Versatile and Automated 3D Polydimethylsiloxane (PDMS) Patterning for Large-Scale Fabrication of Organ-on-Chip (OOC) Components

We present a reproducible process to directly pattern 3-Dimensional (3D) polydimethylsiloxane (PDMS) structures for Organ-on-Chips (OOC) via automated molding. The presented process employs a commercially available system from IC packaging improving the fabrication process for microfluidic channels and thin membranes, which are components frequently used in OOCs. The process removes the manual steps used previously in the fabrication of microfluidic channels and improves the control over the thickness of the PDMS layers. The process was also employed to fabricate and pattern thin PDMS membranes on silicon wafers, without the use of lithography and etching steps and in combination with 3D structures. The use of foil assisted molding techniques presented in this work is an important step toward the large-scale manufacturing of OOCs.

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Integration of lateral porous silicon membranes into planar microfluidics

Lab on a Chip ◽

10.1039/c4lc01094a ◽

2015 ◽

Vol 15 (3) ◽

pp. 833-838 ◽

Cited By ~ 15

Author(s):

Thierry Leïchlé ◽

David Bourrier

Keyword(s):

Porous Silicon ◽

Fabrication Process ◽

Microfluidic Channels ◽

Dead End ◽

Silicon Membranes ◽

On Chip ◽

Mesoporous Membranes

A unique fabrication process was developed to integrate lateral porous silicon membranes into planar microfluidic channels. These mesoporous membranes were demonstrated to be suitable for on-chip dead-end microfiltration.

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A MEMS Thermal Biosensor for Metabolite Measurements

Microelectromechanical Systems ◽

10.1115/imece2005-79614 ◽

2005 ◽

Author(s):

Li Wang ◽

Qiao Lin

Keyword(s):

Flow Rate ◽

Flow Injection ◽

Temperature Sensor ◽

Metabolite Concentration ◽

Microfluidic Channels ◽

Enzymatic Reactions ◽

Thin Membranes ◽

Flow Through ◽

On Chip ◽

Heat Released

We present a MEMS differential thermal biosensor integrated with microfluidics for metabolite concentration measurements either in flow-injection or flow-through modes. The biosensor consists of two identical freestanding polymer thin membranes, resistive on-chip heaters, and a metal thermoelectric differential temperature sensor between the two membranes. Integrated with polymer microfluidic channels and chambers, the biosensor allows efficient handling and measurements of small volumes (~1 μl) of liquid samples. Calibrated with on-chip resistive heaters, the biosensor shows a sensitivity of 1.2 V/W and time constant of 0.58 s. Enzyme-functionalized beads are packed in the chambers and interacted with metabolite solutions. The heat released from the enzymatic reactions is detected by the temperature sensor and used to measure the metabolite concentration. The biosensor demonstrated a glucose concentration resolution of 0.12 mM for flow-injection mode, and 0.48 mM for flow-through mode with a flow rate of 0.5 ml/h. It is found that there exists an optimal flow rate that corresponds to the maximum thermopile output voltage when the biosensor works in the flow-through mode.

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Fast and Cycle-Accurate Emulation of Large-Scale Networks-on-Chip Using a Single FPGA

ACM Transactions on Reconfigurable Technology and Systems ◽

10.1145/3151758 ◽

2017 ◽

Vol 10 (4) ◽

pp. 1-27 ◽

Cited By ~ 4

Author(s):

Thiem Van Chu ◽

Shimpei Sato ◽

Kenji Kise

Keyword(s):

Large Scale ◽

Networks On Chip ◽

On Chip ◽

Large Scale Networks

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Nanolaser-based emulators of spin Hamiltonians

Nanophotonics ◽

10.1515/nanoph-2020-0230 ◽

2020 ◽

Vol 9 (13) ◽

pp. 4193-4198 ◽

Cited By ~ 2

Author(s):

Midya Parto ◽

William E. Hayenga ◽

Alireza Marandi ◽

Demetrios N. Christodoulides ◽

Mercedeh Khajavikhan

Keyword(s):

Large Scale ◽

Optimization Problems ◽

Exchange Interactions ◽

Np Hard ◽

Spin Models ◽

Geometric Frustration ◽

Spin Hamiltonians ◽

Hard Problems ◽

On Chip ◽

Classical Spin Models

AbstractFinding the solution to a large category of optimization problems, known as the NP-hard class, requires an exponentially increasing solution time using conventional computers. Lately, there has been intense efforts to develop alternative computational methods capable of addressing such tasks. In this regard, spin Hamiltonians, which originally arose in describing exchange interactions in magnetic materials, have recently been pursued as a powerful computational tool. Along these lines, it has been shown that solving NP-hard problems can be effectively mapped into finding the ground state of certain types of classical spin models. Here, we show that arrays of metallic nanolasers provide an ultra-compact, on-chip platform capable of implementing spin models, including the classical Ising and XY Hamiltonians. Various regimes of behavior including ferromagnetic, antiferromagnetic, as well as geometric frustration are observed in these structures. Our work paves the way towards nanoscale spin-emulators that enable efficient modeling of large-scale complex networks.

