Future Workshops

The following workshops have been approved by the Science Steering Committee. Their precise scheduling will depend on funding availability for FY 2000 and FY 2001.

1. New Probes of Complex Adaptive Matter: May 1 - May 3, 2000

David Awschalom, UCSB

Today the frontiers of materials research are being defined by extensions beyond the traditional disciplines of physics, metallurgy, chemistry and biology, into new regimes that carve strongly across these areas. In recent years there have been remarkable advances in the synthesis, characterization and modeling of new electronic, magnetic, and optical materials which have revealed complex structure with important functional properties over multiple length scales ranging from the atomic to the macroscopic level. Moreover, experimental and theoretical efforts have shown that these properties evolve within time scales spanning femtoseconds through microseconds to hours and beyond. In response, research and development in materials sciences is currently moving beyond solving difficult problems in deliberately idealized systems -- homogeneous, three dimensional materials with simple unit cells and linear responses -- towards attempts to probe and ultimately control these spatial and temporal complexities for the stringent demands of technology. This research is driven by systematic studies of complex materials in order to unravel the role of reduced dimensionality, complex unit cells, disorder and inhomogeneity, active interfaces, strongly nonequilibrium conditions, and nonlinear, nonadiabatic responses in determining their physical behavior. This combination of difficult circumstances is challenging our conventional wisdom, inspiring new conceptual frameworks and themes, and fueling the development of new research techniques. We are beginning to acquire the basic skills for investigating entangled phenomena -- for example, local competitions between multiple states and interactions resulting in collective behavior, hierarchical landscapes, frustration, and glassy responses; or feedbacks between local and global patterns resulting in extreme sensitivities to small variations in internal conditions, proximities to phase transformations, or external stimuli.

The complexities faced in materials research are frequently due to coupling of structural and electronic degrees of freedom over many scales. This results in intimate relationships between structural, magnetic and optical properties, which are increasingly utilized for new technologies generating applications in sectors from communication to sensors to electrooptics to magnetic recording. The consequences of couplings between spin, charge and lattice degrees of freedom are apparent in both organic and inorganic materials. Indeed, even opportunities for hybrid organic-inorganic materials and multifunctional designs are now emerging in the literature. Many of these strategies are evident in biological materials and are inspiring exciting new directions in soft and biomimetic materials, in materials design and synthesis starting from the molecular level.


2. Physical Studies of Biological Systems: Techniques

Organizers: *David Eisenberg (UCLA) Jill Trewhella (Los Alamos), Feri Mezei (Los Alamos) and *Kurt Wuttrich (Zurich)

*To be confirmed

Biological systems are in many ways the paradigm for complex adaptive matter. Small stimuli, like the binding of a signal molecule at a cell surface or the release of a messenger molecule inside the cell, can give rise to large scale changes in cell function, such as mechanical movement, the generation of energy for synthesis, or the triggering of self replication. The study of these complex systems provides perhaps the greatest challenge for science, and it must draw on an unprecedented breadth of experimental and theoretical tools. This workshop will focus on the structure and dynamics of biological molecules and their interactions in complex networks and assemblies that carry our biological function.

The latter half of the 20th century has yielded a wealth of information on the biological polymers (DNA, RNA, proteins) that contain the blue prints for life as well as the means to translate them and use them to synthesize the basic building blocks. The DNA in our genomes contains the blue prints that are translated by proteins and RNA acting in highly regulated molecular networks to provide the information used by the cell to synthesize every protein it needs. There are 100,000 genes in the human genome that code for distinct proteins, each having unique structural and dynamic properties that confer a specific function needed by the cells that make up an individual. To add to this complexity, the majority of cellular functions are carried out by assemblies of 10 or more proteins that act in concert. These assemblies are often referred to as molecular machines. Since the 1950s we have been accumulating a structural data base of several thousand individual proteins as well as small fragments of DNA and RNA. While an impressive achievement, this data base represents only a tiny fraction of the set of structures we need to determine in order to understand cellular function at the molecular level. Moreover, the majority of known protein structures are relatively small, around 50 kDa, and many represent only a single domain of a larger protein. There are few examples of complexes and even fewer large assemblies.

