Welcome to the Chronos Fusion Energy podcast.
I'm Priyanka Ford, the founder of Chronos Fusion Energy, and today I'm thrilled to be
joined by Paul Weiss, our chief material scientist and board advisor.
Paul is an extraordinary nanoscientist and material science expert with an impressive
career that spans decades.
He's currently affiliated with the University of California, Los Angeles, where he holds
a chair position in the nanosystem sciences and served as the director of the California
Nanosystems Institute.
At Chronos Fusion Energy, Paul brings invaluable insights into the world of materials, and
his work is crucial for our fusion energy technology.
Paul has co-authored over 400 research publications and holds more than 40 U.S. and international
patents.
His academic journey started at the Massachusetts Institute of Technology, MIT, where he earned
his bachelor's and master's of science degrees, and continued to the University of California
in Berkeley, where he completed his Ph.D. in chemistry.
He has worked at Bell Labs, IBM Research, and spent 20 years at Pennsylvania State University,
climbing the ranks from assistant professor to distinguished professor of chemistry and
physics.
Along the way, Paul has received numerous awards, including the IEEE Pioneer Award in
nanotechnology and election into the American Academy of Sciences and Arts.
In this episode, we dwell into Paul's journey from MIT to his current roles at UCLA, Harvard,
and Chronos Fusion Energy.
We'll explore his fascination with nanotechnology, his breakthrough work with the scanning tunneling
microscope, and how his research is driving the material science innovations crucial to
our smart fusion energy generator.
We'll also discuss his role of nanotechnology in various fields, from electronics to medicine,
and how AI and quantum computing might influence future developments in material science.
Paul was my very first partner at Chronos.
Join me as we unravel the incredible story of Paul Weiss, a pioneer in nanoscience, and
gain insights into the breakthroughs that could shape the future of fusion energy.
Here's my co-founder, Paul Weiss.
Hi, Paul.
Thank you so much for doing this.
I think out of all the people that work at our company, when I talk about you, I think
people are really most curious because you just have so much experience in the material
sciences world.
You started at MIT.
What got you into nanotechnology and material science, Paul?
Well, when I went to MIT, there really wasn't nanoscience yet.
My interests there were piqued by work I was doing in chemistry, where I wanted to understand
how chemistry and electronic structure were coupled.
That turned into a career goal that I thought would take my entire career.
Really early on, once I was an independent researcher, we were able to do what I intended
to take a lifetime to do every day in the laboratory, later leading to a crisis.
What I really liked about MIT was all the doors were open to undergraduates.
When I had some interest in something, I would just go look up who was the expert in it.
When I walked into their office, they would spend an hour with me.
If there was something that we could actually do on a problem like that, for instance, I
wanted to digitize data and there was no equivalent, no technology to do that.
I worked with someone who was early in digital photography.
We turned the traces on the paper into digital data that we could use.
That just came from going to someone who worked in that area.
He said, well, that sounds like an interesting problem.
Then we proceeded.
I learned not to be shy about asking for help from the top experts in the world.
I would say that continues to this day.
Yeah.
It's always good to have educational resources you can reach out to.
Yeah, I felt very privileged to have that with my professors.
Do you feel the need to be the same way with your students?
Absolutely.
I'm at UCLA and the culture here is very open door.
I expect my students to go to other faculty and start a conversation, sometimes start
a collaboration.
I do the same with others who come around to my office.
In fact, as you know, we run this initiative where we take on unsolved problems and then
put teams together to go after them.
Part of the fun there is when we think of an idea and start to pursue it, we call up
the top engineers in the world in whatever field it is, whether they're in Harvard or
Stanford or Singapore or wherever else.
A hundred percent of the time, they agree to work with us.
We've been able to move very quickly because we're not reinventing what our friends and
colleagues and collaborators have already done.
We pique their interest with the new problems that we're going after and what the impact
of solutions might be.
I think that really dates back to my time as an undergraduate and the opportunities
that I had there.
I didn't see that graduate students got the same deal for some reason there, but it's
something that's been in my mind.
At the places where that was the culture, I've been much happier.
I'll just leave it at that.
Nice.
Yeah.
How does chemistry and digitization then lead you to nanotechnology?
What does that mean?
My longer trajectory was that I did spectroscopy in a laboratory of a professor I had for two
or three courses.
