SciTech Now Episode 326

In this episode of SciTech Now, NPR’S Science reporter, Adam Cole demonstrates how to find the speed of light with peeps; Adam Cole joins Hari for a conversation on the  speed of light; How is climate change impacting the water cycle?; and a St. Louis lab is engineering a bomb-sniffing locust.



Coming up, finding the speed of light with Peeps.

The speed of light is one of those numbers that people have chased for centuries.

Today, I can find the speed of light in my kitchen.

And that brings us back to Peeps.

In theory, if I measure the distance between melted Peeps, I can find the wavelength.

Studying how forests use water.

The strength in what we do here is that we've got continuous measurements, and what we've seen over time is, our dry years are getting drier, and our wet years are getting wetter.

It takes a long time for these changes to manifest.

Especially given the variability we have in rainfall, you have to have a lot of data to be able to tease out a trend.

Bomb-sniffing locusts.

Even an insect like locust with its antennae, has hundreds of thousands of sensors on the antennae.

And there are so many different varieties of them.

The ultimate goal for this project would be to shrink everything into a very tiny, 3 millimeter by 3 millimeter dot.

So it will not even look like this -- as big as this.

They are engineering marvels.

So, for the amount of footprint they have, the type of sensors they have, the type of energy consumptions they have...

It's all ahead.

Funding for this program is made possible by...

Hello. I'm Hari Sreenivasan.

Welcome to 'SciTech Now,' our weekly program bringing you the latest breakthroughs in science, technology, and innovation.

Let's get started.

What do you get when you combine a microwave and a pan full of those pastel-colored marshmallows known as Peeps?

As NPR science reporter Adam Cole demonstrates in this segment, the squishy mess can actually help you calculate the speed of light.

Let's take a look.

It's the week after Easter, and that means homes all across America are overflowing with stale Peeps.

Now, you could either eat those Peeps, or you could use them to find the speed of light.

♪ Finding the speed of light with Peeps ♪

The speed of light is one of those numbers that people have chased for centuries.

Galileo wanted to know how fast light moves...

Buonasera! he proposed an experiment.

[ Speaks Italian ]

He would uncover a lantern, and when the light reached his assistant, the assistant would quickly uncover his own lantern.

Using a water clock, Galileo would keep track of the time between uncovering his light and seeing his assistant's light.

Up close, there was no noticeable delay except for the split second it took his assistant to react.

Then, they started moving away from each other.

Galileo figured the delay would get longer and longer because the light would need more time to travel the greater distance.

But even when they were a mile apart, there wasn't a noticeable pause.

[ Speaks Italian ]

He couldn't have guessed that light had made that trip in 1/100,000 of a second.

Centuries later, in 1849, a French scientist whose name I can't pronounce...

Armand Hippolyte Louis Fizeau.

...came up with an even better way to measure the speed of light, which was pretty impressive, considering that people weren't even using light bulbs yet.

He took a toothed wheel and spun it faster and faster.

He shot a beam of light between the teeth and reflected that beam of light off a mirror 5 miles away.

By the time the light got back, a tiny fraction of a second later, the teeth had moved over just enough to block the light.

No light made it back through.

But if he made the wheel spin a little faster, the teeth would move over one whole position, and the light could get through.

So when Fizeau saw the light, he knew the wheel was spinning so fast that a single tooth was moving over one place in the time it took light to travel 10 miles.

With some quick math...

Armand Hippolyte Louis Fizeau.

...determined that the speed of light was 700 million miles per hour, which we now know was only 5% off the actual value.

Today, I can find the speed of light in my kitchen, and that brings us back to Peeps.

♪ Finding the speed of light with Peeps ♪

And a microwave.

♪ And a microwave

And just a little bit of physics.

♪ And physics ♪ Just a little bit

Microwaves travel at the speed of light.

And like all waves, their speed is determined by how fast they go up and down -- that's the frequency -- and their wavelength.

Frequency is written on the side of my microwave, right here -- 2,450 megahertz.

So we've got the frequency.

Now, to calculate the speed, we just need to know the wavelength.

And we can find the wavelength by microwaving Peeps.

I'll set it on low so the Peeps don't just explode.

And let it run for a minute or two.

Inside, microwaves are bouncing around.

In some spots, there isn't much energy at all, and the Peeps in those areas stay cold.

In other spots, there's lots of energy, and the Peeps get really hot.

Those hot spots are half a wavelength apart.

So, in theory, if I measure the distance between melted Peeps, I can find the wavelength.

And sure enough, some of the Peeps are really gooey while others haven't melted at all.

Poking around, I found a rough location for a handful of hot spots and measured the distance between them.

Those average out to 2.43 inches.

So that's half a wavelength.

