considerations, and the generation of carbon capture microcapsules through droplet microfluidics are provided. This review highlights the substantial potential of droplet microfluidics as a promising technique for large-scale carbon capture microcapsule production, which could play a significant role in achieving carbon neutralization and emission reduction goals.

With the arrival of the era of artificial intelligence (AI) and big data, the explosive growth of data has raised higher demands on computer hardware and systems. Neuromorphic techniques inspired by biological nervous systems are expected to be one of the approaches to breaking the von Neumann bottleneck. Piezotronic neuromorphic devices modulate electrical transport characteristics by piezopotential and directly associate external mechanical motion with electrical output signals in an active manner, with the capability to sense/store/process information of external stimuli. In this review, we have presented the piezotronic neuromorphic devices (which are classified into strain-gated piezotronic transistors and piezoelectric nanogenerator-gated field effect transistors based on device structure) and discussed their operating mechanisms and related manufacture techniques. Secondly, we summarized the research progress of piezotronic neuromorphic devices in recent years and provided a detailed discussion on multifunctional applications, including bionic sensing, information storage, logic computing, and electrical/optical artificial synapses. Finally, in the context of future development, challenges, and perspectives, we have discussed how to modulate novel neuromorphic devices with piezotronic effects more effectively. It is believed that the piezotronic neuromorphic devices have great potential for the next generation of interactive sensation/memory/computation to facilitate the development of the Internet of Things, AI, biomedical engineering, etc.

It has always been challenging work to reconcile the contradiction between the strength and plasticity of titanium materials. Laser powder bed fusion (LPBF) is a convenient method to fabricate innovative composites including those inspired by gradient layered materials. In this work, we used LPBF to selectively prepare TiN/Ti gradient layered structure (GLSTi) composites by using different N₂–Ar ratios during the LPBF process. We systematically investigated the mechanisms of in-situ synthesis TiN, high strength and ductility of GLSTi composites using microscopic analysis, TEM characterization, and tensile testing with digital image correlation. Besides, a digital correspondence was established between the N₂ concentration and the volume fraction of LPBF in-situ synthesized TiN. Our results show that the GLSTi composites exhibit superior mechanical properties compared to pure titanium fabricated by LPBF under pure Ar. Specifically, the tensile strength of GLSTi was more than 1.5 times higher than that of LPBF-formed pure titanium, reaching up to 1100 MPa, while maintaining a high elongation at fracture of 17%. GLSTi breaks the bottleneck of high strength but low ductility exhibited by conventional nanoceramic particle-strengthened titanium matrix composites, and the hetero-deformation induced strengthening effect formed by the TiN/Ti layered structure explained its strength-plasticity balanced principle. The microhardness exhibits a jagged variation of the relatively low hardness of 245 HV0.2 for the pure titanium layer and a high hardness of 408 HV0.2 for the N₂ in-situ synthesis layer. Our study provides a new concept for the structure-performance digital customization of 3D-printed Ti-based composites.

The use of ‘Electrostatic tweezers’ is a promising tool for droplet manipulation, but it faces many limitations in manipulating droplets on superhydrophobic surfaces. Here, we achieve noncontact and multifunctional droplet manipulation on Nepenthes-inspired lubricated slippery surfaces via triboelectric electrostatic tweezers (TETs). The TET manipulation of droplets on a slippery surface has many advantages over electrostatic droplet manipulation on a superhydrophobic surface. The electrostatic field induces the redistribution of the charges inside the neutral droplet, which causes the triboelectric charged rod to drive the droplet to move forward under the electrostatic force. Positively or negatively charged droplets can also be driven by TET based on electrostatic attraction and repulsion. TET enables us to manipulate droplets under diverse conditions, including anti-gravity climb, suspended droplets, corrosive liquids, low-surface-tension liquids (e.g. ethanol with a surface tension of 22.3 mN·m⁻¹), different droplet volumes (from 100 nl to 0.5 ml), passing through narrow slits, sliding over damaged areas, on various solid substrates, and even droplets in an enclosed system. Various droplet-related applications, such as motion guidance, motion switching, droplet-based microreactions, surface cleaning, surface defogging, liquid sorting, and cell labeling, can be easily achieved with TETs.