I ended up jumping into courses that were way over my head that he was teaching and
then learning all I needed to do since I didn't have the prerequisites and later helping teach
those classes.
What interested me led me to my PhD work at Berkeley where I was looking at the reactions
of excited atoms.
I learned, I would say, a couple of negative lessons there in that it was a way too specific
approach to the problem.
We learned some interesting things and those are textbook experiments now, but it didn't
afford me the kind of creativity I like where I could choose each day what it is I wanted
to do in the laboratory and what I might learn.
I realized I needed a more general solution and I needed to be in a richer environment.
When I was a PhD student, we didn't have the culture of going to other groups.
We had a lot of really smart people in our group who were professors all over the world
now, but it was fairly narrow.
I moved from there to Bell Laboratories thinking that we could manipulate the electronic structure
of semiconductor surfaces, that that would be a general approach.
But nobody was doing that at the time in the context of chemistry, so I found the closest
thing that I could.
There was a terrific scientist there named Mark Cardillo who in many ways acts and looks
and talks like Danny DeVito, so he was also a lot of fun.
What he was doing was exciting semiconductor surfaces from collisions with atoms that didn't
react and then we moved into reactions.
We figured out that we could measure just a tiny fraction of a reaction on a surface
and we were very sensitive to that using the same physics that's involved in the semiconductor
industry, essentially what leads to transistors.
Those were in fact invented at Bell Laboratories and some of the key figures were still walking
around the halls and having lunch with us at the time.
What we didn't know was what was on the surface and where it was.
The scanning tunneling microscope had just been invented at that time and almost all
the work was being done at Bell Laboratories and IBM.
The microscope had been invented at IBM.
The inventors won the Nobel Prize in 1986, which turned out to be the year that I started
my postdoc at Bell.
There was an opportunity to measure where things were and there was another postdoc
at Bell named Don Eidler who when he finished his training position there, he moved out
to IBM in San Jose to the Almondon Laboratory with the idea of measuring what was on the
surface as well using something called vibrational spectroscopy.
There was an idea of how you could do that for a single molecule on the surface so you
could figure out where it was, what its environment was, and then what it was.
That experiment turned out to be hard.
In fact, we worked on it for 13 years before anybody made it work.
I just came back from the American Chemicals side in New Orleans and the person who did
actually succeed first, Professor Wilson Ho who was at Cornell when he did those experiments
now at UC Irvine not too far from here, showed that one could actually make that work.
That was the intriguing piece that sucked me into nanoscience in that I would be able
to visualize the chemistry.
That's the right way to put it.
We could measure structure and we could measure what are called spectra.
Later in my laboratory we also developed a whole series of spectroscopies where we could
also measure the function of single molecules and precise assemblies of molecules mimicking
what happens in our cells in biology.
Would you say this time was an era that was like, what do we say?
Is it the same for computing the excitement, the precipice of something new being on the
horizon?
Is that the same feeling that we now have with quantum computing?
I think nanoscience is probably broader actually.
There was so much unexplored territory that every time we went in the laboratory we discovered
something new.
I think in quantum computing we're trying to figure out what the best implementation
of it will be and then much of what one could possibly do with it has been I think described
theoretically.
Figure those two sides of how far can we take it both experimentally and where will we really
be able to use quantum computers to move forward.
I think in nano it was almost like going into an unexplored world that 99% of the time we
would find things we didn't understand and we'd pick off one in 10 of those to go after
and one in 10 of the ones we decided to pursue we would figure out and that was plenty to
really make a mark in the field.
I think there's so much effort and overlap between groups in quantum computing it's hard
to have the same kind of breakthroughs.
It's a little bit more of a race from one group and approach to another at the moment.
Right, yeah, material science is so vast Paul.
Somebody recently told me about the behavior of graphene and basically we know that it
works but we don't really know how it works and this was like an incredibly smart person
so that scared me.
Is that true?
I would actually say it kind of went the other way around so there was this amazing scientist
named Millie Dresselhaus and I actually get an interview with her for ACS nano and she
was on my board.
She's unfortunately since passed away but she worked out a lot of what the properties
of graphene and other carbon materials would be if anyone were ever to make it and she
really worked independently if you do read that interview when she got her PhD at University
of Chicago the person in charge of the physics graduate program didn't believe that women
should get PhDs so she was left on her own and Enrico Fermi kind of adopted her.
She was the same age as his daughter so he had her over to dinner once a week and encouraged
her and then when she went to Cornell for a postdoc she had a fully funded postdoc but
her husband had a job at Cornell and due to the nepotism laws there she couldn't be hired
and so again she worked independently and her career kind of went on like that.
It was a real lesson in persistence where she thought this was an important area and
the world eventually came around to her and it was part of the reason people called her
the queen of carbon because she figured out what those properties would be in theory before
the materials were ever developed and you know when our friends Kostya Novoselov and
Andre Geim ultimately showed that you know what we were doing to make clean graphite
all the time which was pulling off layers with the scotch tape they looked at the scotch
tape side and thought that they could get individual layers and then they worked out
all the properties because they had that material literally in their hands.
People had actually synthesized single layers of carbon on metals you know some years earlier
and described them and there were even scanning telemicroscope images of them.
John Heminger at UC Irvine for instance and one of my colleagues Rick Koenner had made
some materials as well but to your point I think the theoretical a lot of the theory
was understood and then once the materials were there we could go much much further with
them and to this day people continue there we published a paper on two layers of graphene
that are twisted and their properties just in the last week.
Yeah yeah wow are there a lot of materials like that that we don't know of do you think?
Well there are certainly families of materials that we're opening up so again one of the
parts of this meeting in New Orleans was looking at what are called maxines so a new class
of 2D materials that are a friend and colleague and collaborator Yuri Gagatsi at Drexel discovered
and so that has led to thousands of different materials.
There are other you know two there are many materials in nature that are that are layered
graphene comes from graphite which you can dig out of the ground that was what was you
know used for pencils for many years and still there are other materials like well one mineral
is molybdenite it's probably the second most common layered material it's another one where
you can just peel the layers off with scotch tape if you want to look at individual layers
or people have developed ways to grow most of these now but there are still many many
materials being discovered and those you know one can target such materials that then have
interesting and novel properties where you mix for instance dimensionality so some things
you know 1D and 2D or 2D and 3D at the same time and by modulating you know back and forth
between the two then you get something very interesting.
Is that the kind of data that was fed into that Google AI that created I think it created
like 380,000 material compositions in a couple of weeks and then it was like 800 years worth
of research is that how it does that then it just looks at synthesis of different elements
combined together in different proportions and what they can do?
What we need to learn from AI we'll maybe start with that is a lot of data so that what
you can do really depends upon the data set that's why people are feeding so much into
you know chat gbt and other you know other programs like that it's the same thing with
materials if you have a good enough data set then you can interpolate within it what I
don't think AI does for you is extrapolate to something that's very new so you might
be able to let's say tune the properties to make an extremely efficient catalyst and you
know tell synthetic chemists or material scientists look here and it's you know sort of point
and treasure map kind of way to what you should be targeting and then gather more data specifically
around what looks like an optimized structure but what it won't do I think is jump out of
the known data set into something that doesn't exist at all.
I wonder about that.
We'll see.
Yeah we'll see because then I feel like in the future wouldn't you be able to give it
parameters like for just to connect it with our fusion energy industry like if you could
tell it hey find a way to harness neutrons or something and then you know we don't have
to worry about that so much we have to worry about a little bit of neutrons and a little
bit of radiation but it's just would it be able to do it would it be able to build a
material for a purpose without any given parameters and just like an open data set in that just
go find the data you need.
I think that that's the key point the data have to exist in order to be fed into that
program so it won't jump out at you but you know for things like you know nuclear reactions
where we know their you know we know the cross sections and energies and everything else
I would call that known and some of the data doesn't have to be experimental data can be
theoretical data as long as it's trustworthy and if there are flaws in it then those flaws
will be reproduced in the results of the you know hopefully people figure out how to how
to rate the trustworthiness of data as one goes along because we face the same thing
you know when we don't use AI if we trust some data that turns out to be faulty or erroneous
or even off by a little bit that can affect you know our not only our results but our
direction.
How far has nanotechnology gotten like can are we at a point where we can use it for
surgeries?
Are we like five years away from that?
Well we have I mean it's in every phone and device and computer you have all the all the
chips that are are there made with nanotechnology the if you get a quantum dot television that's
a nanotechnology if you got a COVID vaccine that was nanotechnology so I would say they're
already in us and that is one of the key features that of nano and part of its importance is
that's the scale of function in biology so the if you look at the synapse scale in the
brain my wife as you know is a neuroscientist that's a 10 or 20 nanometer gap across the
synapse and you know her her comment to me all along has been well the brain's been nano
for hundreds of millions of years you people are just slow and and we what the advantage
we have is because we've learned to control materials at the nanoscale we can interact
at the functional scale in biology and that means both readout and you know that was reflected
in the brain initiative that was based largely on her ideas when she left a National Institute
of Mental Health in terms of listening in on chemical communication in the brain but
then also you know directing function and so you know drugs like a Braxane are based
on that's a protein nanoparticle that carries powerful anti-cancer drug a taxol and it's
you know simple but it it leads to greatly reduced side effects based on you know the
the formulations that weren't nano previously and so going you know further one can imagine
designing interactions that led us target a particular part of the body or particular
tumor or taking advantage of things like leaky vasculature and tumors or slightly more acidic
environment you know in in the way nanolithography is done in the semiconductor industry one
of the keys to get much higher resolution than the diffraction limit of light which
was thought to be what was going to limit the scale of devices is to use acid-based
catalysis and polymers and so we can turn reactions on based on pH and we can do the
same thing in the body if there's a different pH for instance there's usually a more acidic
environment in tumor so we can try to turn drugs on or release them in the same way using
those internal variations and if you can do that then you know there are do side effects
for example and there's a there's a big community in nanomedicine that tries to exploit those
possibilities.
Yeah the big applications I've seen with quantum computer quantum computing has been medicine
research and algorithmic trading I've used the IBM's Watson interface for quantum algorithms
with algorithm trading like almost five years ago it's been around yes but the other area
that it's really been kind of around and impacting has been medicine and it's probably because
of like the nanoscale of it all and the huge amounts of data that makes sense.
Yes yeah one time there was a discussion you know that that okay we're done with nano we're
going to move up to a bigger scale meso and then you know the argument against that was
well what don't you want to know that the nanoscale do you not want to know the DNA
sequence or you don't want to know you know what the chemistry on the outside of the virus
is there's you don't just because you moved to a bigger scale it doesn't allow you to
ignore those smaller scales so when you're targeting the smaller scales and I think the
nice thing for where quantum computing is now is we have what will seem like toy systems
compared to what we'll have in the future and so we're able to work out algorithms we'll
be able to work out what it is we will be able to do by looking at relatively small
you know at least what will seem like relatively small calculations now compared to what's
going to happen when we have more qubits in the in the in the quantum computers it's an
exciting time in that way and it's evolving very quickly and we have we can get our students
on quantum computers and have them do some some calculations to gain some familiarity
but that'll also get them thinking about what will they be able to do when the power increases
what is that so where will what will be we be doing in terms of nanotechnology like 15
years from now that sounds infathomable to us today well put it this way we used to have
group meetings where we would try and come up with things that we couldn't do for some
fundamental reason and ultimately you know we didn't always figure out how we could do
something but we didn't really come up with anything that we would not be able to do in
terms of a measurement and or precise control I mean even now we can and this is part of
how and my neuroscientist wife and I got together was we learned to control the placement of
molecules from a fraction of a molecule all the way up to centimeters so we kind of added
that chemical dimension to nanolithography if you will that opened up control of the
control and interactions with the biological world so I don't see a I don't really see
a limit there what we you know when you mentioned medicine nanomedicine one of the you know
one of the things that one has to do I think to be realistic about it is think about what's
going to get through regulatory approval and for that you have to understand how everything
you make is metabolized in the body and so for that reason you know that's an argument
for simplicity so that so that you can move forward and actually have impact clinically
as opposed to just sticking a bunch of nano things together and saying well this one does
that and this one does that I ran a journal for many years and we had a clinician and
other people really involved in medicine who you know we decided together we just would
never publish papers like that that would never have any chance of of getting inside
a human just because of their their complexity they could get a lot of attention for the
papers but they were not meaningful in terms of of actual medicine I don't know if that
makes sense.
It does yeah you don't want to just do it for the sake of doing it it has to metabolize
and actually have a purpose.
