Jason Shulman

Thermal conductivity measurement under hydrostatic pressure using the 3ω method

We have designed and modeled new techniques, based on the 3ω method, to measure thermal conductivity of liquids (κl) and solids (κs) under hydrostatic pressure (P). The system involves a solid sample immersed in a liquid pressure medium, both of which have unknown thermal properties. The temperature (T) and P dependance of κl are first determined through the use of a modified 3ω technique. This method uses a conducting wire (Pt, in this work), which is immersed in the pressure medium, as the heater/sensor. In addition to κl, this allows for the accurate determination of the specific heat per volume of the liquid and Pt, (ρC)l and (ρC)Pt, respectively. The information of κl and (ρC)l can then be used to make corrections to measurements of κs, in which the sample is immersed in the pressure medium, and a metal strip acts as the heater/sensor. We present the T and P dependence of κl and (ρC)l for the widely used pressure medium 3M Fluorinert FC77 up to 0.8 GPa. The measurement of κs for a thermoelectric clat...

Plasmalike negative capacitance in nanocolloids

A negative capacitance has been observed in a nanocolloid between 0.1 and 10−5Hz. The response is linear over a broad range of conditions. The low-ω dispersions of both the resistance and capacitance are consistent with the free-carrier plasma model, while the transient behavior demonstrates a possible energy storage mechanism. A collective excitation, therefore, is suggested.

A negative dielectric constant in nano-particle materials under an electric field at very low frequencies

The significance of a negative dielectric constant has long been recognized. We report here the observation of a field-induced large negative dielectric constant of aggregates of oxide nano-particles at frequencies below ~ 1 Hz at room temperature. The accompanying induced charge detected opposes the electric field applied in the field-induced negative dielectric constant state. A possible collective effect in the nano-particle aggregates is proposed to account for the observations. Materials with a negative dielectric constant are expected to provide an attraction between similar charges and unusual scattering to electromagnetic waves with possible profound implications for high temperature superconductivity and communications.

A Robust Topology-Based Algorithm for Gene Expression Profiling

Early and accurate diagnoses of cancer can significantly improve the design of personalized therapy and enhance the success of therapeutic interventions. Histopathological approaches, which rely on microscopic examinations of malignant tissue, are not conducive to timely diagnoses. High throughput genomics offers a possible new classification of cancer subtypes. Unfortunately, most clustering algorithms have not been proven sufficiently robust. We propose a novel approach that relies on the use of statistical invariants and persistent homology, one of the most exciting recent developments in topology. It identifies a sufficient but compact set of genes for the analysis as well as a core group of tightly correlated patient samples for each subtype. Partitioning occurs hierarchically and allows for the identification of genetically similar subtypes. We analyzed the gene expression profiles of 202 tumors of the brain cancer glioblastoma multiforme (GBM) given at the Cancer Genome Atlas (TCGA) site. We identify core patient groups associated with the classical, mesenchymal, and proneural subtypes of GBM. In our analysis, the neural subtype consists of several small groups rather than a single component. A subtype prediction model is introduced which partitions tumors in a manner consistent with clustering algorithms but requires the genetic signature of only 59 genes.

Experimental determination of circuit equations

Kirchhoffs laws offer a general, straightforward approach to circuit analysis. Unfortunately, their application becomes impractical for all but the simplest of circuits. This work presents an alternative procedure, based on an approach developed to analyze complex networks, thus making it appropriate for use on large, complicated circuits. The procedure is unusual in that it is not an analytic method but is based on experiment. Yet, this approach produces the same circuit equations obtained by more traditional means.

Effective Models of Periodically Driven Networks

Circadian rhythms are governed by a highly coupled, complex network of genes. Due to feedback within the network, any modification of the systems state requires coherent changes in several nodes. A model of the underlying network is necessary to compute these modifications. We use an effective modeling approach for this task. Rather than inferred biochemical interactions, our method utilizes microarray data from a group of mutants for its construction. With simulated data, we develop an effective model for a circadian network in a peripheral tissue, subject to driving by the suprachiasmatic nucleus, the mammalian pacemaker. The effective network can predict time-dependent gene expression levels in other mutants.

Field-induced Giant Static Dielectric Constant in Nano-particle Aggregates at Room Temperature

The analogy between magnetism and electricity was established by Maxwell in the 19th century, despite the subtle difference. While magnetic materials display paramagnetism, ferromagnetism, antiferromagnetism and diamagnetism, only paraelectricity, ferroelectricity and antiferrolelectricity have been found in dielectric materials. The missing ‘diaelectricity’ may be found if there exists a material that has a dc-polarization opposing the electric field or a negative dielectric susceptibility ε′ − 1, with ε′ being the real part of the relative dielectric constant. Both of these properties have been observed in nano-particle aggregates under a dc electric bias field at room temperature. A possible collective effect in the nano-particle aggregates is proposed to account for the observation. ‘Diaelectricity’ implies overscreening by polarization to the external charges. Materials with a negative static ε′ are expected to provide attraction to similar charges and unusual scattering to electromagnetic waves with possible profound implications for high temperature superconductivity and communications.

Controlling networks of nonlinearly-coupled nodes using response surfaces.

Control of complex processes is a major goal of network analyses. Most approaches to control nonlinearly coupled systems require the network topology and/or network dynamics. Unfortunately, neither the full set of participating nodes nor the network topology is known for many important systems. On the other hand, system responses to perturbations are often easily measured. We show how the collection of such responses –a response surface– can be used for network control. Analyses of model systems show that response surfaces are smooth and hence can be approximated using low order polynomials. Importantly, these approximations are largely insensitive to stochastic fluctuations in data or measurement errors. They can be used to compute how a small set of nodes need to be altered in order to direct the network close to a pre-specified target state. These ideas, illustrated on a nonlinear electrical circuit, can prove useful in many contexts including in reprogramming cellular states.

Generation of negative capacitance in a nanocolloid

Negative capacitance (NC) is a rather ubiquitous phenomenon that is found in many complex materials ranging from semiconductor devices to biological membranes. The underlying physical processes in this diverse collection differ considerably. However, we previously demonstrated that a relationship exists between NC and the conductivity of the material. Here, we examine and exploit this relationship in an effort to pinpoint the source of NC in a nanocolloid, composed of urea coated nanoparticles in silicone oil, which has previously been shown to exhibit the NC effect. This is accomplished by investigating the influence of several external parameters, such as temperature and moisture content, on the NC and conductance of the colloid as well as solid materials created from the nanoparticles used in the colloid. In addition to NC, the colloid demonstrates the electrorheological (ER) effect. It is shown that large scale particle motions, such as those that generate the ER effect, are not responsible for the NC...