Versatile carbon-loaded shellac ink for disposable printed electronics

Emerging technologies such as smart packaging are shifting the requirements on electronic components, notably regarding service life, which counts in days instead of years. As a result, standard materials are often not adapted due to economic, environmental or manufacturing considerations. For instance, the use of metal conductive tracks in disposable electronics is a waste of valuable resources and their accumulation in landfills is an environmental concern. In this work, we report a conductive ink made of carbon particles dispersed in a solution of shellac. This natural and water-insoluble resin works as a binder, favourably replacing petroleum-derived polymers. The carbon particles provide electrical conductivity and act as a rheology modifier, creating a printable shear-thinning gel. The ink’s conductivity and sheet resistance are 1000 S m−1 and 15 Ω sq−1, respectively, and remain stable towards moisture. We show that the ink is compatible with several industry-relevant patterning methods such as screen-printing and robocasting, and demonstrate a minimum feature size of 200 μm. As a proof-of-concept, a resistor and a capacitor are printed and used as deformation and proximity sensors, respectively.

Simulation and Characterization of Nanoparticle Thermal Conductivity for a Microscale Selective Laser Sintering System

Additive Manufacturing (AM) technologies are often restricted by the minimum feature size of parts they can repeatably build. The microscale selective laser sintering (μ-SLS) process, which is capable of producing single micron resolution parts, addresses this issue directly. However, the unwanted dissipation of heat within the powder bed of a μ-SLS device during laser sintering is a primary source of error that limits the minimum feature size of the producible parts. A particle scale thermal model is needed to characterize the thermal properties of the nanoparticles undergoing sintering and allow for the prediction of heat affected zones (HAZ) and the improvement of final part quality. Thus, this paper presents a method for the determination of the effective thermal conductivity of metal nanoparticle beds in a microscale selective laser sintering process using finite element simulations in ANSYS. CAD models of nanoparticle groups at various timesteps during sintering are developed from Phase Field Modeling (PFM) output data, and steady state thermal simulations are performed on each group. The complete simulation framework developed in this work is adaptable to particle groups of variable sizes and geometric arrangements. Results from the thermal models are used to estimate the thermal conductivity of the copper nanoparticles as a function of sintering duration.

Broadband High-Efficiency Grating Couplers for Perfectly Vertical Fiber-to-Chip Coupling Enhanced by Fabry-Perot-like Cavity

We propose a broadband high-efficiency grating coupler for perfectly vertical fiber-to-chip coupling. The up-reflection is reduced, hence enhanced coupling efficiency is achieved with the help of a Fabry-Perot-like cavity composed of a silicon nitride reflector and the grating itself. With the theory of the Fabry-Perot cavity, the dimensional parameters of the coupler are investigated. With the optimized parameters, up-reflection in the C-band is reduced from 10.6% to 5%, resulting in an enhanced coupling efficiency of 80.3%, with a 1-dB bandwidth of 58 nm, which covers the entire C-band. The minimum feature size of the proposed structure is over 219 nm, which makes our design easy to fabricate through 248 nm deep-UV lithography, and lowers the fabrication cost. The proposed design has potential in efficient and fabrication-tolerant interfacing applications, between off-chip light sources and integrated chips that can be mass-produced.

Designing Self Supported SLM Structures via Topology Optimization

The potential of Additive Manufacturing (AM) is high, with a whole new set of manufactured parts with unseen complexity being offered. However, the process has limitations, and for the sake of economic competitiveness, these should also be considered. Therefore, a computational methodology, capable of including the referenced limitations and providing initial solid designs for Selective Laser Melting (SLM) is the subject of the present work. The combination of Topology Optimization (TO) with the simplified fabrication model is the selected methodology. Its formulation, implementation, and integration on the classic TO algorithm is briefly discussed, being capable of addressing the minimum feature size and the overhang constraint limitations. Moreover, the performance and numerical stability of the methodology is evaluated, and numerical variables, such as the accuracy of structural equilibrium equations and the material interpolation model, are considered. A comparative study between these variables is presented. The paper then proposes an enhanced version of the selected methodology, with a better convergence towards a discrete solution.

Nanoparticle Sintering Model: Simulation and Calibration Against Experimental Data

One of the limitations of commercially available metal additive manufacturing (AM) processes is the minimum feature size most processes can achieve. A proposed solution to bridge this gap is microscale selective laser sintering (μ-SLS). The advent of this process creates a need for models which are able to predict the structural properties of sintered parts. While there are currently a number of good SLS models, the majority of these models predict sintering as a melting process which is accurate for microparticles. However, when particles tend to the nanoscale, sintering becomes a diffusion process dominated by grain boundary and surface diffusion between particles. As such, this paper presents an approach to model sintering by tracking the diffusion between nanoparticles on a bed scale. Phase field modeling (PFM) is used in this study to track the evolution of particles undergoing sintering. Changes in relative density are then calculated from the results of the PFM simulations. These results are compared to experimental data obtained from furnace heating done on dried copper nanoparticle inks, and the simulation constants are calibrated to match physical properties.