Yeah and that's well there can be a purpose but you also have to know what the products
are and then what those might do in the body and so there's I think in many cases there's
an argument for for simplicity because then you can have understanding of the understanding
the whole system we whenever we do a fair bit of invention we identify problems and
go after them and we always look for the simplest solutions that are effective and that that
lets us go much further much faster.
So are we kind of implying that with computing in the future we'll be able to maneuver those
unknowns a lot better and make more complex things or is simplicity still going to be
the way to go?
I think simplicity still to me the way to go right if even now like chips that we make
there there can be you know hundreds of layers in the processing that's part of what makes
fab cost so much.
Where chips are made right now right TSMC makes most of the complicated chips in the
world because you can't afford to have too many factories like that.
There was a plot that went along with Moore's law showing the cost of the fabrication centers
compared to the GMP of countries.
It's at that scale even to make the chips that go in our laptops and phones.
Yeah did you when you guys were building that stuff out in at IBM did you think that it
was that we would run into the scarcity we're running into now because of geopolitics?
Well we weren't really on that side we were on you know we were on the side of fundamental
science but in fact the reason the microscope was developed originally was to look at flaws
defects in the oxide insulators that people invented didn't expect to get atomic resolution.
I think there wasn't you know as the as the industrial part developed yeah I don't think
when people foresaw all the supply chain issues and everything else that came along with pandemic
it's and it's not just in it's not just in technology you know many countries now are
after food security they want local production so for instance in Korea they're building
an enormous agricultural campus for universities in order to be able to generate food locally
rather than depend upon others in Singapore right it's a it's a tiny tiny place where
people right and they're trying to trying to you know if not be self-sufficient at least
more able to to sustain themselves with what can be grown in you know relatively urban
environments and so there's been a lot of push across many many different fields for
okay what could we do to to mitigate the risk of you know depending internationally so much
on one another.
Yeah switching gears Paul like you you have quite a few awards here you have the IEEE
Pioneer Award that's kind of a big deal like you have so many awards what do you try for
this or do people just look at your work and they seek you out and award you how does this
work in the academic?
It's a combination of things so you know within it does your institution a lot of good when
there is an award so there's a you know there is a group of of people within the department
that looks for honors we can put put our colleagues up for but sometimes people just you know
read a read your CV online or sometimes very outdated biography in one case and then nominate
you for an award and the next thing you know the first time you ever hear about is when
you get a call saying you know you've won this award please come here so there I mean
there's there's a mix some are more kind of lifetime awards and others are more tuned
to a particular project so for instance my student just won this Collegiate Inventors
Award for something he developed in our laboratory and my it was kind of fun for me because our
my very first student had also won that award for inventing some microscopes in the very
early days in our laboratory.
Were there any awards you knew of as a child that you now have as an adult?
I don't think so I wasn't so there are these I wasn't so aware of these things yeah.
What did your parents do?
My father was professor at Cornell in game theory they started they started as so they
they started a statistics department two weeks after he passed away which would have been
the appropriate one for him but he was part of a group of mathematicians at Columbia where
he'd gotten all his degrees and they the five of them moved to Cornell all the same time
and then right after they got there they pulled him away from another university and brought
him in and he never left.
And mom was mom assigned?
He was trained as a mathematician they actually met in a math class but she did many things
over the years during World War II she was an engineer and that and she was one of only
three people they kept on after the war to continue at Western Electric and then later
she taught the death and then did did a whole series of other other things in her career
and she's still still going strong I talked to her this morning living on her own at a
hundred in the house I grew up in.
That's awesome that's like super line that's awesome.
Did they did they tell you about material science when you were young?
Oh not at all.
My father didn't talk very much unless he was in front of a class he was a very good
he was sort of known as very good teacher and he did all pencil and paper theory he'd
used a computer in the early days and when he was a student but there were no programming
languages yet so he decided they were useless and then his his PhD students would turn some
of his you know some of his equations into algorithms that they would test but he didn't
really use them till he was retired and decided they were actually useful after all and then
I don't think he he didn't have too much to do with materials that I was aware of until
he passed away I went through his office and I found a manuscript who was actually working
on a problem in surface and nanoscience with one of my colleagues and I I stupidly threw
the partially finished manuscript away rather than finishing it and publishing it with him
I do regret that very much but in my high school you know we only had one high school
in town in Ithaca oh some of the parents so I didn't know what people's parents did but
some of the parents turned out to be chemists and material scientists and of that we had
one math class that kept in touch even before social media we ended up with five surface
scientists two Greek scholars two economics professors and one close friend who ran at
that starting her career and Alzheimer's Foundation and now at a different a different foundation
so we had we had a we had a pretty good crew there the guy who sat next to me in high school
runs a 200 million dollar material science institute in Korea now and I chair his advisory
board.
