Extending IoT with the Raspberry Pi

Recently, the Raspberry Foundation has updated its embedded Compute Module with a faster ARM processor. This will help developers and businesses build new IoT devices. The new Compute Module 3 (CM3) comes with a powerful new option and embedded compute capabilities for device makers interested in the Internet of Things (IoT).

Although not to be confused with the Single Board Computer, the Raspberry Pi (RBPi), with which the CM3 also shared the latest update, is a tiny form-factor ARM-powered SBC originally developed to help both kids and adults learn computer programming.

Launched with the same form factor as that of the RBPi, the CM3 was specifically targeted at business and industrial users. While the RBPi is a completely standalone device, the CM3, on the other hand, is a module intended for plugging into a separate Printed Circuit Board. The primary aim of the Compute Module is to let vendors and developers develop customized products quickly.

The new CM3, like the RBPi3, also uses the same Broadcom system-on-chip (SoC), the ARM BCM2837. The ARM Cortex A53 design forms the base for the SoC BCM2837, which is a 1.2 GHz, quad-core chip running on 64 bits. As a bonus, the standard CM3 has an on-module eMMC flash memory of 4 GB.

Other than the standard CM3, the Raspberry Pi Foundation also has a CM3L or Compute Module 3 Lite version. With the CM3L, users can wire up their choice of an SD card interface or eMMC memory. While the CM3L also comes with the same BCM2837 SoC, the on-board RAM is still restricted to 1 GB only.

Along with the CM3 and the CM3L, the Raspberry Pi Foundation is also releasing the new Compute Module IO Board V3 (CMIO3). This will provide developers with a starter breakout board to which they can connect their Compute Module.

The CMIO3 offers designers a starting template for designing with the Compute Module, providing them with a quick method to experiment with the hardware and to build and test a system. Once the experiment succeeds, they can proceed with the expense of fabricating a custom board. The CMIO3 also provides the necessary USB and HDMI connectors to make up the entire system that boots up and runs the Raspbian OS, or any other OS you select.

Although the Raspberry Pi Foundation has only recently released new Command Modules, next generation large-format displays based on the modules are already available from the consumer electronics vendor NEC, as they had early access to them.

The idea behind the Compute Modules is to provide a cost-effective and easy route to making customized products using the hardware and software platforms of the RBPi. The modules provided the team in the garage the same technology that the big guys already had. The Module takes care of the complexity of routing the core power supply, the high-speed RAM interface, and the processor pins, while allowing a simple carrier board provide the basics in terms of form factor and external interfaces. The form factor of the module follows that of the inexpensive, easily available, standard DDR2 SODIMM.

Powering the Pacemaker from Solar Energy

Those suffering from certain ailments of the heart, have to have a pacemaker installed. Surgeons place this tiny medical device in the chest or abdomen of the patient and it helps to control abnormal heart rhythms. The device generates electrical pulses and prompts the heart to beat at a normal rate. Power comes from implanted Lithium-iodide or Lithium anode cells, with Titanium as the encasing metal. The downside to this arrangement is the cells need replacement once they are discharged, and that means periodic surgeries.

To avoid repeated surgeries, scientists prefer using solar cells placed under the skin for continuously recharging the implanted electronic medical devices. According to Swiss researchers, a 3.6 square centimeter solar cell generates enough power necessary to keep a typical pacemaker running through the year.

Lukas Bereuter of Bern University Hospital and his team from the University of Bern in Switzerland have presented a study that provides real-life data on the potential of using solar cells to power implanted devices such as deep brain stimulators and pacemakers. Lukas is confident it will become commonplace to wear power generating solar cells under the skin. This will save patients the discomfort of undergoing repeated surgeries to change batteries of such life-saving devices. Lukas has reported the findings in Springer’s journal Annals of Biomedical Engineering.

Electronic implants are invariably battery powered, with their size depending on the volume of the battery necessary for an extended lifespan. When the battery exhausts is power, it must either be charged or changed. This necessitates expensive and stressful medical procedures involving implant replacements, along with the risk of medical complications for the patient. The implantable solar cell is attractive as it converts the light from the sun penetrating the skin surface to generate enough energy for recharging the medical devices.

Lukas and his colleagues have developed devices specially designed for solar measurement to investigate the feasibility of rechargeable energy generators in real-life situations. The devices measure the output power generated. According to the team, 3.6 square centimeter cells generated enough power and were small enough for the intended implantation.

