Neil Gershenfeld

E-broidery: design and fabrication of textile-based computing

Highly durable, flexible, and even washable multilayer electronic circuitry can be constructed on textile substrates, using conductive yarns and suitably packaged components. In this paper we describe the development of e-broidery (electronic embroidery, i.e., the patterning of conductive textiles by numerically controlled sewing or weaving processes) as a means of creating computationally active textiles. We compare textiles to existing flexible circuit substrates with regard to durability, conformability, and wearability. We also report on: some unique applications enabled by our work; the construction of sensors and user interface elements in textiles; and a complete process for creating flexible multilayer circuits on fabric substrates. This process maintains close compatibility with existing electronic components and design tools, while optimizing design techniques and component packages for use in textiles.

Applying electric field sensing to human-computer interfaces

A non-contact sensor based on the interaction of a person with electric fields for human-computer interface is investigated. Two sensing modes are explored: an external electric field shunted to ground through a human body, and an external electric field transmitted through a human body to stationary receivers. The sensors are low power (milliwatts), high resolution (millimeter) low cost (a few dollars per channel), have low latency (millisecond), high update rate (1 kHz), high immunity to noise (>72 dB), are not affected by clothing, surface texture or reflectivity, and can operate on length scales from microns to meters. Systems incorporating the sensors include a finger mouse, a room that knows the location of its occupant, and people-sensing furniture. Haptic feedback using passive materials is described. Also discussed are empirical and analytical approaches to transform sensor measurements into position information.

Musical Applications of Electric Field Sensing

The Theremin was one of the first electronic musical instruments, yet it provides a degree of expressive real-time control that remains lacking in most modern electronic music interfaces. Underlying the deceptively simple capacitance measurement used by it and its descendants are a number of surprisingly interesting current transport mechanisms that can be used to inexpensively , unobtrusively, robustly, and remotely detect the position of people and objects. We review the relevant physics, describe appropriate measurement instrumentation, and discuss applications that began with capturing virtuosic performance gesture on traditional stringed instruments and evolved into the design of new musical interfaces.

Reversibly Assembled Cellular Composite Materials

Quality Ultralight Ensuring the light-weight and high-strength properties of carbon-fiber composite materials is costly. Cheung and Gershenfeld (p. 1219, published online 15 August; see the Perspective by Schaedler et al.) have mass-produced cross-sectional parts that can be assembled into strong, ultralight lattices. Carbon-fiber composites are sliced into cross-shaped pieces that can be independently tested and reliably assembled into rigid and reversible cuboctahedral lattices. Reversible assembly of mass-produced composite-material parts created a stiff, ultralight structure. [Also see Perspective by Schaedler et al.] We introduce composite materials made by reversibly assembling a three-dimensional lattice of mass-produced carbon fiber–reinforced polymer composite parts with integrated mechanical interlocking connections. The resulting cellular composite materials can respond as an elastic solid with an extremely large measured modulus for an ultralight material (12.3 megapascals at a density of 7.2 milligrams per cubic centimeter). These materials offer a hierarchical decomposition in modeling, with bulk properties that can be predicted from component measurements and deformation modes that can be determined by the placement of part types. Because site locations are locally constrained, structures can be produced in a relative assembly process that merges desirable features of fiber composites, cellular materials, and additive manufacturing.

SEA: a scalable encryption algorithm for small embedded applications

Most present symmetric encryption algorithms result from a tradeoff between implementation cost and resulting performances. In addition, they generally aim to be implemented efficiently on a large variety of platforms. In this paper, we take an opposite approach and consider a context where we have very limited processing resources and throughput requirements. For this purpose, we propose low-cost encryption routines (i.e. with small code size and memory) targeted for processors with a limited instruction set (i.e. AND, OR, XOR gates, word rotation and modular addition). The proposed design is parametric in the text, key and processor size, allows efficient combination of encryption/decryption, “on-the-fly” key derivation and its security against a number of recent cryptanalytic techniques is discussed. Target applications for such routines include any context requiring low-cost encryption and/or authentication.

Ultra-small-sample molecular structure detection using microslot waveguide nuclear spin resonance

We here report on the design of a planar microslot waveguide NMR probe with an induction element that can be fabricated at scales from centimeters to nanometers to allow analysis of biomolecules at nano- or picomole quantities, reducing the required amount of materials by several orders of magnitude. This device demonstrates the highest signal-to-noise ratio for a planar detector to date, measured by using the anomeric proton signal from a 15.6-nmol sample of sucrose. This probe had a linewidth of 1.1 Hz for pure water without susceptibility matching. Analysis of 1.57 nmol of ribonuclease-A shows high sensitivity in one- and two-dimensional NMR spectra. Along with reducing required sample volumes, this integrated geometry can be packed in parallel arrays and combined with microfluidic systems. Further development of this device may have broad implications not only for advancing our understanding of many intractable protein structures and their folding, molecular interactions, and dynamic behaviors, but also for high-sensitivity diagnosis of a number of protein conformational diseases.

Cluster-weighted modelling for time-series analysis

The need to characterize and forecast time series recurs throughout the sciences, but the complexity of the real world is poorly described by the traditional techniques of linear time-series analysis. Although newer methods can provide remarkable insights into particular domains, they still make restrictive assumptions about the data, the analyst, or the application. Here we show that signals that are nonlinear, non-stationary, non-gaussian, and discontinuous can be described by expanding the probabilistic dependence of the future on the past around local models of their relationship. The predictors derived from this general framework have the form of the global combinations of local functions that are used in statistics, machine learning and studies of nonlinear dynamics,. Our method offers forecasts of errors in prediction and model estimation, provides a transparent architecture with meaningful parameters, and has straightforward implementations for offline and online applications. We demonstrate our approach by applying it to data obtained from a pseudo-random dynamical system, from a fluctuating laser, and from a bowed violin.

Intrabody buses for data and power

While wearable computers are empowering fashion accessories, they bring with them a tangle of wires which connect their parts. As these subsystems begin to decouple and operate on less power, it becomes possible to wirelessly distribute their required data and power using to the wearers body. We have demonstrated systems that transmit and receive both data and power, and are working to combine the two.

Intelligent Infrastructure for Energy Efficiency

A substantial fraction of wasted energy can be recovered by extending insights from the architecture of the Internet to the infrastructure of buildings. Buildings use 40% of the primary energy supplied in the United States, and more than 70% of all generated electricity (1), primarily for heating, cooling, and lighting. About 20% of the energy used by buildings can potentially be saved by correcting faults, including malfunctions and unnecessary operation (2). Initial deployments of advanced control systems currently in development suggest that they can save an additional 10 to 20% (3). The energy efficiency resource recoverable through such improved building controls and fault detection corresponds to the output from hundreds of power plants, equivalent to more than one-third of the coal-fired power production in the United States (1). Realizing these substantial savings will require introducing intelligence into the infrastructure of buildings, to distribute the optimization of their operation and detection of their faults.

An installation of interactive furniture

We report on a project that explored emerging technologies for intuitive and unobtrusive information interfaces in a compelling setting. An installation at the Museum of Modern Art, New York, was part of a public exhibit and included an interactive table that presented information associated with the exhibit to the gallery visitors without visible conventional computing elements. The enabling devices included noncontact sensing of low-cost tags in physical icons, electrostatic detection of hand location in three dimensions, and sensor fusion through lightweight Internet Protocol access.