Engineers develop new sensor to detect tiny individual nanoparticles

The image shows arrays of self-referenced and self-heterodyned Whispering-Gallery Raman microlasers for single nanoparticle detection. A "pump" laser generates a single Raman lasing mode inside the silica resonators. Upon landing of a nanoparticle on the resonator, Raman laser circulating inside the resonator undergo mode splitting leading to two new lasing modes in different colors. Monitoring the changes in the color difference (frequency difference) enables detecting and measuring of nanoparticles with single particle resolution. Credit: J. Zhu, B. Peng, S.K. Ozdemir, L. Yang

Nanoparticles, engineered materials about a billionth of a meter in size, are around us every day. Although they are tiny, they can benefit human health, as in some innovative early cancer treatments, but they can also interfere with it through viruses, air pollution, traffic emissions, cosmetics, sunscreen and electronics.

A team of researchers at Washington University in St. Louis, led by Lan Yang, PhD, the Das Family Career Development Associate Professor in Electrical & Systems Engineering, and their collaborators at Tsinghua University in China have developed a new sensor that can detect and count nanoparticles, at sizes as small as 10 nanometers, one at a time. The researchers say the sensor could potentially detect much smaller particles, viruses and small molecules.

The research appears in the Proceedings of the National Academy of Sciences online Early Edition Sept. 1, 2014.

Yang and her colleagues have created the Raman microlaser sensor in a silicon dioxide chip to find individual nanoparticles without the need to "dope" the chip with chemicals called rare-earth ions to provide optical gain for the microlaser. Incorporating additions to the microresonator creates the need for more processing steps and increased costs and invites biocompatibility risks. In addition, the use of rare-earth ions requires specific "pump" lasers matching the energy transitions of the ions to generate optical gain, so for different rare-earth ions, different pump lasers must be used. Using the Raman process loosens the requirement of specific wavelength bands for pump lasers because Raman gain can be obtained using pump at any wavelength band, Yang says.

"This gives us the advantage of using the same dopant-free sensor at different sensing environments by tailoring the lasing frequency for the specific environment, for example, at the band where the environment has minimum absorption, and for the properties of the targeted nanoparticles by just changing the wavelength of the pump laser," says Sahin Kaya Ozdemir, PhD, a research scientist in Yang's group and the first author of the paper.

Yang's team integrated Raman lasing in a silica microcavity with the mode splitting technique pioneered by her group to develop a new, powerful sensor that more readily detects nanoparticles. The technology will benefit the electronics, acoustics, biomedical, plasmonics, security and metamaterials fields.

Yang's microsensor is in a class called whispering gallery mode resonators (WGMRs) because it works similarly to the renowned whispering gallery in London's St. Paul's Cathedral, where a person on one side of the dome can hear a message spoken to the wall by another person on the other side. Yang's device does much the same thing with light frequencies rather than audible ones.

One of the main differences between early resonators and the novel resonator, known as a morphology dependent resonator, was they didn't use mirrors to reflect light. Yang's WGMR is an actual mini-laser that supports "frequency degenerate modes," patterns of excitation inside the mini-laser's doughnut-shaped ring that are of the same frequency. One portion of light beamed by the Raman laser goes counterclockwise, another goes clockwise. When a particle lands on the ring and scatters energy between these modes, the single Raman lasing line splits into two lasing lines with different frequencies.

When a Raman laser beam is generated in the resonator, it likely will encounter a particle, such as a virus nanoparticle, on the circle. When the beam initially sees the particle, the beam splits into two, generating two lasing lines that serve as reference to the other to form a self-referenced sensing technique.

"Our new sensor differs from the earlier whispering gallery sensors in that it relies on Raman gain, which is inherent in silica, thereby eliminating the need for doping the microcavity with gain media, such as rare-earth ions or optical dyes, to boost detection capability," Ozdemir says. "This new sensor retains the biocompatibility of silica and could find widespread use for sensing in biological media."

"It doesn't matter what kind of wavelength is used, once you have the Raman laser circulating inside and there is a molecule sitting on the circle, when the beam sees the particle it will scatter in all kinds of directions," Yang says. "Initially you have a counterclockwise mode, then a clockwise mode, and by analyzing the characterization of the two split modes, we confirm the detection of nanoparticles."