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Simba

Communications of the ACM ◽

10.1145/3460227 ◽

2021 ◽

Vol 64 (6) ◽

pp. 107-116

Author(s):

Yakun Sophia Shao ◽

Jason Cemons ◽

Rangharajan Venkatesan ◽

Brian Zimmer ◽

Matthew Fojtik ◽

...

Keyword(s):

Deep Learning ◽

Large Scale ◽

Data Locality ◽

Coarse Grained ◽

Batch Size ◽

Peak Performance ◽

Large Scale Systems ◽

High Area ◽

On Chip ◽

And Storage

Package-level integration using multi-chip-modules (MCMs) is a promising approach for building large-scale systems. Compared to a large monolithic die, an MCM combines many smaller chiplets into a larger system, substantially reducing fabrication and design costs. Current MCMs typically only contain a handful of coarse-grained large chiplets due to the high area, performance, and energy overheads associated with inter-chiplet communication. This work investigates and quantifies the costs and benefits of using MCMs with finegrained chiplets for deep learning inference, an application domain with large compute and on-chip storage requirements. To evaluate the approach, we architected, implemented, fabricated, and tested Simba, a 36-chiplet prototype MCM system for deep-learning inference. Each chiplet achieves 4 TOPS peak performance, and the 36-chiplet MCM package achieves up to 128 TOPS and up to 6.1 TOPS/W. The MCM is configurable to support a flexible mapping of DNN layers to the distributed compute and storage units. To mitigate inter-chiplet communication overheads, we introduce three tiling optimizations that improve data locality. These optimizations achieve up to 16% speedup compared to the baseline layer mapping. Our evaluation shows that Simba can process 1988 images/s running ResNet-50 with a batch size of one, delivering an inference latency of 0.50 ms.

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Design Methodology of Passive In-Line Relays for Molecular Communication in Flow-Induced Microfluidic Channel

Biosensors ◽

10.3390/bios11030065 ◽

2021 ◽

Vol 11 (3) ◽

pp. 65

Author(s):

Puneet Manocha ◽

Gitanjali Chandwani

Keyword(s):

Communication System ◽

Communication Systems ◽

Microfluidic Channel ◽

Microfluidic Channels ◽

Molecular Communication ◽

External Energy ◽

Lab On Chip ◽

Molecular Communication Systems ◽

Macro Scale ◽

On Chip

Molecular communication is a bioinspired communication that enables macro-scale, micro-scale and nano-scale devices to communicate with each other. The molecular communication system is prone to severe signal attenuation, dispersion and delay, which leads to performance degradation as the distance between two communicating devices increases. To mitigate these challenges, relays are used to establish reliable communication in microfluidic channels. Relay assisted molecular communication systems can also enable interconnection among various entities of the lab-on-chip for sharing information. Various relaying schemes have been proposed for reliable molecular communication systems, most of which lack practical feasibility. Thus, it is essential to design and develop relays that can be practically incorporated into the microfluidic channel. This paper presents a novel design of passive in-line relay for molecular communication system that can be easily embedded in the microfluidic channel and operate without external energy. Results show that geometric modification in the microfluidic channel can act as a relay and restore the degraded signal up-to 28%.

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Silicon-Quartz Microcapillary Opto-Fluidic Platform Obtained by CMOS-Compatible Die to Wafer 200 mm Dual Bonding Process

Proceedings ◽

10.3390/proceedings2131018 ◽

2018 ◽

Vol 2 (13) ◽

pp. 1018

Author(s):

Giuseppe Fiorentino ◽

Ben Jones ◽

Sophie Roth ◽

Edith Grac ◽

Murali Jayapala ◽

...

Keyword(s):

Adhesive Bonding ◽

System Analysis ◽

Quartz Substrate ◽

Microfluidic System ◽

Bonding Process ◽

Microfluidic Channels ◽

Fully Integrated ◽

Lab On Chip ◽

Human Blood Cells ◽

On Chip

A composite, capillary-driven microfluidic system suitable for transmitted light microscopy of cells (e.g., red and white human blood cells) is fabricated and demonstrated. The microfluidic system consists of a microchannels network fabricated in a photo-patternable adhesive polymer on a quartz substrate, which, by means of adhesive bonding, is then connected to a silicon microfluidic die (for processing of the biological sample) and quartz die (to form the imaging chamber). The entire bonding process makes use of a very low temperature budget (200 °C). In this demonstrator, the silicon die consists of microfluidic channels with transition structures to allow conveyance of fluid utilizing capillary forces from the polymer channels to the silicon channels and back to the polymer channels. Compared to existing devices, this fully integrated platform combines on the same substrate silicon microfluidic capabilities with optical system analysis, representing a portable and versatile lab-on-chip device.

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