Multiply by 2, and we get a wavelength of 4.86 inches.

So, now, to find the speed of the microwaves, which, remember, is the speed of light, I just have to do the math.

Frequency times wavelength -- 2,450 megahertz times 4.86 inches -- gives us about 12 billion inches per second, or 676 million miles per hour.

And that's pretty close to the actual speed of light.

[ Ding! ]

♪ We just found the speed of light with Peeps ♪

Joining me now is Adam Cole, the creator and host of NPR's science YouTube channel, Skunk Bear.

How many different ways are there of measuring the speed of light?

Well, there's been a lot throughout history.

As soon as people figured out that light was moving, which was, for a long time, mysterious, they wanted to know if it traveled instantaneously from one point to another or if it actually had a speed.

And so there's been a lot of contraptions created since, basically, the 1600s to try and experimentally determine this.


People used rotating mirrors and toothed wheels, like we saw in the video.

People looked at the ticking clock that is the moons of Jupiter eclipsing to try and have a measurement of time and light passing between that planet and ours.


So there's been a lot of different methods and some that were more theoretical, using the constants of physics to try and figure out the speed of light.

So, this Peeps method --

It's probably the most serious of them all and the most precise.

That's right.

We're talking about wavelength and frequency.

What's the difference?

The difference between wavelength and frequency?

Well, wavelength is the distance between -- if you think about a wave in the ocean -- the distance between two troughs.

When a wave goes up and down, the distance from this low and this low is the wavelength.

And the frequency is how fast that wave goes up and down.

So you can think of it as the speed of a person walking is determined by... the length of their step and the number of steps they take per second.

And you multiply those together, you get the speed of them walking.

Multiply a wavelength and frequency, you get the speed of a wave.

Okay, so, this is an experiment that you would recommend that people try at home.

I would.

I hope that they do.

Were the marshmallows delicious after?

You know, I think I didn't have a lot of love for Peeps before this experiment, and after, I definitely don't.

All right.

Adam Cole from the YouTube channel for NPR, Skunk Bear.

Thanks so much.

Thank you.

Local Projects is an experience design firm.

What that means is that we build incredible installations and experiences from the ground up.

Not only do we work on crazy, out-of-the-box concepts, but we have the architects, the software and hardware developers, the creative folks, and content developers to bring that to life.

We worked with a variety of institutions, probably the most famous of which is the 9/11 Memorial & Museum, which we helped build over the course of eight years.

Not only did we contribute to over a hundred museum exhibits, but we also helped create the names-arrangement software for the memorial itself, which arranges over 3,000 names by association rather than alphabetically.

So, folks who lost loved ones during the attacks are able to send in their requests, and 99% of those requests were answered through a special algorithm that we built for the memorial.

We really try and invite visitors to kind of step into an experience.

So, for example, at the Cooper Hewitt National Design Museum, we give every visitor a pen that invites them to become a designer themselves, you know, around themes of storytelling and every visitor's perspective.

We've done projects for StoryCorps or for the 9/11 Museum, which invite visitors to really come and share their own memories, their own perspective.

Where were they when 9/11 happened?

What was that experience like for them?

And to be able to kind of reflect themselves and bring themselves to the museums.

They're not just hearing or learning, but they're also kind of bringing their own meaning, their own stories.

I think because of the interdisciplinary nature of our work, that's why we seek out clients like the American Museum of Natural History.

They were really a pleasure to work with, not just because they're such a prestigious institution but because they have such an incredible collection and inspire so many people of different ages.

So, really, what we were looking for in the iPhone app that we're presenting tonight in collaboration with them is to create a layer on top of the existing, incredible museum experience as opposed to trying to add digital where it doesn't belong, and that's something that runs throughout the -- throughout the course of our work.

You can find us on

Also, feel free to reach out to us on Twitter, @localprojects, and our newly minted Instagram, @local[underscore]projects.

Most elementary-school students learn about the hydrologic cycle -- the circulation of water from the atmosphere to the Earth and back again.

How is this cycle affected by change in climate over time?

To find out, scientists at the Coweeta Hydrologic Laboratory have been recording data from a western North Carolina watershed for more than 80 years, and the data provides valuable information on the effects of climate change.

Let's take a look.

The rain that falls outside your window today is the same rain that watered the grounds and filled the streams and rivers millions of years ago, during Earth's earliest days.

That's right -- the rain that was still is.

So, we're interested into quantifying that, seeing how much it changes, depending on the environmental conditions.

That's because rain -- actually, water -- is vitally important to every living thing on the planet.

And water is constantly cycling from Earth to sky and back again.

So, water in streams important, obviously, right, for not only the fish and the critters that live in the stream but also our water supplies.

