Biomedical Engineering Reference
In-Depth Information
microfluidic platform [14-18]. Therefore, system complexity and integration
levels are likely to increase as chips are designed and manufactured for
emerging applications. Time to market and fault tolerance are also expected
to emerge as design considerations. Therefore, there is a need to deliver the
same level of design automation support to the biochip designers and users
that the semiconductor industry takes for granted.
As in the case of integrated circuits (ICs), an increase in the density and area
of microfluidics-based biochips will also lead to high defect densities, thereby
reducing yield, especially for newer technologies and manufacturing pro-
cess. However, dependability is an important system attribute for biochips.
It is essential for safety-critical applications such as point-of-care diagnostics,
health assessment and screening for infectious diseases, air-quality moni-
toring, and food-safety tests, as well as for pharmacological procedures for
drug design and discovery that require high precision levels. Therefore, these
chips must be tested adequately not only after fabrication but also continu-
ously during in-field operation. Due to the underlying mixed-technology and
multiple-energy domains, microfluidic biochips exhibit unique failure mech-
anisms and defects. In fact, the ITRS 2003 document recognized the need for
new test methods for heterogeneous device technologies that underlie micro-
electromechanical systems and sensors, and highlighted it as one of the five
difficult test challenges beyond 2009 [19].
The increase in the system complexity and integration levels poses addi-
tional challenges for electrode addressing and system control. Most prior work
on biochips computer-aided design (CAD) has assumed a direct-addressing
scheme, where each electrode is connected to a dedicated control pin; it can,
therefore, be activated independently. This method provides the maximum
freedom for droplet manipulation, but it requires an excessive number of
control pins. For example, a total of 10
4
pins are needed to independently
control the electrodes in a 100 × 100 array. Multilayer electrical connection
structures and wire-routing solutions are complicated by the large number
of independent control pins in such arrays. Product cost, however, is a major
marketability driver due to the one-time-use (disposable) nature of most
emerging devices. Thus, the design of pin-constrained digital microfluidic
arrays is of considerable importance for the emerging marketplace.
Some of the preceding issues, especially those related to synthesis and
testing, have been addressed in [20], which presented the first design auto-
mation framework for digital microfluidics. A number of integrated design
automation tools were presented in [20] for chip design and for the chip user.
These tools target design optimization, ease of use, as well as chip testing
and system maintenance, thereby allowing biochip users to focus on tar-
get applications and assay adaptation. However, the design methods in [20]
are often based on unrealistic assumptions. Many practical issues, such as
physical and technology-related constraints, the nature of manufacturing
defects, and fabrication cost, are not taken into account. As a result, the chip
designs resulting from these methods are often impractical. For example, the
