Microfluidics by Additive Manufacturing for Wearable Biosensors: A Review

Wearable devices are nowadays at the edge-front in both academic research as well as in industry, and several wearable devices have been already introduced in the market. One of the most recent advancements in wearable technologies for biosensing is in the area of the remote monitoring of human health by detection on-the-skin. However, almost all the wearable devices present in the market nowadays are still providing information not related to human ‘metabolites and/or disease’ biomarkers, excluding the well-known case of the continuous monitoring of glucose in diabetic patients. Moreover, even in this last case, the glycaemic level is acquired under-the-skin and not on-the-skin. On the other hand, it has been proven that human sweat is very rich in molecules and other biomarkers (e.g., ions), which makes sweat a quite interesting human liquid with regards to gathering medical information at the molecular level in a totally non-invasive manner. Of course, a proper collection of sweat as it is emerging on top of the skin is required to correctly convey such liquid to the molecular biosensors on board of the wearable system. Microfluidic systems have efficiently come to the aid of wearable sensors, in this case. These devices were originally built using methods such as photolithographic and chemical etching techniques with rigid materials. Nowadays, fabrication methods of microfluidic systems are moving towards three-dimensional (3D) printing methods. These methods overcome some of the limitations of the previous method, including expensiveness and non-flexibility. The 3D printing methods have a high speed and according to the application, can control the textures and mechanical properties of an object by using multiple materials in a cheaper way. Therefore, the aim of this paper is to review all the most recent advancements in the methods for 3D printing to fabricate wearable fluidics and provide a critical frame for the future developments of a wearable device for the remote monitoring of the human metabolism directly on-the-skin.

Structure-aware Multi-view 3D Reconstruction of Dislocations in TEM with Message Passing Neural Networks

Okan Altingövde, Pascal Fua, Gulnaz Ganeeva, Cécile Hébert, Anastasiia Mishchuk, Emadeddin Oveisi

Efficient analysis of the three-dimensional (3D) shape and distribution of curvilinear crystal defects, namely dislocations, is an open research topic in material science and computer vision. In order to determine the structural and opto-electrical characteristics of the material, accurate 3D reconstructions of dislocations are required. In its current state, an established way to obtain 3D information of dislocations is electron tomography which relies on acquiring dozens of images from tilted sample for wide range of angles. Although tomography yields sufficient results in many cases, it is manually demanding to acquire, register and process dozens of images. In previous works [1, 2], it is shown that a classical stereo reconstruction approach may be applied as an alternative in order to increase reconstruction throughput while providing good performance. A later work [3] employing modern data-driven computer vision models showed that this stereo approach can be largely automatized and be used in various imaging conditions. In this work, we further improve the performance and memory consumption of previous convolutional neural network (CNN) based stereo reconstruction approach and extend it to be applicable in cases where more than two images are available. Our proposed multi-view approach directly incorporates the structural prior of dislocations to the model"s architecture and estimates 3D line segments approximating 3D shape of dislocations. In its core, our method has two stages which are structural connectivity estimation and depth estimation. In first stage, we employ a CNN to estimate affinity of sampled image locations on dislocation cores. This affinity information is used in the later depth estimation stage to eliminate the depth discontinuities on dislocations (Figure1). Unlike previous deep data-driven method, our new approach uses structural knowledge to separate depth estimations of different dislocation segments and yields more accurate reconstructions. In Figure 2, an example affinity estimation is shown for 4 different image locations on the same dislocation. It may be seen that dislocation points that are connected by dislocation segment in 3D results in higher affinity. This information is crucial to connect 3D point estimations and obtain linear structures in 3D.

2021

Emerging Nanopatterning Methods based on MEMS Technology

Jürgen Brugger

The development of nanosystems and nano-devices demands for patterning methods in the nanoscale. To bring them to the market, there is a need for fast, low-cost nanopatterning methods. In addition, an increased flexibility is important for the engineering of multimaterial and multifunctional nano/micro-electro-mechanical systems (NEMS/MEMS), such as polymer-based electronic and sensor devices, 3D microfluidic systems, and bio-analytical systems. A series of alternative surface micro/nanopatterning methods based on MEMS technology are currently being developed, e.g. local fluidic dispensing and shadow-mask deposition (nanostencil lithography). These methods rely on locally adding material onto the substrate without the need for resist layers, exposure and etch steps. MEMS-based nanopatterning can be implemented in various manners: as scanning devices for the flexible, serial, writing of nanopatternings, as replication tools for the copying of an existing pattern, or as parallel scanning MEMS systems combining both, flexibility and increased aerial through-put. Figure 1 summarizes some existing methods that include MEMS tools. Nanostencil lithography is a resistless, single step patterning method based on direct, local deposition of material on an arbitrary surface through a solid-state membrane, e.g. a 200-nm thick silicon nitride (SiN) membrane. Although the method faces several challenges in terms of membrane fabrication at 100-nm scale, gap control, mechanical stability, aperture clogging, alignment for multi-layer patterning, etc. the technique has tremendous advantages for parallel processing. We have studied patterning by stencil lithography on various surfaces including CMOS chips. Figure 2 shows recent results of nanostencil for the patterning of CMOS wafer. Dispensing of liquid at the nanometer scale has high interest for addressing local functionalization of surfaces and development of nanobiosensors and nanobiochips. Atomic force based technology can be used to locally deposit small quantity of liquid. MEMS technology can be used to fabricate arrays of silicon micro-levers with integrated read-out (piezoresistive) and fluidics systems, so that the deposition can be performed in a controllable and precise way. Two approaches are being developed: modfication of conventional AFM cantilevers and development of dedicated devices.

2006

Advancing towards well-controlled full-wafer nanostencil lithography

Jürgen Brugger, Nao Takano, Marc Antonius Friedrich van den Boogaart

The endeavour to develop nanodevices demands for patterning methods in the nanoscale. To bring nanodevices to the market, there is a need for fast, low-cost replication nanopatterning methods. In addition, an increased flexibility of the nanopatterning methods is important for the engineering of multimaterial and multifunctional nano/micro-electro-mechanical systems (NEMS/MEMS), such as polymer-based electronic and sensor devices, 3D microfluidic systems, and bio-analytical systems. A series of alternative, complementary surface micro/nanopatterning methods are currently being developed, e.g. local printing of molecular layers (soft-lithography), local fluidic dispensing (NADIS), and shadow-mask deposition (nanostencil lithography). These methods rely on locally adding material onto the substrate without the need for resist layers and etching steps. Nanostencil lithography is a resistless, single step patterning method based on direct, local deposition of material on an arbitrary surface through a solid-state membrane, e.g. a 200-nm thick silicon nitride (SiN) membrane. We present two new stencil membrane geometries and associated MEMS processes that allow for advancing further towards a well-controlled full-wafer (100 mm) nanostencil process for reproducible, high-throughput, large-area nanopatterning of mesoscopic structures (10^9-10^3 m). In fact, the major challenges for well-controlled and reproducible nanostencil lithography are to control stress-induced membrane deformation, clogging of membrane apertures and the gap between stencil and substrate. To limit pattern deformation and blurring, i.e. reduced sharpness of edges and limited spatial detail, we have developed two schemes to incorporate in-situ, local stabilization structures in the stencil membranes. These stabilization structures are adaptable to the membrane apertures and they do not interfere with the material flux during deposition. The stabilized membranes show improved membrane stability (i.e. reduced out-of-plane deformation) up to 94%, resulting in an improved pattern definition of stencil-deposited structures. We have also systematically characterized and will present the clogging of membrane apertures as a function of their size and deposited material. Cu and Ti thin-film deposition through 500-nm thick SiN stencil membranes resulted in half of the film thickness (that was evaporated onto the membrane surface) deposited at the inner sides of the membrane apertures. The stabilized membranes are easier to clean with a reduced risk of damage, increasing the reusability of the stencils. Furthermore, the influence of the gap between stencil and substrate on the deposited structures was determined quantitatively. We have studied patterning by stencil lithography of metals (Al, Au, Bi, Cr, Ti, Cu) on various surfaces (Si, SiO2, SU-8, PDMS, PMMA, freestanding SiN cantilevers, curved surfaces, CMOS chips, and self-assembled monolayers (SAM)) for different applications (nanomechanical devices, (molecular) electronic devices, nanoscale Hall-sensor devices, 3D microfluidic systems).

2005