It's called the hydrologic cycle.

Let's follow this drop to see what happens.

When the little water droplet becomes heavy enough... falls from the clouds as snow or rain.

Some of the water washes over the ground and flows into streams and rivers and eventually into lakes and even the ocean.

It evaporates back into the atmosphere, turning back into a cloud.

Water droplets can also fall to Earth and soak into the ground and then be taken up by trees and plants.

It's later released into the atmosphere through transpiration.

But we're only now beginning to understand the specifics of the hydrologic cycle, thanks in part to the Coweeta Hydrologic Laboratory in western North Carolina.

The U.S. Forest Service bought the 5,600-acre forest and set it aside as an experimental forest back in 1934.

The primary focus is on rainfall, stream flow, and how the forest uses water.

One of the main research tools is a weir.

Again, it's called a weir, and this is one of the most precise ways you can use to measure how much water is coming down a stream.

A weir resembles a dam, but it's more than that.

It's a stream-gauging station built across a watershed.

32 weirs are built on various watersheds throughout the Coweeta Basin.

So, this wall extends all the way down to bedrock and extends all the way into the hillslope on one side of the stream.

And we can see it crosses the road and goes into this other hillslope.

And so the idea is that you're taking all the water uphill of this weir, whatever's coming down the stream and whatever's moving in the shallow groundwater, and you're forcing that water to come over this what we call a blade -- this opening of the weir -- to quantify every bit of water leaving this watershed.

You see the pond upstream of the wall.

That pond is connected through pipes to a well inside of our gauge house.

And so the height of the water inside this well is exactly the same as the height of the water in this pond.

So, in this well, we have a float sitting on top of that water that's going up and down with the level of the water, and we record that with a time chart in the gauge house.

And knowing the height of that water and the geometry of this weir, there's been experiments done to calculate flow as a function of the height of that water.

So it's an equation -- a statistical equation that's calculating flow as a function of the height of the water.

Measuring stream flow gives a more accurate view of the water flowing through a watershed because rainfall varies over an area.

And the weir system allows the watershed to be measured day and night, through storm and sunshine.

But here, we're measuring the height of this water to within 1 millimeter of its actual value.

Readings have been taken every five minutes since 1934.

That's roughly 200 million bits of data.

And that consistency is important.

The strength in what we do here is that we've got continuous measurements from one place over time with the same method.

It's very consistent, very robust, and what we've seen over time is not that it's getting -- not that our mean is shifting up or down -- so it's not getting uniformly wetter or uniformly drier -- but our dry years are getting drier, and our wet years are getting wetter.

The long trend of data shows the Coweeta Basin still receives about the same amount of rain each year it's been getting for the past 80 years.

But it also reveals that the dry years are getting drier, which means periods of drought are becoming more common and more severe.

It also shows that wet periods are getting wetter, what many people call a torrential downpour with flooding.

All of that will affect what plants, trees, and eventually animals live in the forest.

So, we expect, in the future, as our climate becomes more variable, we have more drier and more prolonger droughts, that we will see some species suffer as a result of that.

So our species composition is gonna be continuously changing.

To understand what those changes mean for the forest, dozens of experiments are studying sap flow in individual trees, soil moisture, and how the mineral content in the soil is changing.

This instrument-laden tower measures just how much carbon the forest is taking in and releasing.

The leaves, during the daytime, are doing photosynthesis.

So, carbon dioxide enters the leaf, it gets transformed into a carbohydrate, into sugar, but at the same time, those leaves need to metabolize.

They're like all of our cells.

They basically have a certain cost of doing business.

So they're breaking down a certain amount of carbon, releasing that back as carbon dioxide.

It takes a long time for these changes to manifest.

Especially given the variability we have in rainfall, you have to have a lot of data to be able to tease out a trend.

The forest moves slowly.

It takes a long time for a forest to change, and so you can't do this in 10, 20 years.

You have to have a long-term record to do it.

Imagine a world where cyborg locusts are trained to detect bombs.

Sound strange?

One lab in St. Louis, Missouri, is busy making this a reality.

Let's take a look.

So, here's the star of the show.

It's a locust -- a grasshopper, really -- wearing a backpack -- a tiny computer wired into an even tinier brain.

Welcome to the world of biorobotics.

At Washington University in St. Louis, a team of scientists and engineers, headed by Barani Raman, is working to create a bomb-sniffing machine that uses the antennas of living locusts as the detector.

It can actually amplify the signal that they're recording.

As a grad student, Dr. Raman built a smelling machine, a mechanical nose, but realized there was no way he would ever get close to what nature had already come up with.

So, turned out it was a very humbling experience.

Even an insect, like locust with its antennae, has hundreds of thousands of sensors on the antennae, and there are so many different varieties of them.

