And, although the scientific community now take the existence of atoms and molecules for granted, I think the early Avogadros of chemistry would have been especially gratified by the recent work at IBM’s research facility in Zurich to use atomic force microscopy to actually see molecules of pentacene (five fused aromatic 6-carbon rings, pictured below)

The results are detailed both on IBM’s press page as well as in the Aug 28 issue of Science. But, in graphical terms, this is the scientific community’s current best picture of pentacene:

Amazing isn’t it? More of the technical details are presented in the video IBM put together in conjunction with the press release (below), but in a nutshell, atomic force microscopy uses a well-defined atomic tip to “feel” out the electronic surface of a molecule. The ability to do this and even be able to resolve the respective hydrogen atoms is a testament to IBM’s ability to put together an incredibly stable (both to mechanical and thermal fluctuations) and precise setup.

From IBM’s perspective, this breakthrough allows them to continue to push ahead on the advanced nanotechnology and semiconductor research which they depend on to churn out next-generation electronics, but for the scientific community, these advances could result not only in better atomic force microscopy experimental techniques, but potentially also a new way to understand and study the chemical reactions and structures which have such great influence over our lives.

Publication: Science 28 August 2009: Vol. 325. no. 5944, pp. 1110 – 1114; DOI: 10.1126/science.1176210

(Image credit – Pentacene chemical diagram) (Image credit – AFM picture)

The interesting thing about this particular problem is, unlike with games of Go and Chess which have clearly defined rules and discrete moves/outcomes, playing a game of Jeopardy requires an understanding of semantics which has traditionally been relegated to the human domain.

Admittedly, there are natural language processing solutions out there. But at the end of the day, we’re a long way off from the computers displayed in Star Trek which can:

• Understand spoken words – This is a very challenging problem. How do you instruct a computer to not just comprehend words, but comprehend actual meaning to those words (semantics). The ability to understand that the “can” in “I can do it” is very different from the “can” in “soda can”, or that “being on pins and needles” is just an expression, or to even understand when a sentence is a question versus a statement are very deep problems. But this is only the beginning of Watson’s challenges, for Watson must also be able to…
• Search a massive database for relevant information – Merely searching a database for a list of possible results is a tractable problem that many database/search engines have already solved (e.g. searching for “Indian economy” on Google’s search engine). Searching a large database to find a particular answer behind the reams of data is much harder (e.g. understanding that “Economic Output” can be measured by a country’s GDP).
• Understand the relevant information – Just as it’s harder to understand Quantum Theory than it is to merely read the papers, IBM’s Watson must be able to parse the information that it’s found from its database. For instance, if asked to compare India’s economic output to its neighbors, a computer must not only understand that economic output is GDP, it must also understand what “neighbors” means in the context of India, understand that GDP may be “real” or “nominal” and may need to be adjusted by currency, and understand what it means to “compare” GDP’s.
• Formulate a response – This is related to the first ask, but is more challenging. Just as its harder to memorize the Bible than it is to recognize specific passages, IBM’s Watson must do more than just recognize/understand words – it must be able to create its own sentences which use the relevant information and understanding its developed.

The task is challenging, but not impossible. Already, researchers have demonstrated computers which have been able to do the scientific method (hypothesize –> experiment/test –> analyze –> formulate new hypotheses) all on their own. Granted, the scientific problem explored was more systematic in nature (and had a more well-defined solution set than a game of Jeopardy) as it was focused on finding missing pieces in metabolic networks, but the fact that a computer was capable of performing basic high level logic is very promising for fields of research (although threatening to lab techs and uncreative grad students everywhere) which were formerly intractable due to their scope (e.g. mapping out the human proteome or transcriptome).

“The essence of making decisions is recognizing patterns in vast amounts of data, sorting through choices and options, and responding quickly and accurately,” said Samuel J. Palmisano, IBM Chairman, President and Chief Executive Officer. “Watson is a compelling example of how the planet—companies, industries, cities—is becoming smarter. With advanced computing power and deep analytics, we can infuse business and societal systems with intelligence. This project is the latest example of IBM’s longstanding commitment to fundamental research and to overcoming ‘grand challenges’ in science and technology.”

Although I don’t know how well Watson would fare against Ken Jennings, Watson’s completion would be a landmark in artificial intelligence. It’ll be interesting to see if IBM’s Watson does as well as IBM promises. Although I don’t know how well Watson would fare against Ken Jennings, Watson’s completion would be a landmark in artificial intelligence and computer science. Watson may pave the way to an age where computers can actively aid doctors diagnose patients or help business executives make financial decisions (which is probably what IBM is going for here).

(Image Credit) (Video)

From IBM’s abstract:

We have combined ultrasensitive magnetic resonance force microscopy (MRFM) with 3D image reconstruction to achieve magnetic resonance imaging (MRI) with resolution <10 nm. The image reconstruction converts measured magnetic force data into a 3D map of nuclear spin density, taking advantage of the unique characteristics of the “resonant slice” that is projected outward from a nanoscale magnetic tip. The basic principles are demonstrated by imaging the 1H spin density within individual tobacco mosaic virus particles sitting on a nanometer-thick layer of adsorbed hydrocarbons.

While we have seen other exciting developments in the MR industry as well as the imaging industry, this breakthrough is especially revolutionary because of how much it influences the scientific community. If IBM’s new microscope is as good as advertised, we will be able to produce three dimensional images of viruses, view the structure and interactions of proteins, and study the physical nature of certain chemical reactions, all while evading the disadvantages which plague electron microscopy. The benefits of understanding how things work at a molecular level can lead to better modeling, better drugs, smaller chips, and maybe even better detection mediums for cancer.

Here’s a video describing the technique: