Researchers develop Sodium Battery at par with Lithium Battery

A research carried out by researchers at Washington State University and Pacific Northwest National Laboratory has led to development of a new sodium-ion battery. The new battery holds as much energy and works as well as chemistries of some commercial lithium-ion batteries. Thus, this makes for a potentially viable battery technology developed out of abundant and cheap materials.

Consequently, this has led to the creation of one of the best sodium-ion battery, reports the team. The battery delivers capacity and successful recharging comparable to some lithium-ion batteries, wherein it saves 80 percent of the charge after 1,000 cycles.

The research is published in the journal ACS Energy Letters.

“The research is a major development for sodium-ion batteries,” stated director of Energy at Office of Electricity, Department of Energy in the US. The capability has displayed great interest of battery manufacturers to replace lithium-ion batteries with sodium-ion ones for many applications.

Expensive and Rare Materials used for Lithium Battery pins need for Alternative

Meanwhile, lithium-ion batteries are ubiquitous, which find in use in many applications. This includes laptops, cell phones, and electric vehicles. But lithium-ion batteries are made of materials such as lithium and cobalt that are rare and expensive, and are mostly found outside the US.

As the demand for electric vehicles and electric storage spikes, the availability of these materials will be difficult and would possibly be expensive. For such reasons, lithium-ion batteries would also not be able to keep up with the massive growing demand for power grid energy storage.

Whilst, sodium-ion batteries, made from inexpensive, abundantly available and sustainable sodium from the earth’s crust or oceans could make for a viable option for large-scale energy storage. However, low capacity of energy storage as compared to lithium batteries is a drawback.

New IoT Labels to reveal Consumers which Devices are spying on them

In a ground-breaking development, IoT labels will help consumers with the security and privacy practices of new IoT devices. The finding is an effort of a team of researchers at Carnegie Mellon University CyLab who developed a prototype security and privacy nutrition label, and has showcased to work well with user tests. The finding is published in the proceedings of the IEEE symposium on Security and Privacy.

Besides this, the team also developed an IoT label generator for manufacturers which will allow them to easily create labels for their devices.

“As per survey results, vast majority of individuals are concerned with security and privacy practices of devices,” said the lead author of the study. The display of information pertaining to security and privacy practices of devices should be concise and understandable, same as nutrition label on food products.

Survey reveals consumers Wary to share Personal Data

Meanwhile, a recent survey conducted by the Economist Intelligence Unit reveals a large percentage of participants are uncomfortable with sharing of personal data with third-parties without consent. Of this participating group, ninety-two percent opined it is important for consumers to know when personal data is collected.

Despite this, consumers do not have a clue about the privacy and security policies of devices at the time of purchase.

To throw light on the label, it consists of a primary layer meant to be displayed on the outside of a device’s box. This conveys the most important information pertaining to the type of data the device collect, the purpose of the data, and information of third-party with whom the data is shared.

In the next step, scanning a QR code on the primary layer provides consumers access to secondary layer of the label. This layer provides additional information.

Smarter Use of Energy Key to Greener Future, says study

Despite a slew of innovations to optimize efficiency of electric energy, which includes LED lightbulbs, electric vehicles, programmable thermostats, and high-density insulation, in the U.S., about two-thirds of the energy produced is lost in inefficiency.

Meanwhile, it’s a dire number of scientists and economists who work on the barrier between people and sustainable future, nonetheless, modern data management is helping to reduce it.

“The amount of energy available is abundant, but it is not used wisely,” says a researcher at University of Georgia Regents.

It is commonly observed, heating rooms when there is no one in them, or even the use of wrong lighting settings for the use of the room. Energy inefficiency of some of these might be minor, but, it can make a big impact if these changes throughout a large institution or across a number of institutions.

The researcher at University of Georgia Regents and his research co-author pioneered energy informatics across a number of universities. For the past decade, the focus has been on research and training students to use big data analysis to optimize energy use systems in universities, skyscrapers, factories, and other large scale energy users.

Initiatives of Department of MIS favor Energy Informatics Studies

“Energy informatics is embraced by many universities around the world, and a journal and conference have been created with large number of scholars contributing to this stream of research,” stated the head of the department of management information systems at Terry College of Business.

Moreover, it is exciting that many undergraduate and graduate students get the opportunity to learn about energy informatics through the elective class that department of management information systems has been offering since 2011.

The attention now is on energy informatics of greenhouses to produce fresh flowers and vegetables.

New AI System enables Smart Machine Maintenance, detects unknown faults too

In a new research, a team of researchers have been able to combine artificial intelligence with sensors. The AI-based maintenance system gathers data on industrial machinery, thus helping to make sensors smart. The system features to detect damage, wear, and error states. And, it can uniquely recognize when a previous unknown state of the machine arises, thereafter, learns from them and assigns to their underlying root cause.

Using this approach, small and mid-sized enterprises can automate their machine maintenance and service operations. This allows these companies to plan more precisely and avoid unpleasant surprises.

System features Detection and Interpretation of Changes in Machine

Meanwhile, vast number of sensors constantly collect data from industrial machinery. And, these data sets can be of immense use. When a machine operates normally, the way it shakes, hums, vibrates is unique to that device. However, when machine components start to wear out, these characteristics undergo subtle changes. Slight changes in vibrational behavior, minute temperature fluctuations, and minor shifts in measurement data all act as early signals of warning that indicate when a component begins to show signs of wear. Thus, the subtle variations needs to be detected within the sea of data that is produced.

A single sensor can produce a terabyte of raw data in just few days. Nonetheless, in addition to detect changes, it is important to know how to interpret these changes.

The team has been working with partners in academia and industry to develop a system that is able to extract valuable signal data from vast quantities of data being generated. For this, the system independently assigns signal patterns for specific damage, wear or error states, thus, makes the machine’s status permanently visible.