The team tested ten cells by covering them with optical filters for simulating the properties of human skin. This influenced the amount of sunlight penetrating the skin. A test group of 32 volunteers wore the cells on their arm for one week during summer, autumn, and winter months.

According to the team, the tiny cells were able to generate power more than the 5-10 microwatts required by a regular cardiac pacemaker, irrespective of the season. The lowest power output the team recorded on average was 12 microwatts. The overall mean power obtained from the cells was enough to power a pacemaker completely, or at least extend the lifespan of an active implant. Furthermore, the use of solar cells or energy-harvesting devices for powering an implant dramatically reduces the size of the device, while at the same time, helps to avoid device replacements.

According to Lukas, the results of the study may be suitably scaled up and applied to other mobile applications, especially solar powered applications on the human body. The only aspect that requires attention is the efficiency and catchment area of the solar cell, and the thickness of the skin covering it.

A Raspberry Pi DAC for the Audiophiles

Raspberry Pi (RBPi) users have several choices for using Digital to Analog Converters (DACs) when listening to music. Two of the latest DACs available in the market are discussed here. One of them is the DragonFly series from AudioQuest and the other is i-Sabre from Audiophonics. Both offer stronger and more meaningful connections between music enthusiasts and the albums, songs, videos, and artists they adore.

DragonFly USB DAC, Preamp, and Headphone Amplifier

The multi-award-winning DragonFly USB DAC, preamp, and headphone amplifier from AudioQuest is a popular product that effectively bridges the gap between extreme audiophiles and mainstream music lovers.

Plugging into the USB port of a computer, including single board computers such as the RBPi, the DragonFly bypasses the compromised audio circuitry of the computer to deliver clearer, cleaner, more natural sounding music and sound to headphones, powered speakers, and complete audio systems.

Two versions of the DragonFly are available—the Black, and a higher-performing Red version. Both versions offer 32-bit digital performance using the Microchip PIC32MX micro-controller, which draws 77% less current from what the previous micro-controllers did that AudioQuest was using. Both versions offer naturally detailed, more authentic sound thanks to the improved ESS Sabre DAC chips working at 32-bits, and using minimum-phase filtering. The DragonFly Red has the latest ESS headphone amplifier and a bit-perfect digital volume control incorporated on the 9016 DAC chip. This ensures maximum fidelity, improved signal-to-noise ratio, and high dynamic contrast.

Both versions of the DragonFly generate enough power to drive all preamplifier input circuits successfully, and they are compatible with a wide range of efficient headphones. While the Black outputs 1.2 Volts, the Red has a 2.1 Volt output and is further compatible with a wider range of power-hungry, low-efficiency models.

The iSabre ES9023

This product from Audiophonics is an I2S DAC, suitable for RBPi model 2, and it has a high precision clock onboard. It produces better quality sound as compared to the DragonFly USB DAC. The clarity is very good and the iSabre gives offers good stereo placement along with detailed high frequency reproduction. This makes the sound very transparent and optimally realistic.

The iSabre ES9023 ideally transforms the RBPi A+, B+, or 2.0 into a high-definition music file player. The converter offers a high value for money and has direct analog outputs on high-quality headers.

The converter has ultra-low noise regulators, OS-CON capacitors, which gives the DAC its musical sound and rich mono details. The HAT format allows direct access to the RBPi GPIO pins, but users have the additional choice to use I2S inputs or the USB interface.

To use the DAC, you may need to install the Hifiberry or the Hifiberry+ driver on the RBPi. The appropriate I2S card will show up on the list of audio devices in the Playback menu.

The cornerstone of a top-quality audio system depends on the accurate conversion of music and sound from the digital to the analog world. The two DACs described above do this conversion admirably. An oversampling process eliminates all the clocking inconsistencies or jitter commonly found in typical digital-to-analog conversions.

The Law, Big Data, and Artificial Intelligence

We use a lot of electronic gadgets in our lives, revel in Artificial Intelligence, and welcome the presence of robots. This trend is likely to increase in the future, as we continue to allow them to make many decisions about our lives.

For long, it has been a common practice using computer algorithms for assessing insurance and credit scoring among other things. Often people using these algorithms do not understand the principles involved, and depend on the computer’s decision with no questions asked.

