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Engineering

Stanford Engineers Create Water Droplet Based Computer

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Stanford engineers create computer based on water droplets moving in a magnetic field

A team of Stanford engineers led by assistant professor of bioengineering Manu Prakesh have created a miniature computer which operates using the physics of water droplets and magnetic fields.

The idea came to Prakash almost a decade ago, when he was a graduate student. Now, using his expertise in manipulating droplet fluid dynamics, he’s managed to create one of the fundamental components of a computer – an operating clock.

So why is a clock so important? And how can you use water droplets to make one? To answer the first question, consider this: in order to function properly, any computer program requires several operations running simultaneously and in a step-by-step manner. If the clock doesn’t work as it should, the operations can run out of sync, and your computing machine is pretty much useless.

Now, how do you get drops of water to act like a clock? Prakash and his team needed to make the mechanism easy to operate, but also scalable, ensuring a large number of droplets could be manipulated simultaneously in the future. The solution was to use a rotating magnetic field. The researchers first built an array of tiny iron bars on a glass slide (a setup somewhat reminiscent of a Pac-Man maze). A layer of oil was placed above, and a blank glass slide was then laid on top. Finally, individual water droplets infused with tiny magnetic nanoparticles was added to the mechanism. Now all the scientists had to do was place the setup within a magnetic field generated by system of coils, and periodically flip the field. Every time this happens, the polarity of the bars reverses, drawing the droplets into a different, pre-determined configuration. Each of these flips counts as one clock cycle, and every drop advances exactly one step per cycle.

Water droplet Based Computer

The presence of absence of a water droplet counts as a 1 or a 0, which is all you need for the binary code a computer understands. According to Giorgios Katsikis, a member of Prakash’s team, “following these rules, we’ve demonstrated that we can make all the universal logic gates used in electronics, simply by changing the layout of the bars on the chip.”

You might be thinking, ”even if it works, this is an awfully slow and cumbersome way of doing computations.” And you’d be right. While the droplet computer can theoretically perform any operation an electronic computer can do, it does it at a much slower rate. However the Stanford team aren’t looking for new ways to build computers, but rather for novel methods of manipulating matter at the very small scales. With the basic design now figured out, scientists can scale it to manipulate potentially millions of droplets at a time, and at increasingly faster rates. One application could involve turning the droplet computer into sort of a miniature chemistry or biology lab, using the water particles to carry chemicals and thus providing scientists with a lot more control over these reactions than ever before.

The Stanford team also plans to make a design tool for the setup publicly available, so that groups of researchers from anywhere in the world could explore its capabilities.

Who doesn’t enjoy listening to a good story. Personally I love reading about the people who inspire me and what it took for them to achieve their success. As I am a bit of a self confessed tech geek I think there is no better way to discover these stories than by reading every day some articles or the newspaper . My bookcases are filled with good tech biographies, they remind me that anyone can be a success. So even if you come from an underprivileged part of society or you aren’t the smartest person in the room we all have a chance to reach the top. The same message shines in my beliefs. All it takes to succeed is a good idea, a little risk and a lot of hard work and any geek can become a success. VENI VIDI VICI .

Artificial Intelligence

The Holodeck from Star Trek has been replicated as a virtual training environment for advanced robots of the future

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Many Star Trek enthusiasts have pondered the possibilities of encountering a new species, swiftly teleporting out of an uncomfortable social situation, or zooming through space at warp speed (just be cautious not to exceed warp 10!). Many of the impressive technological advancements portrayed in the franchise are still confined to the realm of fiction. However, certain innovations inspired by Star Trek have indeed materialized in the real world. Thanks to a group of brilliant minds at the University of Pennsylvania, we can now proudly include a holodeck on that remarkable list.

Let me clarify something as we share your disappointment. We’re not referring to a futuristic world where humans can engage with characters in a holographic environment. That kind of technology is still a long way off. A team at Penn Engineering and their collaborators created the Holodeck system, which has the remarkable ability to create a wide variety of 3D environments. All you need to do is inquire.

“Language can be utilized to exert control,” stated Yue Yang, one of the co-creators. You have the ability to effortlessly describe any environments you desire and train the AI agents that inhabit them.

The holodeck system portrayed in Star Trek series such as The Next Generation and Voyager is a highly adaptable virtual environment capable of transforming simple verbal commands into fully simulated worlds. These types of environments, although smaller in scale, have significant applications in training robots.

