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Capacitive-based disposable pH sensor. The silver pen could be replaced with aluminum foil. (credit: Joanna M. Nassar et al./Advanced Materials Technologies)

Here’s a challenge: using only low-cost materials available in your house (such as aluminum foil, pencil, scotch tape, sticky-notes, napkins, and sponges), build sensitive sensors (“smart skin”) for detecting temperature, humidity, pH, pressure, touch, flow, motion, and proximity (at a distance of 13 cm). Your sensors must show reliable and consistent results and be capable of connecting to low-cost, tiny computers such as Arduino and Raspberry Pi devices.

The goal here is to replace expensive manufacturing processes for creating paper-based sensors with a simple recyclable 3D stacked 6 × 6 “paper skin” array for simultaneous sensing, made solely from household resources, according to Muhammad Mustafa Hussain, senior author of an Advanced Materials Technologies journal open-access paper and professor at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia.

How to create a temperature sensor

Schematic of temperature sensors using aluminum foil or silver ink pen (credit: Joanna M. Nassar/Advanced Materials Technologies)

Creating a highly sensitive temperature sensor requires just two things: a Post-It note and a piece of aluminum foil (a silver ink pen would be more sensitive).  A change of temperature would change the resistance of an aluminum strip. To measure the resistance change, connect the sensor to a highly sensitive ohmmeter, using an Arduino Uno, for example. (The output of the Arduino could trigger an alarm, for example.)

Arduino Uno and ohmmeter circuit. The sensor would replace the “resistor to be measured” in the schematic. The bottom resistor value would depend on the sensor resistance range. (credit: Adafruit and Learning About Electronics)

 Two designs for a simple pressure sensor

Two designs for a pressure sensor using a parallel-plate structure: (top) Microfiber wipe and sponge; (bottom) more sensitive air-gap structure with sponge. As applied pressure increases, the dielectric thickness decreases, increasing the output capacitance. To measure it, the aluminum foil is connected to a resistor–capacitor circuit (RC circuit), which is connected to an Arduino or Raspberry Pi device to calculate associated pressure change. (credit: Joanna M. Nassar et al./Advanced Materials Technologies)

The simple fabrication process and low-cost materials used “make this flexible platform the lowest cost and accessible to anyone, without affecting performance in terms of response and sensitivity,” Hussain says.

“Democratization of electronics will be key in the future for its continued growth. … This is the first time a [single] platform shows multi-sensory functionalities close to that of natural skin.”

Abstract of Paper Skin Multisensory Platform for Simultaneous Environmental Monitoring

Human skin and hair can simultaneously feel pressure, temperature, humidity, strain, and flow—great inspirations for applications such as artificial skins for burn and acid victims, robotics, and vehicular technology. Previous efforts in this direction use sophisticated materials or processes. Chemically functionalized, inkjet printed or vacuum-technology-processed papers albeit cheap have shown limited functionalities. Thus, performance and/or functionalities per cost have been limited. Here, a scalable “garage” fabrication approach is shown using off-the-shelf inexpensive household elements such as aluminum foil, scotch tapes, sticky-notes, napkins, and sponges to build “paper skin” with simultaneous real-time sensing capability of pressure, temperature, humidity, proximity, pH, and flow. Enabling the basic principles of porosity, adsorption, and dimensions of these materials, a fully functioning distributed sensor network platform is reported, which, for the first time, can sense the vitals of its carrier (body temperature, blood pressure, heart rate, and skin hydration) and the surrounding environment.

If you zap a crystal (green, left) containing highly ordered protein molecules with X-rays, the X-rays scatter and produce useful regular patterns of spots known as Bragg peaks (red dots). But if the protein in the crystal is less ordered or disordered (right), the X-rays produce some spots along with patterns of light and shade known as a continuous diffraction pattern that’s not useful. (credit: Eberhard Reimann/DESY)

Researchers have overcome a long-standing technical barrier to imaging 3D structures of thousands of molecules important to medicine and biology.

The 3D structures of many protein molecules have been discovered using a technique called X-ray crystallography, but the method relies on scientists being able to produce highly ordered crystals containing the protein molecules in a regular arrangement. When X-rays are shone on highly ordered crystals, the X-rays scatter and produce regular patterns of spots called Bragg peaks (see figure above, left). High-quality Bragg peaks contain the information to produce high-resolution 3D structures of proteins.

Unfortunately, many important and complex biomolecules do not form highly ordered crystals; instead, the protein arrangements are slightly disordered. When X-rays are shone on these more disordered crystals, a smaller number of Bragg peaks are produced, along with a vague pattern of light and shadow known as a continuous diffraction pattern (right).

In the past, scientists discarded these less-than-perfect crystals. Unfortunately, many of the molecules forming disordered crystals are important molecular complexes such as those that span cell membranes.