With increasing use of machine learning and predictive modeling becoming more sophisticated in the near future, complex algorithm based decision-making is likely to intrude into every field. As such, expectedly, individuals in the future will have further reduced understanding of the complex web of decision-making they are likely to be subjected to when applying for employment, healthcare, or finance. However, there is also a resistance building up against the above, mainly in the EU, as two Oxford researchers are finding out from their understanding of a law expected to come into force in 2018.

With increasing number of corporations misusing data, the government is mulling the General Data Protection Regulation (GDPR), for imposing severe fines on these corporations. GDPR also contains a clause entitling citizens to have any machine-driven decision processes explained to them.

GDPR also codifies the ‘right to be forgotten’ while regulating the overseas transfer of private data of an EU citizen. Although this has been much talked about, not many are aware of two other clauses within GDPR.

The researchers feel the two clauses may heavily affect rollout of AI and machine learning technology. According to a report by Seth Flaxman of the Department of Statistics at the University of Oxford and Bryce Goodman of the Oxford Internet Institute, the two clauses may even potentially illegalize most of what is already happening involving personal data.

For instance, Article 22 allows individuals to retain the right not to be subject to a decision based solely on automatic processing, as these may produce legal complications concerning them or affect them significantly.

Organizations carrying out this type of activity use several escape clauses. For instance, one clause advocates use of automatic profiling—in theory covering any type of algorithmic or AI-driven profiling—provided they have the explicit consent of the individual. However, this brings up questions whether insurance companies, banks, and other financial institutions will restrict the individual’s application for credit or insurance, simply because they have consented. This can clearly have significant effect on an individual, if the institutes turn him or her down.

According to article 13, the individual has the right to a meaningful explanation of the logic involved. However, organizations often treat the inner working of their AI systems and machine learning a closely guarded secret—even when they are specifically designed to work with the private data of an individual. After January 2018, this may change for organizations intending to apply the algorithms to the data of EU citizens.

This means proponents of the machine learning and AI revolution will need to address certain issues in the near future.

Wordery Uses the Raspberry Pi for Book-Wrangling

Among the mass of technologically advanced stuff done with the popular single board computers, the Raspberry Pi (RBPi) has also been helping booksellers. At Wordery, an online bookshop, Jeff Podolski, an IT and network technician, is using the RBPi at their warehouse.

Wordery has over 10 million book titles in their list, including several on RBPi. Over the last few years, they have been working on improving their productivity and customer service drive. For their sorting and distribution operation, they have taken up a greater automation. This is allowing them to track packed items and offer interactive feedback to their staff. For this, they needed PCs on the desks they use for packing and mailing. However, a PC with a screen and barcode scanner would take up considerable space on the desk and consume a lot of power. Therefore, their IT team had the brainwave of using RBPis instead.

Jeff and his team conducted initial tests using an RBPi and a standard PC. They settled on using a setup with the 7-inch official LCD screen and case for the RBPi, and used a USB barcode scanner. This setup saved more than four-fifths of the space a PC would have used up on the desk, while using substantially less power.

However, an RBPi with screen and scanner, left unsecured on the desk, was likely to be knocked and bumped by items being packed and possibly smashed on the warehouse floor. This led Jeff to use a tablet-mounting arm, originally designed for wheelchairs. He clamped the arm to a table, and attached a backboard to the bracket meant to hold the tablet.

Making use of the rear mounting screw holes, Jeff was able to attach the RBPi and screen to the bracket. By routing and tidying the cable layout, Jeff and his team had a low power, small, easily movable interactive terminal, which all the staff in the warehouse could use.

The success of the project led to an installation of over 40 of these terminals in the warehouse, with benefits clearly visible. The warehouse has since processed record volumes using the terminals. They have improved on the previous year’s performance by 11%. Since they set up the RBPi terminals, the warehouse has been handling additional volumes, and packing productivity has increased by 30%. According to Jeff, the resounding success of the RBPi terminals has encouraged their use elsewhere in the building also, further reducing their equipment costs and power consumption.

With the RBPi community and the team at ModMyPi helping with the sourcing of the kit and cables in large volumes, Jeff’s team did a great job of modifying the tablet arm to make it fit another purpose. The RBPi Thin Client Project made the simple configurable thin client for project, while Martin Kirst helped to make the terminal emulator screens more readable and added new functionality to the units. By making the interaction wireless, the terminals can be moved to places where they are currently needed.

This project proves the RBPi can be used for making automation cheaper, more accessible, and much more flexible in an industrial setting.

What is a Programmable Logic Controller?