Developing a virtual world can be quite time-consuming. “Creating these environments requires manual effort, with artists dedicating a significant amount of time to building just one,” Yang explained. To effectively train a robot to navigate real life, it is crucial to expose it to a diverse range of environments for testing purposes. Generative AI, which has gained significant popularity in recent months, appeared to be the obvious solution.

“AI systems such as ChatGPT undergo extensive training on an enormous amount of textual data, while image generators like Midjourney and DALLE are trained using a vast collection of images,” explained Chris Callison-Burch, an Associate Professor specializing in Computer and Information Science at the University of Pennsylvania.

The Holodeck utilizes a sophisticated language model known as a large language model (LLM). This powerful system, similar to the ones used in chatbots like ChatGPT, engages in a conversation with the user to determine the specific parameters of the desired environment. The system utilizes a vast digital library known as the Objaverse, which contains countless preexisting objects. It can effortlessly choose appropriate furnishings from this collection. Additionally, a layout design module ensures that the spatial arrangement of these objects is logical and coherent within the room.

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Practically speaking, if you inquire about the apartment of a cat owner, Holodeck will make sure that the final room is equipped with all the necessary furniture, including a cat tree.

The team conducted a comparison between Holodeck and a previous tool called ProcTHOR. They created 120 scenes and administered a blinded test to students, asking them to indicate their preferences. Holodeck clearly outperformed its competitor in every aspect. The system demonstrated its versatility by successfully generating a wide range of unique spaces, including science labs and wine cellars.

According to co-creator Assistant Professor Mark Yatskar, the ultimate test of Holodeck is its ability to assist robots in safely navigating unfamiliar environments.

Virtual training typically focuses on residential environments, but there are countless unfamiliar worlds that a robot may encounter and must learn to navigate. Utilizing Holodeck instead of the previous tool had a significant positive impact. For instance, a robot that underwent pre-training on 100 virtual music rooms created by Holodeck demonstrated a 30 percent success rate in locating a piano, compared to just 6 percent after training with ProcTHOR.

This holodeck has the potential to make a significant impact in the field of robotics, although it may not be suitable for running a Dixon Hill holonovel.

The study is scheduled to be presented at the 2024 IEEE/CVF Computer Vision and Pattern Recognition Conference. An unpublished paper that has not undergone peer review can be accessed through arXiv.

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Engineering

Dali forcefully collided with Key Bridge, with a force equivalent to that of 66 heavy trucks traveling at high speeds on a highway

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The cargo ship Dali caused significant damage to the Francis Scott Key Bridge when it collided with one of the bridge piers. As a result, three main truss spans, which were constructed using connected steel elements forming triangles, were knocked down. This incident occurred early on Tuesday morning, March 26, 2024.

The bridge collapse occurred with such suddenness that it afforded the work crews on the bridge little opportunity to evacuate. As a civil engineer, I have been closely monitoring this disaster, as it presents an opportunity to explore methods for enhancing the resilience of infrastructure, such as large bridges. For a bridge of this magnitude to fail, a significant impact force would be necessary. By applying the fundamental principles of physics, we can make a rough estimation of the force involved.

The impulse momentum theorem
Calculating the magnitude of the collision force of Dali can be done using the impulse momentum theorem, a fundamental principle in physics.

The theorem is derived from Newton’s second law, which states that force equals mass times acceleration. Adding time to both sides of the equation, the impulse momentum theorem reveals that force multiplied by time is equal to mass multiplied by the change of velocity when the force is applied.

The equation F*∆t = m*∆v represents a fundamental relationship in physics.

When calculating the impulse momentum theory for Dali’s collision, you’ll need to multiply the collision force by the duration of the collision. Then, compare that to Dali’s mass times the difference in velocity between before and after the crash. The mass of Dali, the length of the collision, and the amount of deceleration that occurs after the crash all affect its collision force.

The data regarding Dali’s accident
When fully loaded, Dali weighs a staggering 257,612,358 pounds or 116,851 metric tonnes. The vehicle was moving at a velocity of 10 miles per hour, equivalent to 16.1 kilometers per hour, prior to the impact. Following the collision with the bridge pier, Dali decelerated to 7.8 miles per hour, or 12.6 kilometers per hour.

Another crucial factor to consider is the collision time, which denotes the duration of the ship’s impact with the bridge during the crash, resulting in a sudden deceleration for Dali.

Based on the data from Dali’s voyage data recorder and the Maryland Transportation Authority Police log, it has been determined that the collision time was less than four seconds, although the exact time is still unknown.

When cars collide on a highway, the duration of the collision is typically between half a second and one second. It is logical to estimate the collision force by using the collision time duration, as Dali’s crash bears resemblance to a vehicle crashing on a bridge pier.

The powerful impact of Dali’s collision
By utilizing those estimates and applying the impulse momentum theory, one can gain a solid understanding of the likely magnitude of Dali’s collision force.

The collision force is determined by multiplying the mass of the object by the change in velocity before and after the crash and then dividing that by the duration of the collision. If we assume a collision time of just one second, the resulting collision force amounts to a staggering 26,422,562 pounds.

Calculating the equation, the result is 26,422,562 pounds

As a biophysicist would know, the American Association of State Highway and Transportation Officials has provided valuable information regarding the collision force on a highway bridge pier resulting from a truck crash, which is estimated to be around 400,000 pounds.

That being said, the impact of the cargo ship Dali on the Baltimore Key Bridge pier is comparable to the combined force of 66 heavy trucks traveling at a speed of 60 miles per hour (97 km per hour) and colliding with the bridge pier simultaneously. This level of magnitude exceeds the force that the pier is capable of withstanding.

Creating a bridge that can withstand such a high level of collision force would be technically feasible, but it would significantly raise the cost of the project. Engineers are exploring various methods to decrease the impact on the piers, such as implementing protective barriers that can absorb and dissipate energy. Implementing these types of solutions has the potential to avert future disasters.Engaging in a dialogue
Amanda Bao is an Associate Professor of Civil Engineering Technology, Environmental Management, and Safety at the Rochester Institute of Technology.

This article has been republished from The Conversation under a Creative Commons license. Check out the original article.

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Engineering

A drone is able to travel through the skies at speeds close to the speed of sound, namely at Mach 0.9

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A test flight of a new drone has taken off at speeds close to supersonic, going through the sky at Mach 0.9, which is 1,111 kilometers per hour (690 miles per hour).

But this is only the start of things. Venus Aerospace, the company that made the drone, hopes to get it to go nine times the speed of sound, or Mach 9.

The missile-shaped 2.4-meter (8-foot) drone was taken to a height of 3,657 meters (12,000 feet) on February 24 by an airplane. When the drone was let go, its hydrogen peroxide monopropellant engine was set to 80% power so that it wouldn’t go faster than Mach 1. It then flew for 16 kilometers (10 miles).

“Using a platform launched from the air and a rocket with wings lets us quickly and cheaply do the bare minimum test of our RDRE as a hypersonic engine.” Andrew Duggleby, CTO and co-founder of Venus Aerospace, said in a statement, “The team did a great job and now has a lot of data to use and tweak for the next flight.”

The new aerospace business, Venus Aerospace, is based in Houston, Texas. Its goal is to pave the way for hypersonic flight (speeds of Mach 5 and above).

In their most recent test flight, they did some testing for their Rotating Detonation Rocket Engine (RDRE). This engine is being made in collaboration with DARPA, the US State Department’s research agency that works on a lot of strange and cool technologies.

“Next is RDRE flight, and then hypersonic flight, which proves that the RDRE is the key to the hypersonic economy,” the company’s CEO and co-founder, Sarah “Sassie” Duggleby, said.

They want to make a car that can go to Mach 9, which is about 11,000 kilometers per hour (6,835 miles per hour).

This is way too fast of a speed. The NASA/USAF X-15 is still the fastest plane that a person has ever flown. In 1967, pilot Pete Knight took this jet to a crazy high speed of Mach 6.7, which is about 4,520 miles per hour or 7,274 kilometers per hour.

Concorde was a business supersonic plane that flew people for money until 2003. Its top speed was Mach 2, which is about 2,179 kilometers per hour (1,354 miles per hour).

Even worse, Venus Aerospace wants to let people fly on these Mach 9 trips. Venus Aerospace thinks it’s making good progress toward its pipe dream, even though there’s still a lot of work to be done.

Sarah Duggleby said, “One bite at a time is how you do hard things.”

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