SRC Proposals for SemiSynBio
Overview
Welcome to the SRC information page for submitting proposals to Semiconductor Synthetic Biology (SemiSynBio), a jointly funded program of Semiconductor Research Corporation (SRC) and the National Science Foundation (NSF). Below is a description of the goals of this program and the research topics of interest. See also: NSF information about SemiSynBio.
After becoming familiar with the description of desired research, if you wish to submit a proposal, first submit your proposal to NSF, and then follow these steps to submit the same proposal to SRC.
Semiconductor Synthetic Biology
About SemiSynBio
SemiSynBio is a joint effort of the National Science Foundation (NSF) and the Semiconductor Research Corporation (SRC). In order to be considered for funding under SemiSynBio, a proposal must be submitted to both NSF and SRC according to each organization's proposal and submission guidelines. It is expected that, at a minimum, the project summary, project description, and research budget, will be identical in the proposals submitted separately to NSF and SRC. Certain documentation/information specific to each organization is required. Please see: NSF information about SemiSynBio and SRC's SemiSynBio Proposal Submission Guide.
INTRODUCTION
Currently, semiconductor and information technologies are facing many challenges as CMOS/Moore’s Law approaches its physical limits, with no obvious replacement technologies in sight. There have been several recent breakthroughs in synthetic biology for demonstrating the suitability of biomolecules as carriers of stored digital data for memory applications. At the same time, the semiconductor industry has accumulated unique tools and experience in design and fabrication of complex hybrid systems, which incorporate unconventional materials, to meet future information processing needs. Semiconductor Synthetic Biology for Information Processing and Storage Technologies (SemiSynBio) seeks to explore synergies between synthetic biology and semiconductor technology. Today is likely to mark the beginning of a new technological boom to merge and exploit the two fields for information processing and storage capacity.
The goal of the proposed SemiSynBio research program will be to foster exploratory, multi-disciplinary, longer-term basic research leading to novel high-payoff solutions for the information technology industry based on recent progress in synthetic biology and the know-how of the semiconductor technology. It is also anticipated that molecular and cellular research in synthetic biology will benefit by leveraging semiconductor capabilities in design and fabrication of hybrid and complex material systems for extensive applications in biological and information processing technologies.
The community is ready to address the topic as a growing number of engineers, physicists, chemists, materials and computer scientists are turning to apply their expertise to synthetic biology, hybrid living cell- microelectronics systems, cell-inspired and cell-based physical and computational systems. This new direction complements the growing use of semiconductor microfabrication technologies in synthetic biology. Indicators of success will be a demonstration of a new generation of prototypical highly robust and scalable bio-computers inspired by mixed- signal electronic design.
The significance of the topic lies in part in the potential for a dramatic increase in memory storage capacity. For example, nucleic acids have an information storage density that is several orders of magnitude higher than any other known storage technology. In theory, a few kilograms of nucleic acid with proper encoding could meet all of the world’s data storage needs in a form that is chemically stable with retention for centuries, a feat that could not be currently supported by the projected silicon-based resources. Therefore, it is an opportune time to capitalize on the emerging field of synthetic biology integrated with semiconductor technology to enable the next generation of information processing and storage. SemiSynBio promotes fundamental interdisciplinary research at the interface of biology, engineering, physics, chemistry, material science, and computer science for information technology.
This program aims to seed and foster collaboration among the faculties in the biological, engineering, physics, chemistry, materials sciences, computer science, information science and the design automation disciplines to develop new cross-disciplinary curricula that integrate concepts, tools and methodology from biology, physics, semiconductor engineering and computer engineering. The role of this program is to stimulate non-traditional thinking about the issues facing the semiconductor industry in the following research areas:
- Advancing basic research by exploring new programmable models of computation, communication, and memory based on synthetic biology.
- Enriching the knowledge base and addressing foundational questions at the interface of biology and semiconductors.
- Promoting the frontier of research in design of new bio-nano hybrid devices based on sustainable materials, including carbon-based systems that test the physical size limit in transient electronics.
- Designing and fabricating hybrid semiconductor-biological microelectronic systems based on living cells for next-generation of storage and information processing functionalities.
- Integrating scaling-up and manufacturing technologies involving electronic and synthetic biology characterization instruments with CAD- like software tools.