In addition to the demonstration of Raman microlasers for particle sensing, the team says their work shows the possibility of using intrinsic gain mechanisms, such as Raman and parametric gain, instead of optical dyes, rare-earth ions or quantum dots, for loss compensation in optical and plasmonic systems where dissipation hinders progress and limits applications.

Source: Washington University in St. Louis

Screening tools to detect lung, heart disease developed by two high school students

Two Michigan high school students, sisters Ilina and Medha Krishen, have developed screening tools using electronic stethoscopes to detect lung and heart disease. The sisters will present their findings at CHEST 2014 in Austin, Texas next week. Credit: The Krishen family

Two Michigan high school students, sisters Ilina and Medha Krishen, have developed screening tools using electronic stethoscopes to detect lung and heart disease. The sisters will present their findings at CHEST 2014 in Austin, Texas next week.

Ilina Krishen became aware of the dangers of smoking and chemical air pollution when she saw the effects of lung disease on family members. Curious to find a way to detect early lung damage in people exposed to noxious air pollutants, Ilina, a high school senior at Port Huron Northern High School in Michigan, developed a screening mechanism using an electronic stethoscope. An electronic stethoscope overcomes the problem of low sound levels by electronically amplifying body sounds, using an electromagnetic diaphragm that captures the diaphragm movement as an electrical signal.

Ilina recruited 16 smokers, 13 firefighters, and 25 nonsmokers for her test. The electronic stethoscope recorded one breath cycle from each volunteer. Frequency peaks were used to analyze the frequency distribution of breath sounds. Differences of peaks above 125 Hz were analyzed.

Ilina found that the number of peaks was significantly higher in smokers and firefighters, even if the firefighters were nonsmokers. She realized that although firefighters wear protective masks when fighting fires, they often do not wear masks when making a second check of the building after the fire is out. "The firefighters are exposed to many poisonous chemicals that remain in the air after the fire has gone out," said Ilina. "Screening with an electronic stethoscope may be able to detect early changes in lung function in individuals without symptoms of lung disease."

Medha Krishen, Ilina's sister and a junior at Port Huron Northern High School, also presented a study that used an electronic stethoscope to screen student athletes for hypertrophic cardiomyopathy (HCM).

Medha studied 13 individuals: 10 with a normal cardiac sports physical and three with a diagnosis for HCM. Heart sounds were recorded in 5-second periods while the athletes were lying down, standing, and after exercise. Frequency peaks of a frequency amplitude plot were analyzed. Studies showed a significant difference in the distribution of frequency peaks in the two groups between the lying down position and after exercise. Normal athletes showed a lower percentage of peaks above 131 Hz after exercise, while the athletes at risk showed a rise in frequency peaks following exercise.

"When I was in fifth grade, a family friend died after exercise, and I always wanted to learn more about how to prevent something like that happening," said Medha. "My study analyzing heart sound frequencies may be a useful technique that school staff could use to screen for HCM."

The sisters are both athletes -- Ilina is a varsity tennis player, and Medha is an accomplished figure skater -- and they take a personal interest in the health of athletes. They are also nonsmokers and hope to encourage others not to smoke. After Ilina completed her study and showed her study subjects the results of her tests "two or three of the smokers have quit smoking, and that makes me feel good," says Ilina.

Source: American College of Chest Physicians

Wearable device to track diet under development

A concept of the device with sensor was made through 3-D printing. Credit: The University of Alabama

Sensors and software used to track physical activity are increasingly popular, as smart phones and their apps become more powerful and sophisticated, but, when it comes to food, they all rely on the user to report meals.

Dr. Edward Sazonov, an associate professor of electrical and computer engineering at The University of Alabama, hopes to change that through development of a sensor worn around the ear that would automatically track diet, giving medical professionals and consumers accurate information that can be missed with self-reporting.

"Weight gain comes from an unbalance of the energy we take in versus the energy we expend," Sazonov said. "We can estimate diet and nutrient intake, but the primary method is self-reporting. The sensor could provide objective data, helping us better understand patterns of food intake associated with obesity and eating disorders."