Programmable Logic Controllers (PLCs) are miniature industrial computers. The hardware and software in a PLC are meant to perform control functions. Specifically, a PLC helps in the automation of industrial electromechanical processes. This includes controlling machinery on assembly lines in a factory, rides in an amusement park, or instruments in a food processing industrial establishment.

Most PLCs are designed to facilitate multiple arrangements of analog and digital inputs and outputs. They typically operate with extended temperature range, resistance to impact or vibration, and immunity to electrical noise and disturbances. The basic sections of a PLC usually consist of two sections—the first, the central processing unit (CPU), and the second, an Input/Output (I/0) interface system.

The CPU uses its processor and memory systems to control all system activity. Within the CPU is the micro-controller, memory chips, and other integrated circuits for controlling logic, monitoring, and communications. The CPU may operate in different modes—programmable or run. The programming mode allows the CPU to accept changes to the logic received from another computer. In the run mode, the CPU will execute the program to operate the process.

In the run mode, the CPU will accept input data from connected field devices such as switches, sensors, and more. After processing the data, it will execute or perform the control program stored in its memory system. As the PLC is a dedicated controller, the single program in its memory is processed and executed repeatedly. The scan time, the time taken for one cycle through the program, is typically of the order of one-thousandth of a second. The memory within the system stores the program, while at the same time holding the status of the I/O and provides a means to store values.

Typically, industrial users can fit a wide range of I/O modules to a PLC to accommodate various sensors and output devices. For instance, there are discrete input modules for detecting the presence of objects or events using photoelectric or proximity sensors, limit switches, and pushbuttons. Similarly, with discrete output modules it is possible to control loads such as motors, lights, solenoid valves, mainly to turn them On or Off.

The PLC can be fitted with analog input modules to accept signals generated by process instrumentation such as temperature, pressure, flow, and level transmitters. The modules interpret the signal from their sensors, and present a value within the range determined by the electrical specification of the device.

In the same way, the PLC can use analog outputs to command loads requiring a varying control signal, such as analog flow valves, variable frequency drives, or panel meters. PLCs can also use specialized modules such as serial or Ethernet communications, and high-speed I/O or motion control.

The greatest benefits of a PLC are its ability to change and replicate or repeat the operation of a process while simultaneously collecting and communicating critical information. In the industry, all aspects of a PLC—cost, power consumption, and communication capabilities—are subject to consideration when selecting the right one for the job. Industry automation owes a lot to the PLC or Programmable Logic Controller.

Networked Storage with the Raspberry Pi

With memory going cheap, almost everyone has a plethora of high-capacity hard disks lying around. Networking them makes it super convenient for use, as you can access files from any computer, even if they are remote. However, this can be an expensive proposition, unless you are using a convenient single board computer such as the Raspberry Pi (RBPi).

The RBPi can be used to create a very cheap NAS setup with a few hard drives connected to a network and accessible from anywhere. Apart from the hard drive itself, you will need an RBPi. Although models 1 and 2 may work just fine, they may not be able to provide enough power to operate some hard disk drives. In this context, the RBPi3 offers better support, but you will still be limited to 100 Mbps via its Ethernet, and USB 2.0. However, using a powered USB hub for powering the external hard drives may be another alternative.

You will need to install the operating system for the RBPi on to an 8 GB micro SD card. Use the OpenMediaVault OS, by downloading it from here. Format the SD card to FAT32, and write the image of the downloaded and extracted OS to the SD card.

Now connect peripherals to the RBPi and its power supply. Initially, you will need a keyboard, a monitor, and a local network connection via Ethernet. Power up the RBPi and allow it to complete the initial boot process.

Once completed, you can use the default web interface credentials to sign in—use admin as the username and openmediavault as the password. The login will give you the IP address of the RBPi, and for subsequent log-ins, you will no longer need the monitor and keyboard connected to the RBPi.

At this stage, you can connect the storage devices to the RBPi. On another computer, on the same network, open a web browser and enter the IP address of the RBPi. Enter the same credentials in the web interface that appears, and you will reach the web interface for the OpenMediaVault. This will bring you to the navigation menu.

To get your NAS online, you first need to mount the external drives. In the navigation menu, clicking on File Systems under Storage will allow you to locate your storage drives under the Devices column. Click on one drive to select it and click Mount. Now click Apply to confirm the action. Repeat the steps to mount additional drives.