Submitted proposals should address at least three of the five research areas (detailed below), and should comprehensively address the most aggressive goals within the chosen approach with an overarching goal of educating a new cadre of students that will meet the need of industries stemming from synthetic biology.
RESEARCH AREAS
- Advancing basic and fundamental research by exploring new programmable models of computation, communication, and memory based on synthetic biology.
Understanding principles of information processing in living cells could enable new generations of computing systems. Among the most promising characteristics of biological computing is the extremely low requirement for energy of operation, close to thermodynamic limits.
Another relevant characteristic of biological circuits is their physical size: although the progress of silicon technology has been extraordinary, sub-microscopic computers remains beyond our reach. Nature appears to have successfully addressed the sub-microscopic design challenge, and may suggest new solutions for future microsystems for information processing. Advances in the science of synthetic biology are beginning to suggest possible pathways for extending future semiconductor technologies. For example, by using nucleic acids, it might be possible to achieve storage densities that cannot be approached by the known semiconductor technologies. This topic encourages research ideas motivated by biological information processing and aiming at future highly functional, space-limited, digital and analog computing and semiconductor technologies with high information density and extremely low energy consumption. Research in this domain is expected to spur new ways in the area of alternative computing paradigm.
- Enriching the knowledge base and addressing foundational questions at the interface of biology and semiconductors.
It is becoming increasingly clear that information processing plays a central role in enabling the functionality of biological systems from the molecular to the organismal scale, and even to the ecological scale.
Semiconductor information processing is providing revolutionary tools and instrumentation for fundamental biological discovery and for its practical applications while increasingly sophisticated computational models and software strategies provide the logical connection between instrumentation, samples, and the data sets generated. Deriving the principles and rules that govern the formation, functioning, and evolution of simple and complex biological systems is still a challenge and sets new goals for how software engineering may bring fresh insights. This topic also seeks to devise new methodologies and design principles that embrace the complexity of multi-scaled electronic-biological systems integration. The scope includes theoretical foundations, design methodology and standards, and research targets aiming at the development of new engines for transformation and integration of synthesis artifacts, and effective methods for programmer interaction and feedback. This topic encourages research that can harness and accelerate the synergies among the three domains of biology, electronics, and software that will address the interface challenges between biology and semiconductors.
- Promoting the frontier of research in design of new bio-nano hybrid devices based on sustainable materials, including carbon- based systems that tests the physical size limit in transient electronics.
A new materials base is likely to be needed for future electronic hardware. While most of today’s electronics use silicon, this may not be a sustainable or optimal approach tomorrow, as billions of sensor nodes are realized as a part of the Internet-of-Things, many of which have short lives and are disposable. Novel materials systems that can be implemented in future electronic components and systems and can support sustainability through recycling and bio-degradability are of interest. It may also be possible to reuse and repurpose silicon as is done by microscopic diatoms and glass sponges. These organisms acquire Si from their environments and use it to build repeatable and complex structures. More study of such systems is also encouraged.
An electronic materials base will require new fabrication technologies that use synthetic biology to create “cellular factories.” Microorganisms can be programmed to produce a range of important chemicals and materials for semiconductor processes that have the desired chemical composition and morphology. An additional requirement is that the manufacturing of these materials, as well as the materials themselves, are engineered to be biologically benign. Living systems fabricate complex nanometer-scale structures with high yield and low energy utilization. For example, biological self-assembly occurs at a rate of ~1018 molecules per second (at biological growth rates, a 1Gb chip could be built in about 5 s), with energy utilization of ~10-17 J/molecule, which is 100x less than that of conventional subtractive manufacturing.
Combining these capabilities of living systems with synthetic nucleic/protein-based self-assembly offers transformative potential for revolutionizing the synthesis of complex electronic architectures.
- Designing and fabricating hybrid semiconductor-biological microelectronic systems based on living cells for next-generation of information processing functionalities.
The hybrid biology-semiconductor systems can be employed in a broad spectrum of critical applications with ground-breaking scientific, economic, and societal impacts. Leveraging the built-in or synthetically programmed cellular machineries and their interactions with semiconductor platforms can potentially offer unprecedented capabilities far beyond conventional electronics-only devices. Emerging hybrid biological-semiconductor platforms will leverage both natural/synthetic biological processes and semiconductor technologies. In such hybrid platforms, living cells and tissues can function as a “Biological Front-End” layer with the cellular biochemical processes serving as an organic interface to the external environment and performing synthesis, biological sensing, actuation, signal processing, and energy harvesting.