Sazonov is the lead on a $1.8 million, five-year grant from the National Institute of Health to test the practical accuracy of the wearable sensor in tracking diet. Already proven viable, the device will be updated, further miniaturized and validated in a more formal, robust experiment in the community.

Called an Automatic Ingestion Monitor, or AIM, it has potential to monitor eating by automatically detecting and capturing imagery of food intake and to estimate the mass and the energy content of ingested food.

The sensor feels vibrations from movement in the jaw during food intake, and the device is programmed to filter out jaw motions, such as talking, that are not coming from drinking or eating. Estimates of energy intake would be taken from the pictures of food or drink.

More than two-thirds of adults in the United States are clinically overweight or obese, according to estimates from the Center for Disease Control and Prevention.

"Eating may be an unconscious, even automatic behavior for some individuals, and the literature is full of examples of dietary behaviors which increase the risk for overeating," Sazonov said.

In a study, the AIM will be tested against the accuracy of an alternative method, the use of a doubly-labeled water to track energy use by humans. That method measures the body's elimination rate of stable isotopes of hydrogen and oxygen added to the water, a process that can take two weeks. The information can be used to estimate how many calories a person consumes over a period of time.

However, this method is expensive and requires medical specialization, and, unlike the proposed AIM, does not track eating behavior.

The information provided by AIM could be used to improve behavioral weight loss strategies or to develop new kinds of weight-loss interventions. In addition, the AIM could also provide an objective method of assessing the effectiveness of pharmacological and behavioral interventions for eating disorders.

It's likely the technology's first application would be as a medical device, but Sazonov said it's possible it could become a consumer device that would eliminate the need for health-conscious people to keep a record of their diet.

Source: University of Alabama

Smartphone sensors leave trackable fingerprints

Example demonstrating how accelerometer data shared with separate traffic and health applications could indicate Bob's location. Credit: Image courtesy of University of Illinois College of Engineering

Fingerprints -- those swirling residues left on keyboards and doorknobs -- are mostly invisible. They can affirm your onetime presence, but they cannot be used to track your day-to-day activities.

They cannot tell someone in real time that after exercising at the gym, you went to office in a bus and played video games during lunch. But what if our hand-held electronics are leaving real-time fingerprints instead? Fingerprints that are so intrinsic to the device that, like our own, they cannot be removed?

Research by Associate Professor Romit Roy Choudhury and graduate students Sanorita Dey and Nirupam Roy has demonstrated that these fingerprints exist within smartphone sensors, mainly because of imperfections during the hardware manufacturing process.

In some ways, it's like cutting out sugar cookies. Even using the same dinosaur-shaped cutter, each cookie will come out slightly different: a blemish here, a pock there. For smartphone sensors, these imperfections simply occur at the micro- or nanoscale.

Their findings were published at the Network and Distributed System Security Symposium (NDSS), a major conference on wireless and web security, held last February in San Diego. 

The research also won the best poster award at the HotMobile international workshop in 

2013.

The researchers focused specifically on the accelerometer, a sensor that tracks three-dimensional movements of the phone -- essential for countless applications, including pedometers, sleep monitoring, mobile gaming -- but their findings suggest that other sensors could leave equally unique fingerprints.

"When you manufacture the hardware, the factory cannot produce the identical thing in millions," Roy said. "So these imperfections create fingerprints."

Of course, these fingerprints are only visible when accelerometer data signals are analyzed in detail. Most applications do not require this level of analysis, yet the data shared with all applications -- your favorite game, your pedometer -- bear the mark. Should someone want to perform this analysis, they could do so.

The researchers tested more than 100 devices over the course of nine months: 80 standalone accelerometer chips used in popular smartphones, 25 Android phones, and 2 tablets.

The accelerometers in all permutations were selected from different manufacturers, to ensure that the fingerprints weren't simply defects resulting from a particular production line.

With 96 percent accuracy, the researchers could discriminate one sensor from another.

"We do not need to know any other information about the phone -- no phone number or SIM card number," Dey said. "Just by looking at the data, we can tell you which device it's coming from. It's almost like another identifier."