The remarkable capabilities of 2D plasmonic surfaces in controlling optical waves have garnered significant attention. However, the challenge of large-scale manufacturing of uniform, well-aligned, and tunable plasmonic surfaces has hindered their industrialization. To address this, we present a groundbreaking tunable plasmonic platform design achieved through magnetic field (MF) assisted ultrafast laser direct deposition in air. Through precise control of metal nanoparticles (NPs), with cobalt (Co) serving as the model material, employing an MF, and fine-tuning ultrafast laser parameters, we have effectively converted coarse and non-uniform NPs into densely packed, uniform, and ultrafine NPs (~3 nm). This revolutionary advancement results in the creation of customizable plasmonic 'hot spots,' which play a pivotal role in surface-enhanced Raman spectroscopy (SERS) sensors. The profound impact of this designable plasmonic platform lies in its close association with plasmonic resonance and energy enhancement. When the plasmonic nanostructures resonate with incident light, they generate intense local electromagnetic fields, thus vastly increasing the Raman scattering signal. This enhancement leads to an outstanding 2-18 fold boost in SERS performance and unparalleled sensing sensitivity down to 10-10 M. Notably, the plasmonic platform also demonstrates robustness, retaining its sensing capability even after undergoing 50 cycles of rinsing and re-loading of chemicals. Moreover, this work adheres to green manufacturing standards, making it an efficient and environmentally friendly method for customizing plasmonic 'hot spots' in SERS devices. Our study not only achieves the formation of high-density, uniform, and ultrafine NP arrays on a tunable plasmonic platform but also showcases the profound relation between The remarkable capabilities of 2D plasmonic surfaces in controlling optical waves have garnered significant attention. However, the challenge of large-scale manufacturing of uniform, well-aligned, and tunable plasmonic surfaces has hindered their industrialization. To address this, we present a groundbreaking tunable plasmonic platform design achieved through magnetic field (MF) assisted ultrafast laser direct deposition in air. Through precise control of metal nanoparticles (NPs), with cobalt (Co) serving as the model material, employing an MF, and fine-tuning ultrafast laser parameters, we have effectively converted coarse and non-uniform NPs into densely packed, uniform, and ultrafine NPs (∼3 nm). This revolutionary advancement results in the creation of customizable plasmonic 'hot spots,' which play a pivotal role in surface-enhanced Raman spectroscopy (SERS) sensors. The profound impact of this designable plasmonic platform lies in its close association with plasmonic resonance and energy enhancement. When the plasmonic nanostructures resonate with incident light, they generate intense local electromagnetic fields, thus vastly increasing the Raman scattering signal. This enhancement leads to an outstanding 2-18 fold boost in SERS performance and unparalleled sensing sensitivity down to 10^-10 M. Notably, the plasmonic platform also demonstrates robustness, retaining its sensing capability even after undergoing 50 cycles of rinsing and re-loading of chemicals. Moreover, this work adheres to green manufacturing standards, making it an efficient and environmentally friendly method for customizing plasmonic 'hot spots' in SERS devices. Our study not only achieves the formation of high-density, uniform, and ultrafine NP arrays on a tunable plasmonic platform but also showcases the profound relation between plasmonic resonance and energy enhancement. The outstanding results observed in SERS sensors further emphasize the immense potential of this technology for energy-related applications, including photocatalysis, photovoltaics, and clean water, propelling us closer to a sustainable and cleaner future.