You will also need to create a shared folder to allow other devices on the network to access the drives. Finally, to allow an external computer on the network share the folders and drives, you must enable SMB/CIFS from Services in the navigation menu. Next, click on the Shares tab and Add the created folders one by one. For each, click Save.

Now that the NAS is up and running, you can access the drives from another computer by mapping them. To access them, the RBPi will ask for login credentials. By default, these are pi as the username and raspberry for the password.

Python Libraries for Machine Learning

Machine learning helps with many practical applications, suitably augmented by deep learning and with extensions of the overall field of artificial intelligence. Many people, with the help of analytics and statistics, are busy navigating the vast universe of deep or machine learning, artificial intelligence, and big data. However, they do not really have to qualify as data scientists, as popular machine learning libraries in Python are available.

Machine learning is promoting deep learning and AI for all kinds of machine assists, including driverless cars, better prevention healthcare, and even better movie recommendations.

Theano

A machine-learning group at the Universite de Montreal developed and released Theano a decade ago. In the machine learning community, Theano is one of the most used mathematical compiler for CPUs and GPUs. A 2016 paper describes Theano as a “Python framework for fast computation of mathematical expressions,” and offers a thorough overview of the library.

According to the paper, development of several software packages build on the strengths of Theano, offering higher-level user interface, making them more suitable for specific goals. For instance, expressing training algorithms mathematically and evaluating the architecture of deep learning models using Theano became easier with the development of Keras and Lasagne.

Likewise, a probabilistic programming framework PyMC3, using Theano, derives expressions automatically for gradients. PyMC3 also generates C-codes for fast execution. That people have forked Theano over two-thousand times, it has almost 300 contributors on GitHub, and it garners more than 25,000 commits, is testimony to its popularity.

TensorFlow

Although a newcomer to the world of open source, TensorFlow is a library for numerical computing and uses data flow graphs. In its first year itself, TensorFlow has helped students, artists, engineers, researchers, and many others. According to the Google Developers Blog, TensorFlow has helped with preventing blindness in diabetes, early detection of skin cancer, language translation, and more.

TensorFlow has appeared several times in the most recent Open Source Yearbook. It has been included as a project in the list of top ten open source projects to watch in 2017. In a tour of Google’s 2016 open source releases, an article by Josh Simmons refers to Magenta, a TensorFlow based project.

According to Simmons, Magenta advances the technology in machine intelligence for music and art generation. It also helps build a collaborative community of coders, artists, and researchers dealing with machine learning. According to another researcher, Rachel Roumeliotis, she lists TensorFlow as a language for powering AI as a part of her roundup of Hot programming trends of 2016.

Anyone can learn more about TensorFlow by watching the live stream of recording from the TensorFlow Dev Summit 2017, or by reading the DZone series—TensorFlow on the Edge.

Scikit-Learn

Spotify engineers at okCupid use Scikit-Learn for recommending music, for helping evaluate and improve their matchmaking system, and for exploring phases of new product development at Birchbox. Scikit-Learn is built on Matplotlib, SciPy, and NumPy. It has 800 contributors on GitHub, and garners almost 22,000 commits.

The Scikit-Learn project website offers free tutorials, where one can read about using Scikit-Learn for machine learning. Alternately, they can watch the PyData Chicago 2016 talk given by Sebastian Raschka.

Super Efficient Diamond Batteries from Nuclear Waste

So far, we have been dumping our dangerous nuclear waste into oceans or deep inside the earth, hoping they will stay there. Now, there is a better way out. Scientists are now confident they can use nuclear waste as a source of energy to convert radioactive gas into diamonds of the artificial type, not as jewelry, but to be used as batteries.

Scientists claim the diamonds can generate their own electrical current. As they are made of radioactive material with long half-life, the batteries could potentially provide power for thousands of years. According to Tom Scott, a geochemist from the University of Bristol in the UK, the batteries will simply produce direct current, without emissions, and without requiring any moving parts or maintenance.

The radioactive material, encapsulated within a diamond, will turn the long-term problem of handling nuclear waste into a nuclear powered battery producing a long-term supply of clean energy. As a demonstration of their claims, Scott’s team has developed a prototype diamond battery using an unstable isotope of Nickel-63 as its source of radiation.

The half-life of Nickel-63 is approximately 100 years. That means after 100 years, the prototype battery would still be retaining about 50 percent of its original charge. However, the scientists claim they have an even better source for making these batteries. They want to use the huge quantities of nuclear waste generated and stockpiled by UK.