In the real world, this suggests that even when a smartphone application doesn't have access to location information (by asking "this application would like to use your current location"), there are other means of identifying the user's activities. It could be obtained with an innocuous-seeming game or chatting service, simply by recording and sending accelerometer data. There are no regulations mandating consent.

To collect the data, the researchers -- as with any would-be attacker -- needed to sample the accelerometer data. Each accelerometer was vibrated using a single vibrator motor -- like those that buzz when a text message is received -- for two-second intervals. During those periods, the accelerometer detected the movement and the readings were transmitted to a supervised-learning tool, which decoded the fingerprint.

"Even if you erase the app in the phone, or even erase and reinstall all software," Roy said, "the fingerprint still stays inherent. That's a serious threat."

At this point, however, there is no absolute solution. Smartphone cases made of rubber or plastic do little to mask the signal. Deliberately injecting white noise in the sensor data can smudge the fingerprint, but such noise can also affect the operation of the application, making your pedometer inaccurate and functionally useless.

If accelerometer data were processed directly on the phone or tablet, rather than on the cloud, the fingerprint could be scrubbed before sending information to the application.

That is, the pedometer application might only receive basic information like "300 steps taken," rather than receiving the raw accelerometer data. This, however, imposes a load on the phone's processor and, more importantly, reduces the phone's battery life.

The research also suggests that other sensors in the phone -- gyroscopes, magnetometers, microphones, cameras, and so forth -- could possess the same types of idiosyncratic differences. So even if, at a large scale, the accuracy of accelerometer fingerprints diminishes, when combined with prints from other sensors, an attack could be even more precise.

"Imagine that your right hand fingerprint, by some chance, matches with mine," Roy Choudhury said. "But your left-hand fingerprint also matching with mine is extremely unlikely. So even if accelerometers don't have unique fingerprints across millions of devices, we believe that by combining with other sensors such as the gyroscope, it might still be possible to track a particular device over time and space."

For smartphone users and e-book readers, smartwatch wearers and tablet devotees, perhaps the most critical take-home message, in the short run anyway, is the importance of vigilance.

"Don't share your accelerometer data without thinking about how legitimate or how secure that application is," Dey said. "Even if it's using only the sensor data, still it can attack you in some way. The consumer should be aware."

Source: University of Illinois College of Engineering

Glove shows its true colors: Identifies poisons on contact

The sensor glove turns blue in the presence of hazardous substances. Credit: © Fraunhofer EMFT

Security takes top priority in laboratories and in production. In the future, employees exposed to risks will only have to put on a glove in order to receive a toxic substance warning: This textile identifi es poisonous substances, and points them out immediately.

Employees in chemical production, the semiconductor industry or in laboratories are frequently exposed to harmful substances. The problem: Many of these aggressive substances are imperceptible to human senses, which makes handling them so risky. That's why there is a broad range of solutions that employers can use to protect their staff from hazardous substances -- from highly sensitive measuring equipment to heat imaging cameras. Soon, this spectrum will be enhanced by one more clever solution that is easy to handle, and that dispenses with a power supply. Researchers at the Fraunhofer Research Institution for Modular Solid State Technologies EMFT in Regensburg have engineered a glove that recognizes if toxic substances are present in the surrounding air.

The protective glove is equipped with custom-made sensor materials and indicates the presence of toxic substances by changing colors. In this regard, the scientists adapted the materials to the corresponding analytes, and thus, the application. The color change -- from colorless (no toxic substance) to blue (toxic substance detected), for example -- warns the employee immediately. "By synthesizing the adapted color sensor materials, we can detect gases like carbon monoxide, for example, or hydrogen sulfide. Still, this protective gear represents only one potential area of application. Sensor materials could also be deployed for the quick detection of leaks in gas lines," explains Dr. Sabine Trupp, head of the Fraunhofer EMFT Sensor Materials group. The researcher and her team will exhibit this occupational safety article of clothing at Fraunhofer's joint exhibition booth (Hall 12, Booth 537) at the Sensor + Test trade show in Nuremberg from May 14 to 16.