The NIH, with the DOE, is implementing structural genomics initiatives to facilitate the rapid expansion of our biomolecular structural data base in much the same way the Human Genome initiative delivered a plethora of DNA sequence information. High through put structural techniques such as synchrotron based crystallography will be key, and the community is evaluating the role for high resolution NMR. The challenge in using this data base to understand function, however, will lie in leveraging the information on the component structures into an understanding of how the larger molecular machines and molecular networks function in a coordinated fashion. This grand challenge will require the convergence of different experimental, modeling, and theoretical tools to study mesoscale structures to Techniques, is intended to be but the first of a series of four workshops, held at approximately six month intervals, on the broad topic of physical studies of biological systems. Each workshop will focus on a few biological systems as examples and ask what developments in experimental and theoretical tools are needed to make the fundamental advances required to arrive at a holistic understanding of biological systems. Topics to be discussed at this initial workshop include:

High throughput structure determination for component structures; crystallography and NMR (David Eisenberg, UCLA; Joel Berendzen, LANL))

Small-angle neutron scattering with contrast variation; molecular complexes and assemblies (Guiseppi Zaccai, CNRS, France; Jill Trewhella, LANL)

Microscopy and fluorescence techniques (Carlos Bustamante, UC Berkeley; David Agard, UC San Francisco)

Modeling and simulation in biology (Stephen Perkins, Royal Free Hospital, London; Chang-Shung Tung, LANL; Angel Garcia, LANL)

Inelastic neutron scattering for studying macromolecular dynamics (Guiseppi Zaccai, CNRS, France)


3. Designing Emergent Matter: an Interdisciplinary Workshop Exploring the Next Frontier for Research on Complexity in Matter

Organizers: Laura Greene and Ralph Nuzzo (UIUC) and George Whitesides (Harvard)

Biological structures and processes offer perhaps the most inspiring examples of organizational and functional complexity known to science. The emergent characteristics of these systems derives from a complex interplay of factors, ones both thermodynamic and dynamical in nature, which are essential to the construction of stable systems which none-the-less can still demonstrate adaptive behaviors. Complexity and emergence are broadly interdisciplinary concepts that have not been deeply developed in the larger context of applications to materials and the related sciences concerned with condensed matter systems. The development of these essential connections represents an area of significant opportunity for progress in research that will benefit technological development and serve as a major theme around which to develop interdisciplinary programs of study.

This workshop will bring together a preeminent group of scholars from a wide variety of disciplines to explore and discuss these issues. The topics we will consider span the frontiers of condensed matter research. Our speakers will discuss opportunities for progress afforded by a focus on complexity and the needs for a truly interdisciplinary approach to the field. Emerging areas of research that will be covered in the charge to workshop participants include self-replication, hierarchical organization at many length scales, energy-dissipative assembly, driven processes, non-equilibrium structural evolution and pattern formation, emergent behavior in strongly correlated electron systems, among others. In our discussions, we will seek to develop a set of general tools that enable the design and study of materials and condensed matter systems that exhibit complex properties and functionality, that is to say ones that arise from influences which involve more than a direct structural correlation.


4. Neural Complexity for Physical Scientists

Organizers: Charles Stevens (Salk Institute) and David Pines (ICAM and Los Alamos)

We propose to hold an eight day school/workshop on Neural Complexity for Physical Scientists, chaired by Charles Stevens (Salk) and David Pines (ICAM) at the Salk Institute in late fall, 2000. The workshop would bring together senior neurobiologists, ten physical scientists (some experimental, some theoretical), and ten graduate students or postdoctoral fellows. It would focus on two frontier topics in neurobiology: pattern formation in cortical architecture, and the problem of representation in sensory systems as revealed by the visual and olfactory systems. Both of these topics are at the heart of research in modern neurobiology and have been chosen as areas in which theory is most likely to be required.

The workshop would last some 3 1/2 days and be preceded by an intensive course, a three day series of elementary lectures designed to solve the jargon problem by presenting to non-experts enough of the language and ideas of neural complexity that they would be in a position to follow the more specialized lectures and discussion in the workshop proper. On the first day, there would be three lectures which provide a general introduction to the brain: three lectures on each of the two following days would be devoted to each of the two workshop topics, with the material again being presented to provide the background necessary for an understanding of the more specialized lectures to be presented in the workshop to follow.

The graduate students and postdocs in attendance would be responsible for writing up lecture notes on the three-day short course, which, following a review by the lecturers, would be published under the title of Elements of Neural Complexity. Following the workshop, a subset of the workshop organizers and lecturers would meet for the purpose of producing a popular account of the workshop, suitable for publication in Nature or Science.

Neurobiologists being considered for the short course of lectures and/or the workshop include Charles Stevens (Salk Institute), Marcus Meister (Harvard), Tony Zaider (Cold Spring Harbor), Larry Katz (Duke),Tom Albright (Salk), Ken Miller (UCSF), Mitya Shklovskii (Cold Springs Harbor), and Alexei Kulakov (Salk Institute)

Senior physical scientists under consideration for the workshop include Bob Laughlin (Stanford), Peter Wolynes (UIUC), Sudip Chakravarty (UCLA),), David Awschalom (UCSB), Joerg Schmalian (Iowa State), Andy Millis (Rutgers), Seb Doniach (Stanford), Lubert Stryer (Stanford), Boris Shraiman (Lucent)

The graduate students and postdocs participating in the workshop would be chosen by the Workshop Steering Committee following an open competition.