Nanoparticle Sintering Model, Simulation and Calibration Against Experimental Data

One of the limitations of commercially available metal Additive Manufacturing (AM) processes is the minimum feature size most processes can achieve. A proposed solution to bridge this gap is microscale selective laser sintering (μ-SLS). The advent of this process creates a need for models which are able to predict the structural properties of sintered parts. While there are currently a number of good SLS models, the majority of these models predict sintering as a melting process, which is accurate for microparticles. However, when particles tend to the nanoscale, sintering becomes a diffusion process dominated by grain boundary and surface diffusion between particles. As such, this paper presents an approach to model sintering by tracking the diffusion between nanoparticles on a bed scale. Phase Field Modeling (PFM) is used in this study to track the evolution of particles undergoing sintering. Part properties such as relative density, porosity, and shrinkage are then calculated from the results of the PFM simulations. These results are compared to experimental data gotten from a Thermogravimetric Analysis done on dried copper nanoparticle inks, and the simulation constants are calibrated to match physical properties.

A process for estimating minimum feature size in selective laser sintering

Purpose Manufacturer specifications for the resolution of an additive manufacturing (AM) machine can be ten times smaller (more optimistic) than the actual size of manufacturable features. Existing methods used to establish a manufacturable design rule-set are conservative piecewise-constant approximations. This paper aims to evaluate the effectiveness of a first-order model for producing improved design rule-sets for feature manufacturability, accounting for process variation. Design/methodology/approach A framework is presented which uses an interpolation method and a statistical model to estimate the minimum size for a wide range of features from a set of iterative experiments. Findings For an SLS process, using this approach improves the accuracy and reliability of minimum feature size estimates for a wider variety of features than assessed by most existing test artifacts. Research limitations/implications More research is needed to provide better interpolation models, broaden applicability and account for additional geometric and process parameters which significantly impact the results. This research focuses on manufacturability and does not address dimensional accuracy of the features produced. Practical implications An application to the design of thin channels in a prosthetic hand shows the utility of the results in a real-world scenario. Originality/value This study is among the first to investigate statistical variation of “pass/fail” features in AM process characterization, propose a means of estimating minimum feature sizes for shapes not directly tested and incorporate a more efficient iterative experimental protocol.

LIFT OFF PROCESS ON FABRICATION OF CARBON MONOXIDE (CO) GAS SENSOR DEVICES

<p>This paper discuss the design and fabrication of microdevice to be used as platform for CO (Carbon monoxide) gas sensor based on tin dioxide (SnO₂). The device has been designed on silicon substrate with an active area of 3x3 mm², and it is consist of bonding pad, heater, electrode, and temperature sensor components. The minimum feature size used is 50 microns, as allowed by the capability of photolithographic process. The formation of microdevice structure was carried out by lift-off technique on platinum (Pt) layer, which was deposited by DC sputtering with aluminum (Al) as sacrificial layer. The overall chip dimension is 5x5 mm². The measurement that was conducted to study the characteristic of resistance asfunction of temperature has shown that the heater and temperature sensor elements could work as expected, in which their resistances change linearly as the temperature of the substrate increase by 20 – 200 °C. The resistance values of the heater increase 500 – 1000 ohm. Meanwhile, the resistance increasing for temperatur sensor is between 100 – 300 ohm. </p>

LIFT OFF PROCESS ON FABRICATION OF CARBON MONOXIDE (CO) GAS SENSOR DEVICES

<p>This paper discuss the design and fabrication of microdevice to be used as platform for CO (Carbon monoxide) gas sensor based on tin dioxide (SnO₂). The device has been designed on silicon substrate with an active area of 3x3 mm², and it is consist of bonding pad, heater, electrode, and temperature sensor components. The minimum feature size used is 50 microns, as allowed by the capability of photolithographic process. The formation of microdevice structure was carried out by lift-off technique on platinum (Pt) layer, which was deposited by DC sputtering with aluminum (Al) as sacrificial layer. The overall chip dimension is 5x5 mm². The measurement that was conducted to study the characteristic of resistance asfunction of temperature has shown that the heater and temperature sensor elements could work as expected, in which their resistances change linearly as the temperature of the substrate increase by 20 – 200 °C. The resistance values of the heater increase 500 – 1000 ohm. Meanwhile, the resistance increasing for temperatur sensor is between 100 – 300 ohm. </p>