So, in terms of the complexity that the biology has, it beats the engineering, hands down.

With funding for the Office of Naval Research, they hope one day to be able to send a swarm -- yes, a swarm -- of bomb detectors wherever needed.

Great idea, really complicated to do.

First of all, you have to train the locust to recognize a particular odor.

Then you have to equip it with a backpack computer, and then figure out how to steer the locust where you want it to go.

Turns out that training a locust to detect a smell, that's the easy part.

The researchers won't exactly say what chemical they're targeting, but let's say it's TNT.

So, what is going on here is, there are a bunch of six locusts.

Each one is getting trained.

So in order to give them this, they are being starved for a day, so they are very motivated to learn this task.

The locusts are strapped in, facing a tube that will send puffs of the odor.

Their mouthparts are painted green so researchers can easily see them when they open up.

And it only takes a few sessions with hungry locusts.

They get a puff followed by a piece of grass.

Puff, grass, puff, grass.

Pretty soon, they get a puff, and they're opening their mouths in anticipation.

So, they get a puff...

They get a puff.

They've been trained on this puff already.

See that?


Yeah, so that definitely is.

Here's the instant replay.

And they keep responding to that smell even when they're not being fed.

So we can actually train them like Pavlov's dog, right?

So, you ring the bell, feed the dog.

Same thing you can do with a locust, too.

Training to recognize the smell?


But here's what they're really watching now -- not the moving mouthparts on the locust.

They need to identify what the odor response looks like inside the locust's brain.

So, the popping sound that you're hearing are the neurons of the brain talking with each other.


These are the wires that get implanted in the locusts' brain.

Say it again -- you've implanted electrodes in the locust's brain.

Arrays of electrodes.

Not just one wire but a bunch of wires.

And this is where they start turning an insect into a cyborg, part animal, part machine, that can translate, amplify, and transmit a bomb alert in the field.

Enter the guy from the Computer Science and Engineering Department.

Because my area is in electronics, integrated circuit design, microchip design.

We can only train biology to pick up interesting signatures.

But then the filtering mechanism has to be done on the electronic side.

There's a lot going on in this little backpack.

Right now, yes.

But the ultimate goal for this project would be to shrink everything into a very tiny, 3 millimeter by 3 millimeter dot.

So it will not even look as big as this.

It will be close... It will be as small, or as big, as something like the locust's head.

But then the challenge is, of course -- which is true with any electronics -- is how do we power them?

So that's where also my expertise also came in is because my area is to, how do make such systems without running into batteries?


So, that's also one of the parts of this project is, how do you make this whole electronics run without any -- by harvesting energy from the ambient source?

So, let's say they solve all the challenges of detection and transmission, and the locust is ready to go to work.

How do you keep it from just flying away?

There has to be some method of remote control, of turning the locust into a drone.

For that, they turn to a professor of engineering and materials science, who brought in a vial of gold nanoparticles, which are most commonly used in cancer treatment.

What these gold nanorods are good at is they can absorb a lot of light and convert the light into heat.

Here's the thing about locusts -- they naturally turn away from heat.

So they will tattoo a bit of that heat-absorbing gold on each of the locust's wings.

Heat the right side, the locusts goes left, heat the left, it turns right.

You can apply the heat with a light, and in the lab, it works, but they're going to have to do this in mid-flight.

But at some point later, what we are going to do is actually have the light right on the locust itself.

We are going to have tiny LEDs on the locust itself, and you just turn on and off these LEDs to start heating these tattoos and start steering the locust.

If that steering system works, they may have a working prototype -- a bomb-sniffing, data-processing, remote-controlled cyborg locust -- by the end of 2017.

Locusts only live a few months, so the training and the wiring continues on a regular basis.

But they're small.

They're cheap.

They're easy to train.

And they don't spend any time thinking, analyzing, considering options.

It's those antennas.

When it comes to odors, they can find a needle in a haystack.

Actually, the truth is, they are engineering marvels.

For the amount of footprint they have, the type of sensors they have, the type of energy consumptions they have, we cannot make machines that actually match them.

We need machines that match them.

So if you cannot build one, why not hijack one?

That's the philosophy here.

And we have tools right now to hijack.

All these tools are there, independently, if you look at them.

They are pretty standard tools of the whole field.

It is the integration of these multidisciplinary tools together that makes this particular project possible, and this is the perfect time to do that.

And that wraps it up for this time.

For more on science, technology, and innovation, visit our website, check us out on Facebook and Instagram, and join the conversation on Twitter.

You can also subscribe to our YouTube channel.

Until next time, I'm Hari Sreenivasan.

Thanks for watching.

Funding for this program is made possible by...