5. Cellular Complexity for Physical Scientists

Organizers: Daniel Gottschaling and Lee Hartwell (Hutchinson Cancer Research Institute), Stanislas Leibler (Princeton) and David Pines (Los Alamos)

There is a growing conviction on the part of some cellular biologists and theoretical physicists that much promising science could emerge as a result of fruitful interactions between members of these two communities. What is being sought is sufficient overlap, via a workshop or workshops, that a theorist would begin to have an idea of what is going on in a cell, and, as a result, would be led to suggest experiments to test possible models for that behavior.


6. Complex Adaptive Matter Dynamics: from Clusters and Polymers to Proteins and Nucleic Acids

Organizers: R. Stephen Berry (Chicago and NAS) and Angel Garcia (Los Alamos)

One large class of systems providing an archetype for complex behavior consists of assemblies of tens to millions of interacting particles. In particular this class includes atomic and molecular clusters, polymers and biopolymers such as proteins and nucleic acids. Traditional molecules do not fit well into this category because they typically have only one or a very few stable, observable structures; an important characteristic of this class is the multiplicity of stable structures they may exhibit. In fact this number grows with the number of particles N in the system at a rate that has been estimated as a product of something faster than and exponential in N (the number of geometrically-distinct structures) times N!, the approximate number of permutational isomers if all the particles are identical. It is difficult to find any system more complex than this, whose dynamics or kinetics we might hope to analyze.

Considerable progress has occurred in this area in very recent years. While there have been many approaches to specific kinds of problems, such as the enumeration of the number of stable isomers and the rate of folding of specific protein models, recent advances have started to accelerate the rate of progress by addressing the class of problems in a general, more fundamental way. Specifically, there have been two converging lines that have sought to establish some general principles on which further progress may (and has already started to be) built.

One line has been establishing the links between elementary interparticle forces, the topography of the many-dimensional potential energy landscape generated by these forces, the consequent dynamics and kinetics produced by the topography, the characteristics of the topography and dynamics that determine whether a system tends to find amorphous, glassy structures or selected, special structures such as crystalline or "native" structures of clusters and proteins, respectively. As an illustration, one central part of the recent results shows that short-range forces are associated with very sawtooth-like topographies, few-particle motion from one locally-stable structure to another, and a strong tendency to formation of amorphous structures; long-range (or effective long-range) interparticle forces generate staircase-like landscapes, on which structure-to-structure motions are highly collective, and make systems into "structure-seekers".

The second line is based on the realization that with growing complexity, systems require successively higher levels of aggregation and abstraction in the description of their behavior. Detailed computations, based on full knowledge of the potential surface, serve to describe systems of up to about 10 or 15 particles, but no more. Statistical approaches must be used even for systems of 18 or 20 particles. Molecular dynamics simulations obtained by solving equations of motion, are suitable for addressing specific problems of systems consisting of as many as hundreds or even thousands of particles, but become too inefficient for most problems with larger systems. Consequently, statistical approaches, based on kinetics rather than dynamics (so that "state" takes on a meaning implying an average behavior over a time of picoseconds, rather than an instantaneous condition), become a natural approach for describing large clusters and small proteins and polymers. Larger systems require still higher levels of aggregation, such as may be obtained by replacing sets (matrices) of rate coefficients with random matrices whose distributions of values mimic those of their smaller counterparts. Topological analyses can replace more detailed topographical analyses, provided the questions one addresses are suitably recast. The crucial barrier to carrying out these successive levels of aggregation and abstraction is validation, at each stage, of the next level. This requires careful comparison of the results from the more detailed level with results from the more abstracted level, by working with systems in regions of size and complexity in which the two approaches may overlap. This kind of analysis reveals how to carry out the more abstracted approach so that it can reproduce the conclusions of the more detailed approach. This kind of study has been done for establishing how to carry out the transition from dynamics to kinetics, and, in at least initial steps, to move from full to statistical-sample descriptions of complex potential surfaces.

To bring scientists together who can contribute the many skills required to exploit this rapidly-growing field (if it can be called a field at all), is one of the important functions that ICAM can perform. This will require mathematicians, statisticians, atomic, molecular, polymer and condensed-matter physicists and chemists, and molecular biologists, at very least. University settings rarely provide fertile ground for such collaborations; ICAM can do just that.