Mask image projection-based vat photopolymerization (MIP-VPP) offers advantages like low cost, high resolution, and a wide material range, making it popular in industry and education. Recently, MIP-VPP employing liquid crystal displays (LCDs) has gained traction, increasingly replacing digital micromirror devices, particularly among hobbyists and in educational settings, and is now beginning to be used in industrial environments. However, LCD-based MIP-VPP suffers from pronounced pixelated aliasing arising from LCD’s discrete image pixels and its direct-contact configuration in MIP-VPP machines, leading to rough surfaces on the 3D-printed parts. Here, we propose a vibration-assisted MIP-VPP method that utilizes a microscale vibration to uniformize the light intensity distribution of the LCD-based mask image on VPP’s building platform. By maintaining the same fabrication speed, our technique generates a smoother, non-pixelated mask image, reducing the roughness on flat surfaces and boundary segments of 3D-printed parts. Through light intensity modeling and simulation, we derived an optimal vibration pattern for LCD mask images, subsequently validated by experiments. We assessed the surface texture, boundary integrity, and dimensional accuracy of components produced using the vibration-assisted approach. The notably smoother surfaces and improved boundary roughness enhance the printing quality of MIP-VPP, enabling its promising applications in sectors like the production of 3D-printed optical devices and others.

Fatigue properties are crucial for critical aero-engine components in extreme service environments, which are significantly affected by surface integrity (SI) indexes (especially surface topography, residual stress σ_res, and microhardness) after machining processes. Normal-direction ultrasonic vibration-assisted face grinding (ND-UVAFG) has advantages in improving the machinability of Inconel 718, but there is a competitive relationship between higher compressive σ_res and higher surface roughness R_a in affecting fatigue strength. The lack of a quantitative relationship between multiple SI indexes and fatigue strength makes the indeterminacy of a regulatory strategy for improving fatigue properties. In this work, a model of fatigue strength (σ_f)_sur considering multiple SI indexes was developed. Then, high-cycle fatigue tests were carried out on Inconel 718 samples with different SI characteristics, and the influence of ND-UVAFG process parameters on SI was analyzed. Based on SI indexes data, the (σ_f)_sur distribution in the grinding surface layer for ND-UVAFG Inconel 718 samples was determined using the developed model, and then the fatigue crack initiation (FCI) sites were further predicted. The predicted FCI sites corresponded well with the experimental results, thereby verifying this model. A strategy for improving the fatigue life was proposed in this work, which was to transfer the fatigue source from the machined surface to the bulk material by controlling the SI indexes. Finally, a critical condition of SI indexes that FCI sites appeared on the surface or in bulk material was given by fitting the predicted results. According to the critical condition, an SI field where FCI sites appeared in the bulk material could be obtained. In this field, the fatigue life of Inconel 718 samples could be improved by approximately 140%.

Multi-level programmable photonic integrated circuits (PICs) and optical metasurfaces have gained widespread attention in many fields, such as neuromorphic photonics, optical communications, and quantum information. In this paper, we propose pixelated programmable Si₃N₄ PICs with record-high 20-level intermediate states at 785 nm wavelength. Such flexibility in phase or amplitude modulation is achieved by a programmable Sb₂S₃ matrix, the footprint of whose elements can be as small as 1.2 µm, limited only by the optical diffraction limit of an in-house developed pulsed laser writing system. We believe our work lays the foundation for laser-writing ultra-high-level (20 levels and even more) programmable photonic systems and metasurfaces based on phase change materials, which could catalyze diverse applications such as programmable neuromorphic photonics, biosensing, optical computing, photonic quantum computing, and reconfigurable metasurfaces.

Biomimetic materials that use natural wisdom to solve practical problems are developing rapidly. The trend for systematic biomimicry is towards in-situ characterization of natural creatures with high spatial resolutions. Furthermore, rapid reconstruction of digital twin models with the same complex features as the prototype is indispensable. However, it faces bottlenecks and limits in fast characterization and fabrication, precise parameter optimization, geometric deviations control, and quality prediction. To solve these challenges, here, we demonstrate a state-of-the-art method taking advantage of micro-computed tomography and three-dimensional printing for the fast characterization of the pitcher plant Nepenthes x ventrata and fabrication of its biomimetic model to obtain a superior drainage controller with multiscale structures with precise surface morphology optimization and geometric deviation control. The film-rupture-based drainage dynamic and mechanisms are characterized by x-ray and high-speed videography, which determines the crucial structures for unique directional drainage. Then the optimized artificial pitchers are further developed into sustained drainage devices with novel applications, such as detection, reaction, and smoke control.