Tailor-made indicator dyes

The warning signal is triggered by an indicator dye integrated into the glove that reacts to the presence of analytes, in this case, the toxic substances. The experts at EMFT used a variety of techniques in order to furnish textiles with sensor-activated dyes. The sensor-activated dyes are applied to the clothing with the customary dye and print process, for example, by affixing them in an immersion bath. Previously, the researchers used targeted chemical modification to adapt the color molecules to the fiber properties of the respective textile. Alternatively, the textiles can also be coated with sensor particles that are furnished with sensor dyes. For this purpose, the scientists integrated the dye molecules either into commercial pigments or they built them up on an entirely synthetic basis. The pigments are then manufactured according to the customary textile finishing process, for instance, the sensor particles are also suitable for silkscreening. "Which version we opt for depends on the requirements of the planned application," says Trupp.

The challenge lies foremost in the tailored development of sensor dyes. "The dye molecule must detect a specific analyte in a targeted manner -- only then will a chemical reaction occur. Moreover, the dye must adhere securely; it cannot disappear due to washing. We aim for the customer's preferences in the color selection as well. All of these aspects must be kept in mind when developing the molecule and pigment properties," explains Trupp.

The expert already has new ideas about how the solution could be developed further. For example, a miniaturized sensor module, integrated into textiles, could record toxic substances, store the measurement data and even transmit them to a main unit. This way, you could document how frequently an individual within a hazardous environment was exposed to poisonous concentrations over a longer period of time.

The researchers also envision other potential applications in the foodstuffs industry: In the future, color indicator systems integrated into foils or bottle closures are intended to make the quality status of the packaged foods visible. Because the sell-by date does not represent a guarantee of any kind. Foodstuffs may often spoil prematurely -- unnoticed by the consumer -- due to a packaging error, or in the warehousing, or due to disruptions in the refrigeration chain. Oil-based and fat-containing products are specifically prone to this, as are meats, fish and ready meals.

Source: Fraunhofer-Gesellschaft

Sensors that improve rail transport safety

Cloud-supported sensor network for the condition-based maintenance of rail vehicles.
Credit: © Fraunhofer IZM

A new kind of human-machine communication is to make it possible to detect damage to rail vehicles before it's too late and service trains only when they need it -- all thanks to a cloud-supported, wireless network of sensors.

A train running on damaged wheels could easily be heading for serious trouble. This is why German national rail corporation Deutsche Bahn continuously monitors the wheelsets of its intercity express trains -- a process that costs a considerable amount of time and money. 

Researchers at the Berlin-based Fraunhofer Institute for Reliability and Microintegration IZM are collaborating with industry partners to develop a solution that ensures a great safety while reducing effort and cost. "We want to root out any damage early on and move away from maintenance at set intervals in favor of condition-based maintenance," explains Dr. Michael Niedermayer, microsystems engineer and head of the IZM's Technology-Oriented Design Methods working group. He is also project coordinator for "Mobile Sensor Systems for Condition-Based Maintenance," or MoSe for short.

Seamless monitoring

It's all based on a cloud-supported, wireless network of sensors. Every axle and undercarriage on a train is fitted with small radio sensors, which collect data on the condition of wearing parts. These data are then transferred to the online maintenance cloud, where the measurement and analysis data are encrypted and stored ready for use. The sensors can detect even the tiniest scratch on a ball bearing. As Niedermayer says, "Here we have sensor nodes that can capture even the slightest variations in vibration. We call this in-depth diagnosis." As a result, repairs can be made before anything works its way loose and causes damage.

"What's remarkable about this approach is that it allows everything to be monitored with the train in service, rather than having to inspect it at the rail yard. And in any case, visual checks are not 100 percent reliable," says Manfred Deutzer from project partner Deutzer Technische Kohle GmbH. Although there are wired sensors out there that can be used to examine rail vehicle chassis for wear and tear, these fail to match the high diagnostic quality standards the MoSe developers are striving for.

Using the new method, it is possible to get precise data on, say, whether an axle bearing will have to be replaced three months down the line, which avoids the need to replace it prematurely just in case. The latter is just as uneconomical as the custom of overhauling wheels at preset intervals with a view to resolving any wheel flats that could damage rails. 

