Fuel Cells – Now for Portable Devices

Fuel Cells were originally conceived as early as 1839 and derive their electrochemical fuel and oxidant externally as opposed to a battery which contains the fuel and requires recharging. This primer on fuel cells provides a simple overview. Achieving sufficient power levels from a fuel cell requires “stacking” multiple units.

In the past fuel cell advocates focused on large stationary applications (home, commercial buildings, etc.) due to the size and weight of the fuel cell. Today, portable applications are targeted. There are two types of fuel cells – proton exchange membrane, and direct methanol. In the proton exchange membrane method, a thin membrane forms a barrier that contains the electrical flow but provides excess protons to support charge transfer. In the Direct Methanol method, methanol is fed to the anode as fuel which simplifies the overall design of the fuel cell.

The key issue in bringing fuel cells to the portable market is cost. While the technology is available, the price of a fuel cell for a handheld device must be competitive to batteries. A number of companies are starting to achieve that price point.

Ultracell using a reformed methanol system offers a portable fuel cell that can power a laptop for several days at 25W. Called the XX25, they recently received funding from the US Army CERDEC program. The XX25 is 75% lighter than comparable batteries.

MTI MicroFuel Cells now sells a Direct Methanol Fuel cell to replace Lithium-ion batteries increasing device usage times by 2x to 10x.

Medis Technologies uses a special blend of chemicals including borohydride to achieve a longer lasting fuel cell.

This article indicates it won’t be too long before fuel cells are incorporated into portable devices rather than simply powering them.

Computer vendors are also starting to implement fuel cells in their laptops. Panasonic showed a laptop powered by a fuel cell at the CES show earlier this year.

Fuel cells will be slightly different from batteries in their usage. With a rechargeable battery, one plugs the battery into a recharger and then waits. With portable fuel cells, one will buy replacement cartridges (containing the fuel) and plugging it in without waiting for recharging as with batteries. Given this method of operation, fuel cells will compete with rechargeable batteries and not use-once batteries since the cost is much lower.

Other issues remain with portable fuel cells. The methanol fuel inside the fuel cell is flammable which exposes the user to some risk of burn and taking flammable substances on board an aircraft is also problematic. Some predict fuel cells will perform as a battery backup system rather than the primary electrical source for portable devices. This technology isn’t coming too soon – my laptop battery is about to run out.

Best regards,
Hall T.

Graphical User Interfaces—Semanticons Anyone?

In my last post about graphical user interfaces, the state of the art was moving into 3-D representations with the goal of making more realistic interfaces.

Technology Research News ran an article in December about the use of photos for making files and folders more meaningful. Northwestern developed a system called Semanticons that examines the contents of a file, and generates a set of keywords. It then does a lookup on images associated with those keywords and creates a composite image that represents the files’ contents.

Imagine a LabVIEW program in which the icons used a similar concept to create a visual cue indicating the contents of a user created virtual instrument. The “semanticon” could indicate the icon’s functionality (i.e. acquiring data, analyzing data, converting data, or displaying data). Or it could be used to indicate the virtual instruments position in the hierarchy (i.e. primitive, mid-level, or higher-level icon). So for the LabVIEW community I ask – Semanticons anyone?

GUIs have come a long way in the last 25 years. For a walk down memory lane check out this timeline. In looking forward, Gartner predicts that the current GUI standards will remain in place until the year 2010, at which point it will shift to a new generation driven by the emergence of handheld computing, and a shift in users from early adopters to more mainstream users.

In this MIT paper the authors blur the distinction between input devices (keyboard and mouse) and output devices (monitors and touch screens) by creating a new concept called “tangible user interfaces.” Drawing inspiration from the abacus which has no input or output distinction but only a physical representation, the authors contend the next generation of GUIs will be tangible objects imbued with computational control. At the Siggraph 2006 conference the authors presented this concept as “Tangibles at Play” in which they shift the graphical representation from a screen to a set of physical objects.

Other techniques for working with graphical user interfaces involve the systems’ ability to recognize the user’s gesture or motion. Gesture recognition uses a camera to view the user’s hand and converts the position and movement into commands for the computer. MIT created the “Conductor’s Jacket” controlled by LabVIEW. The system converts a person’s movement into music by connecting feeding signals through a MIDI interface into a music synthesizer.

Another example of gesture recognition is multi-touch by Jeff Han’s team at NYU which senses the position and movement of the users fingers and reacts accordingly. In the associated video you can see how the screen reacts to the pressure and touch from multiple points which are far beyond the one-touch screens we use today.

It seems clear that graphical user interfaces are going to shift not just to 3-D representations on the screen but will shift to the real world of 3D with the screen disappearing altogether.

Best regards,
Hall T.

Bioinformatics—Leveraging the Power of FPGAs

In my post on January 23, of this year regarding the Top 12 Hot Technologies to watch, I listed Bioinformatics. After a recent travel to the Bay Area, I found bioinformatics is still a hot topic with growing interest. The number of databases continues to grow. In the past scientists worked with gene expression data, gene sequence data, or proteomic data. Today, some are starting to ask that all three be combined into one analysis so they can see the total picture.

In looking into the bioinformatics area, I was surprised by the lack of standards. There is a great deal of homebrew software. BLAST (Basic Local Alignment Search Tool) and SAGE (Serial Analysis of Gene Expression are about the only standards available. BLAST takes two gene sequences (i.e. string sequence 1 -- ATTTACCTGGT and string sequence 2 --ATTTAGGTCCT) and compares them to see if they are the same or similar. SAGE analyzes gene expression patterns with digital analysis. After that, a host of small company niche players and university developed tools comprise the landscape. The reason for this is the nature of government funding. A number of companies invested heavily into bioinformatics tools and databases only to see the US Government come along and provide similar tools at little or no charge. This wiped out the market for developing tools and opened the door for a host of custom-developed software.

Most university-developed software tools gain little following outside the lab where it is developed and without a revenue stream, there’s little incentive to provide support. The one exception to this is MEGA (Molecular Evolutionary Genetics Analysis) which performs gene sequencing and alignment and web-based data mining. Developed by Dr. Sudhir Kumar of Arizona State University, the software has over 50,000 downloads making it one of the more popular tools for bioinformatics research.

FPGA’s are increasingly used in gene sequencing because it speeds up the pattern matching algorithm by breaking the pattern into sub-strings and matching on each part simultaneously.

A number of companies develop FPGA based solutions for bioinformatics work including Impulse, Timelogic, and Mitrion based in Los Angeles who is developing a BLAST application to run on it’s FPGA-based Virtual Processor. They took the open source version of NCBI’s BLAST algorithm and rewrote portions of it to run in C-code on their processor. They claim 10-100 times performance improvement. This seems to be a common method – take standard, open source algorithms and modify them to work on an FPGA.

Xilinx, the leading vendor of FPGA technology, offers this paper on an FPGA-architecture.

I believe we’ll FPGA’s become more common in bioinformatics applications.

Best regards,
Hall T.