Synthetic vascular grafts suitable for small-diameter arteries (<6 mm) are in great need. However, there are still no commercially available small-diameter vascular grafts (SDVGs) in clinical practice due to thrombosis and stenosis after in vivo implantation. When designing SDVGs, many studies emphasized reendothelization but ignored the importance of reconstruction of the smooth muscle layer (SML). To facilitate rapid SML regeneration, a high-resolution 3D printing method was used to create a novel bilayer SDVG with structures and mechanical properties mimicking natural arteries. Bioinspired by the collagen alignment of SML, the inner layer of the grafts had larger pore sizes and high porosity to accelerate the infiltration of cells and their circumferential alignment, which could facilitate SML reconstruction for compliance restoration and spontaneous endothelialization. The outer layer was designed to induce fibroblast recruitment by low porosity and minor pore size and provide SDVG with sufficient mechanical strength. One month after implantation, the arteries regenerated by 3D-printed grafts exhibited better pulsatility than electrospun grafts, with a compliance (8.9%) approaching that of natural arteries (11.36%) and significantly higher than that of electrospun ones (1.9%). The 3D-printed vascular demonstrated a three-layer structure more closely resembling natural arteries while electrospun grafts showed incomplete endothelium and immature SML. Our study shows the importance of SML reconstruction during vascular graft regeneration and provides an effective strategy to reconstruct blood vessels through 3D-printed structures rapidly.

Bi-activated photonic materials are promising for various applications in high-capacity telecommunication, tunable laser, and advanced bioimaging and sensing. Although various Bi-doped material candidates have been explored, manufacturing of Bi heavily doped fiber with excellent optical activity remains a long-standing challenge. Herein, a novel viscosity evolutional behavior mediated strategy for manufacturing of Bi-doped active fiber with high dopant solubility is proposed. The intrinsic relation among the evolution of Bi, reaction temperature and viscosity of the glass system is established. Importantly, the effective avenue to prevent the undesired deactivation of Bi during fiber drawing by tuning the temperature dependent viscosity evolution is built. By applying the strategy, for the first time we demonstrate the success in fabrication of heavily doped Bi active fiber. Furthermore, the principal fiber amplifier device is constructed and broadband optical signal amplification is realized. Our findings indicate the effectiveness of the proposed temperature dependent viscosity mediated strategy for developing novel photonic active fiber, and they also demonstrate the great potential for application in the next-generation high-capacity telecommunication system.

Surface-enhanced Raman scattering (SERS) platform, which enables trace analyte detection, has important application prospects. By structuring/modifying the surface of the SERS substrate, analyte in highly diluted solutions can be concentrated into localized active areas for highly sensitive detection. However, subject to the difficulty of the fabrication process, it remains challenging to balance hot-spot construction and the concentration capacity of analyte simultaneously. Therefore, preparing SERS substrates with densely ordered hot spots and efficient concentration capacity is of great significance for highly sensitive detection. Herein, we propose an Ag and fluoroalkyl-modified hierarchical armour substrate (Ag/F-HA), which has a double-layer stacking design to combine analyte concentration with hotspot construction. The microarmour structure is fabricated by femtosecond-laser processing to serve as a superhydrophobic and low-adhesive surface to concentrate analyte, while the anodic aluminium oxide (AAO) template creates a nanopillar array serving as dense and ordered hot spots. Under the synergistic action of hot spots and analyte concentration, Ag/F-HA achieves a detection limit down to 10^-7 M doxorubicin (DOX) molecules with a RSD of 7.69%. Additionally, Ag/F-HA exhibits excellent robustness to resist external disturbances such as liquid splash or abrasion. Based on our strategy, SERS substrates with directional analyte concentrations are further explored by patterning microcone arrays with defects. This work opens a way to the realistic implementation of SERS in diverse scenarios.