"Wheels can tolerate such repairs no more than three times before they have to be scrapped," Deutzer reports. "It would make more sense and cost less to grind only those wheels we know actually turn poorly. The problem is that there has never been a suitable way of checking for wheel flats." MoSe is to change all that and much more besides.

"Not only do we intend to improve diagnostics, a top priority is also to process the data collected in as detailed and tailored a manner as possible," says Niedermayer. The idea is to provide train drivers with all relevant data (for instance about critical wheel damage), diagnostic technicians with detailed measurement data so they can assess how fast gear damage is progressing, and designers with measurement statistics covering wear to all parts, enabling them to improve the technical design of the next product generation. Making sure everyone involved receives the data they need in a form they can work with right away involves developing some clever diagnostic algorithms. "Yet another advantage is that wireless sensors can be easily retrofitted," adds Niedermayer.

What's also new is that the system can adapt to the different rotational speeds of the parts being examined -- such as the wheels on a train -- and in doing so, deliver incredibly precise data at whatever speed the train happens to be traveling. It used to be that sensors were designed to work at constant rotational speeds. Although this setup may be easier to manage, it means that the diagnostic quality suffers. Thanks to analysis algorithms, this is set to change. But developing these algorithms is a balancing act: "Since the system is intended to work without batteries, the algorithms mustn't drain unnecessary energy by using up excessive computing power," explains Niedermayer. As MoSe uses energy harvesting, it can tap energy from the vibrations and heat generated as the parts rotate.

Over the next couple of years a prototype will be developed that will be tested in a tram run by the German city of Brandenburg an der Havel. The system could then be used for monitoring purposes in suburban or long-distance trains.

Source: Fraunhofer-Gesellschaft

Wearable tech for battlefield, people at risk for heart attacks

The wearable system, under development by Sentient Science and the University at Buffalo, includes electrodes that relay data to a sensor, which connects with a remote computer network.
Credit: University at Buffalo

Wearable devices can count the steps you take and the calories you burn. But can they help soldiers in the field? Or prevent someone from having a heart attack?

Researchers at Sentient Science and the University at Buffalo say yes.

The sensor and software development company is working with UB engineering professor Albert H. Titus to create wearable technology that fuses real-time medical and physiological data with computer models. The system would then send personalized alerts indicating when the individual's level of stress, fatigue and resilience may put them in danger.

The work is funded by a $150,000 grant from the Office of Naval Research's Small Business Technology Transfer program, which enlists small businesses and research institutions to develop technology with military and commercial applications.

"Whether carrying 100 pounds of gear up a mountain or avoiding makeshift bombs, today's soldiers face incredible physical and mental stress," said Titus, PhD, professor and chair of UB's Department of Biomedical Engineering. "Our wearable system aims to measure how the body reacts to those challenges and combine that information with algorithms designed to help keep soldiers as safe as possible."

The wireless system, which is under development, will feature a series of electrodes that measure heart rate, brain activity and other vital signs. The electrodes may be attached to the skin like a Band-Aid or sewn into clothing that hugs the skin -- researchers are still deciding the best method.

The electrodes will relay information to a sensor (slightly smaller than a dime, attached to the skin like a patch), which will deliver that information to a remote computer network.

"It's like the hospital when you have a bunch of wires and equipment monitoring a patient. We're taking that technology and compressing it into a lightweight, wireless system," said the project's principal investigator Jennifer Haggerty, a research scientist and implementations manager at Sentient. Haggerty is an alumnus of UB.

As the information enters the computer network, it will fuse with Sentient's DigitalClone Live software, which has been validated by NASA and used to test the materials and components in the Hubble telescope, the F-35 fighter jet, wind turbines and other products.

The software includes complex algorithms that consider things like the terrain, weather and other environmental information, as well as the soldier's activity level. It will analyze the data and send personalized health alerts to soldiers and, if necessary, emergency medical facilities in the field. The idea is to improve soldiers' cognitive and physical abilities, making them more resilient and less prone to physical and psychological injuries.

In addition to serving the armed forces, the technology has commercial applications as a health-monitoring device. Sentient is exploring how the sensor can be applied to everyday items such as baseball caps. The individual wearing the cap would receive personalized health alerts regarding their risk of suffering a heart attack and other potential danger.

Source: University at Buffalo