In parallel, the underlying semiconductor platforms can form a “Semiconductor Back-End” layer for information computation, control, communication, storage, and energy supply. If reliable two-way communication schemes, for both information and energy, are achieved between the “Biological Front-End” and “Semiconductor Back-End” with a high spatiotemporal resolution and massively parallel operations, one can expect a creation of a hybrid biotic-abiotic feedback system.
Advances in this field could stimulate developments of self-powered Intelligent Sensor Systems that integrate biological sensing and energy generation functions with inorganic information/computation capabilities to enable diverse new applications.
- Integrating scaling-up and manufacturing technologies involving electronic and synthetic biology characterization instruments with CAD-like software tools.
Currently, semiconductor technologies have directly enabled remarkable progress in sequencing, microscopy, and other types of instrumentation. However, synthetic biology is at an early-stage of engineering due to limited automation and no large-scale integration in the build to test phases of the design cycle. As instrumentation miniaturizes and the demand for high-throughput characterization increases, semiconductors and electronic assembly technologies will become better suited to continue to scale into the biological domain as essential platforms. New tools for characterization and metrology for hybrid bio-electronic systems are needed. The incorporation of these technologies will further require a step-change in the way that Software Design Automation (SDA) for Synthetic Biology will be approached. Synthetic Biology designs should be verified to be trustworthy and economical and thus requires breakthroughs in programming languages used in biology and formal verification techniques for large-scale biological engineering. While the first-generation synthetic biology has demonstrated many impressive proof-of-concept circuits, full-scale computer-aided design tools will be needed for reliable design of larger and more complex systems, such as cellular-scale models. One recent benchmark is ~104 biological design automation (BDA) designed equivalent “bits” (e.g. DNA base-pairs) versus ~109 EDA “bits” (e.g. binary switches on a chip). Leveraging advanced electronic design automation (EDA) tools and concepts for complex design could enable a radical increase in the complexity of biological design automation (BDA) capabilities. Currently, the biological design cycle is slow, expensive and laborious, and in most cases design is carried out empirically using a small number of parts; exper lution, an essential ingredient of the design cycle, is often not supplemented with predictive outcomes. Thus the development of EDA/BDA/SDA interface requires expert input from the three communities.
Guide for submitting your SemiSynBio proposal to SRC
0 Establish an SRC web account.
If you have not yet done so, sign up for a web user account now.
1 Request an SRC SemiSynBio proposal ID.
As early as possible, and well prior to the submission deadline, request your Proposal ID via email from the SRC proposal coordinator.
- Your SRC proposal ID and your NSF proposal ID will be different.
- You may request your SRC proposal ID before you submit your proposal to NSF.
Use the subject line "SRC Proposal ID (SemiSynBio)", and include this information in the email:
- Title of proposal (please match the title of your NSF-submitted proposal)
- University name (U.S. universities only)
- Principal Investigator's (PI's) university phone and email address
Check for an email response from SRC containing your SRC proposal ID.
2 Generate a cover page for your SRC proposal.
On the SRC proposal submission page, enter the SRC proposal ID and the email address of the Principal Investigator (PI). Then complete the form to generate an SRC proposal cover page using the following guidance.
- On the submission form, the contract start and end dates should be 04/01/2018 and 03/31/2021.
- When asked about related work previously receiving funding, answer “No” — we assume that related funding has been described in the NSF proposal.
- In response to the cost sharing question, answer “No.”
- For budget, enter the three-year and first-year totals from the NSF proposal submission.
When ready, print your SRC proposal cover page.
3 Prepare the SRC proposal PDF.
Collect signatures, then scan the signed proposal cover page. Generate a proposal PDF that uses the PDF of the proposal you submitted to NSF Fastlane and incorporates the SRC cover page (as the first page). Note: SRC will use the detailed budget information from the NSF proposal.
4 Upload the SRC proposal PDF.
Return to the SRC proposal submission page, resume the proposal submission process by entering the proposal ID and PI's email address, then upload the proposal PDF (with the SRC cover page on top).