From the 1950s through the 1970s, the first generation of Magnox nuclear reactors in the UK used graphics blocks to sustain nuclear reactions. However, the graphite blocks turned radioactive and generated an unstable carbon isotope, the Carbon-14.

Although UK had retired the last of these Magnox reactors by 2015, the decades of power generation has left a huge amount of nuclear byproduct as waste—nearly 95,000 tons of radioactive graphics blocks need to be safely stored and monitored.

Additionally, as Carbon-14 has a half-life of 5,730 years, UK may have to take care of this dangerous waste for a long, long time. However, it also means this material could be used to make batteries that last an amazingly long time—provided scientists could repurpose them into the diamond structure, just as they did with Nickel-63.

Carbon-14 emits only short-range radiation, one quickly absorbed by any nearby solid material. According to Neil Fox, one of the researchers, although touching or ingesting Carbon-14 would be dangerous, encasing it within diamond would prevent any short-range radiation from escaping. Moreover, diamond would offer the ultimate protection, as it is the hardest substance known to man.

The team presented their ideas at a lecture at the University of Bristol, but has yet to publish their research. The researchers claim that although Carbon-14 batteries would be good for low-power applications, their endurance would be on an entirely different scale.

For instance, an alkaline battery weighing 20 grams has an energy density of 700 Joules/gram, giving a life of 24 hours of continuous usage.

On the other hand, a diamond battery with 1 gram of C-14 will deliver only 15 Joules per day. However, it will continue to produce this level of output for more than 5,730 years—giving a total energy density of 2.7 TeraJoules/gram.

Explosion and Damage Proof High Energy Density Batteries

We seem to spend a major part of our waking life charging batteries of our smartphones, laptops, watches, wearables, and more. Although most of our gadgets work at lightning speeds, one common frustrating weakness lingers on—the batteries. Of course, they have improved tremendously in the last fifty years, yet they have retained characteristics such as being toxic, expensive, bulky, finicky, and most maddeningly, short-lived. The quest for a super battery does not end with smartphones alone, rather it continues with electric cars and renewable energy sources such as wind and solar power, holding the keys to a greener future.

Mike Zimmerman, a Professor at the Tufts University just outside Boston, and his team have created what they claim is the next generation of the Lithium-ion battery. The main characteristic of this new type of battery is it is safe to power up cars, phones, and other gadgets.

The current breed of Lithium-ion batteries relies on a liquid electrolyte between their positive and negative electrodes. When hit or pierced, the leaking liquid electrolyte makes the battery vulnerable to fire or even explosion. The Galaxy Note 7 phones from Samsung aptly demonstrated this—it had spontaneously exploding batteries that would catch fire as the battery casing caused one of the electrodes to bend, increasing the risk of short circuits.

However, Zimmerman’s battery won’t explode or catch fire even if most of it has been chopped away. Rather, it will continue to power the device. It will endure repeated damage without risk of fire or explosion, thanks to its solid electrolyte.

Besides being the Holy Grail for safe batteries, solid electrolytes can hold more charge for a given volume compared to what the liquid electrolytes can. The solid plastic electrolyte developed by Professor Zimmerman does not allow the formation of dendrites—tendrils of Lithium that originate from the electrodes and spread throughout the electrolyte—that cause the dangerous short-circuits.

Other researchers have been looking at charging times for batteries and trying to speed up the process. Rather than improve the charging times for Lithium-ions, scientists have been experimenting with different types of batteries, and claim to have hit success with batteries made from Aluminum foil.

Although research on Aluminum batteries has continued for years, most prototypes were incapable of withstanding more than a few dozen charges, before they lost their potency. Most cellphones, on the other hand, sustain more than a thousand charge cycles before their capacity deteriorates.

The Aluminum foil batteries can sustain a staggering 7,000 charge cycles. They are also safe—researchers could drill a hole into the battery while it was operating, and unlike a Lithium-ion battery, the Aluminum battery did not explode. However, Aluminum batteries are not yet ready for the market, as they are heavier than Lithium-ion batteries of the same capacity.

The researchers used a solution of Aluminum Trichloride dissolved in an organic solvent containing Chlorine. Although the Aluminum atom has three electrons in its outer shell, the present chemistry utilizes only one of them. Lithium atoms also do the same, as they have only one electron in their outer shell. However, Lithium atoms are only one-third as heavy as the Aluminum atoms.