This review gives an overview of techniques used for high-resolution jet printing that rely on electrohydrodynamically induced flows. Such methods enable the direct, additive patterning of materials with a resolution that can extend below 100 nm to provide unique opportunities not only in scientific studies but also in a range of applications that includes printed electronics, tissue engineering, and photonic and plasmonic devices. Following a brief historical perspective, this review presents descriptions of the underlying processes involved in the formation of liquid cones and jets to establish critical factors in the printing process. Different printing systems that share similar principles are then described, along with key advances that have been made in the last decade. Capabilities in terms of printable materials and levels of resolution are reviewed, with a strong emphasis on areas of potential application.

We present a pulsed dc voltage printing regime for high-speed, high-resolution and high-precision electrohydrodynamic jet (E-jet) printing. The voltage pulse peak induces a very fast E-jetting mode from the nozzle for a short duration, while a baseline dc voltage is picked to ensure that the meniscus is always deformed to nearly a conical shape but not in a jetting mode. The duration of the pulse determines the volume of the droplet and therefore the feature size on the substrate. The droplet deposition rate is controlled by the time interval between two successive pulses. Through a suitable choice of the pulse width and frequency, a jet-printing regime with a specified droplet size and droplet spacing can be created. Further, by properly coordinating the pulsing with positioning commands, high spatial resolution can also be achieved. We demonstrate high-speed printing capabilities at 1 kHz with drop-on-demand and registration capabilities with 3-5 μm droplet size for an aqueous ink and 1-2 μm for a photocurable polymer ink.

Self-assembly of block-copolymers provides a route to the fabrication of small (size, <50 nm) and dense (pitch, <100 nm) features with an accuracy that approaches even the demanding specifications for nanomanufacturing set by the semiconductor industry. A key requirement for practical applications, however, is a rapid, high-resolution method for patterning block-copolymers with different molecular weights and compositions across a wafer surface, with complex geometries and diverse feature sizes. Here we demonstrate that an ultrahigh-resolution jet printing technique that exploits electrohydrodynamic effects can pattern large areas with block-copolymers based on poly(styrene-block-methyl methacrylate) with various molecular weights and compositions. The printed geometries have diameters and linewidths in the sub-500 nm range, line edge roughness as small as ∼45 nm, and thickness uniformity and repeatability that can approach molecular length scales (∼2 nm). Upon thermal annealing on bare, or chemically or topographically structured substrates, such printed patterns yield nanodomains of block-copolymers with well-defined sizes, periodicities and morphologies, in overall layouts that span dimensions from the scale of nanometres (with sizes continuously tunable between 13 nm and 20 nm) to centimetres. As well as its engineering relevance, this methodology enables systematic studies of unusual behaviours of block-copolymers in geometrically confined films.

In this paper, we focus on improving performance and robustness in precision motion control (PMC) of multi-axis systems through the use of iterative learning control (ILC). A norm optimal ILC framework is used to design optimal learning filters based on design objectives. This paper contains two key contributions. The first half of this paper presents the norm optimal framework, including the introduction of an additional degree of design flexibility via time-varying weighting matrices. This addition enables the controller to take trajectory, position-dependent dynamics, and time-varying stochastic disturbances into consideration when designing the optimal learning controller. Explicit guidelines and analysis requirements for weighting matrix design are provided. The second half of this paper seeks to demonstrate the use of these guidelines. Using the design details provided in the paper, norm optimal learning controllers using time-invariant and time-varying weighting matrices are designed for comparison through simulation on a model of a multi-axis robotic testbed.Index Terms-Design methodology, learning control systems, multiple-input-multiple-output (MIMO) systems, time-varying systems.

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