X-raying crystal patterns to detect hidden protein structures

Analysis of Bragg peaks alone (top) reveals far less details than analysis of the high-res continuous diffraction pattern (bottom). Magnifying glasses show actual data. (credit: DESY, Eberhard Reimann)

So a team led by Professor Henry Chapman from the Center for Free-Electron Laser Science at DESY in Hamberg, Germany turned to the world’s most powerful X-ray laser: the SLAC LCLS at Stanford University.

Kartik Ayyer, PhD., lead author of the article in Nature, explains that the method uses an approach similar to that used to image a single molecule.

“If you would shoot X-rays on a single molecule, it would produce a continuous diffraction pattern free of any Bragg spots,” he says. “The pattern would be extremely weak, however, and very difficult to measure. But the ‘background’ in our crystal analysis is like accumulating many shots from individually aligned single molecules. We essentially just use the crystal as a way to get a lot of single molecules, aligned in common orientations, into the beam.”

As the model protein, the researchers crystallized photosystem II (PSII), a large membrane–protein complex of photosynthesis that plants use to produce oxygen for life on Earth.

After exposing the crystal to X-rays, the researchers first analyzed the Bragg peaks of PSII to produce a low-resolution outline of the 3D structure (figure above, top). They then improved this data, using an algorithm, to analyze the continuous diffraction pattern and produced a higher-resolution 3D structure (figure, bottom).

This novel method means that imperfect crystals containing a slightly disordered protein arrangement can now be used to “directly view large protein complexes in atomic detail,” says Chapman. “This kind of continuous diffraction has actually been seen for a long time from many different poorly diffracting crystals,” says Chapman. “It wasn’t understood that you can get structural information from it and so analysis techniques suppressed it.

“We’re going to be busy to see if we can solve [additional] structures of molecules from old discarded data.”

Abstract of Macromolecular diffractive imaging using imperfect crystals

The three-dimensional structures of macromolecules and their complexes are mainly elucidated by X-ray protein crystallography. A major limitation of this method is access to high-quality crystals, which is necessary to ensure X-ray diffraction extends to sufficiently large scattering angles and hence yields information of sufficiently high resolution with which to solve the crystal structure. The observation that crystals with reduced unit-cell volumes and tighter macromolecular packing often produce higher-resolution Bragg peaks suggests that crystallographic resolution for some macromolecules may be limited not by their heterogeneity, but by a deviation of strict positional ordering of the crystalline lattice. Such displacements of molecules from the ideal lattice give rise to a continuous diffraction pattern that is equal to the incoherent sum of diffraction from rigid individual molecular complexes aligned along several discrete crystallographic orientations and that, consequently, contains more information than Bragg peaks alone. Although such continuous diffraction patterns have long been observed—and are of interest as a source of information about the dynamics of proteins—they have not been used for structure determination. Here we show for crystals of the integral membrane protein complex photosystem II that lattice disorder increases the information content and the resolution of the diffraction pattern well beyond the 4.5-ångström limit of measurable Bragg peaks, which allows us to phase the pattern directly. Using the molecular envelope conventionally determined at 4.5 ångströms as a constraint, we obtain a static image of the photosystem II dimer at a resolution of 3.5 ångströms. This result shows that continuous diffraction can be used to overcome what have long been supposed to be the resolution limits of macromolecular crystallography, using a method that exploits commonly encountered imperfect crystals and enables model-free phasing.

ICSPACE exercise feedback display (credit: ICSPACE)

A virtual “intelligent coaching space” (ICSPACE) developed by Cluster of Excellence Cognitive Interaction Technology (CITEC) at Bielefeld University in Germany is assisting patients with physical rehabilitation and helping athletes improve their performance with sports exercises.

The user is 3D-scanned in advance and used to create an avatar. Participants wear 3D stereoscopic glasses, which create the impression of working out in a gym with a coach. Reflective markers attached to the user are tracked by infrared cameras and a virtual display allows users to watch themselves from various angles to see how they are performing the exercises and make improvements.

Mistakes made during movement exercises, such as bending one’s neck too far during a squat, are depicted in the display in an exaggerated way to draw attention to the error.

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A virtual coach instructs a user how to do a squat (credit: CITEC/Bielefeld University)

A virtual coach is also available and can mark individual body areas on the display to show needed improvement. A slow-motion video of the user performing the exercise can demonstrate correct motions.

“The planned range of activities will include gymnastics exercises, tai chi, yoga, or, for example, how to swing a golf club,” says cognitive scientist Professor Thomas Schack.

The research is funded by the German Research Foundation (DFG).

Abstract of Multi-Level Analysis of Motor Actions as a Basis for Effective Coaching in Virtual Reality

In order to effectively support motor learning in Virtual Reality, real-time analysis of motor actions performed by the athlete is essential. Most recent work in this area rather focuses on feedback strategies, and not primarily on systematic analysis of the motor action to be learnt. Aiming at a high-level understanding of the performed motor action, we introduce a two-level approach. On the one hand, we focus on a hierarchical motor performance analysis performed online in a VR environment. On the other hand, we introduce an analysis of cognitive representation as a complement for a thorough analysis of motor action.