Oh so cool.
Yeah it's very funny they connect after all these years when I went back to visit Cornell
I met the you know met the faculty and I really just knew them as the parents of my of my
you know elementary school through high school friends and some are pretty famous chemists
and material scientists but the first thing when I'd walk in their office I'd go oh
you're Yoni's father oh you're so and so it was a kind of a surreal visit the first
time I did and then later I figured it out you know I figured out who everybody was and
how they were connected academically and and in terms of families.
Yeah they say you are the average of the five people you're around the most and so yeah
like you're around like spectacular human beings and yeah the people rub off on you
it's I tell my dog about all the time like be careful who your friends are.
Perfect.
Well I had my brother my two older brothers who were both both women of science and medicine
before me.
Oh I thought you were I thought you were gonna say one is a drunk the other one is in jail
oh no no they turned out.
Unless you know something I don't know.
No no he turned out good.
Why don't I have a birthday tomorrow I'll check I'll check to make sure he's he's safe.
Nice not one bad pancake man that's so awesome that's awesome.
What are you like most proud of Paul like what is the big hall breakthrough or is it
yet to come.
Well I hope it's yet to come.
Me too.
I'll tell you a couple things we've done along the way so the as I said early in my career
I was trying to figure out how to how electronic structure and chemistry were coupled and we
figured out how to measure that every day and that was kind of a crisis in my career
that it was supposed to take longer and the next thing we did was taking inspiration from
biology and trying to understand how the very efficient motors in the body work so we have
motors in us where the chemical fuel is turned to motion with more than 99 percent efficiency
so much so that they're used to pump protons through a membrane if you push the protons
back the other way you get the fuel back it's almost like you know the the scene in Ferris
Bueller where they're trying to make the miles off the odometer by running it backwards on
blocks it's almost as if they're trying to get the fuel back in the tank there's nothing
that humans can do at any scale that is close to that efficiency and so what we try and
do in in my laboratory is recapitulate natural features where we understand where every atom
is so we go from quantum mechanics to engineering and experiment theory and simulation where
basically we do the experiments then we test different theories and we figured out now
a whole series of these functional molecules by developing both microscopes that can measure
their function and their structure at the same time and tens and hundreds of thousands
of times just for a single molecule or assembly not the same one chemically but the very same
actual one and then along the way we developed this you know this ability to place chemical
functionality that I mentioned before so that became sort of a thing if you will you know
people came up with different functional systems and then asked us to figure out the mechanisms
or more often sort out between opposing ideas about how they worked and then the long came
hand really I was very much curiosity driven and she's focused on anxiety and depression
and how neurotransmission works and that really led me to target problems you know first first
hers a later one in doing safe efficient high throughput gene editing and now institutionalizing
that and that's what we're having our meeting next week about that I hope you're going to
join on this challenge initiative where we identify unsolved problems and then we put
teams together to go after them and develop novel effective solutions for them and that's
become just an exciting way to live where you know you ask someone what would revolutionize
their field if you could do it or what would they like to be able to say they could do
in 10 years or in medicine very specifically you know what did a particular patient need
in terms of a device therapeutic or diagnostic so we train medical students and MDPs in our
lab and part of their job is to in their training when they go and see patients to ask that
question and then to bring back the problems to us sometimes they'll propose solutions
sometimes they'll just throw it open and then one of the big advantages of nanoscience is
because the field developed from chemistry physics materials toxicology medicine engineering
you know all these areas we learn communication skills that as far as we can tell nobody else
did and so we shared problems and approaches and we developed new tools between us and
so we developed those skills in our trainees and we also developed them in the medical
students who when they're doctors and they're speaking to intelligent patients or intelligent
parents of patients you know they can explain a disease and what the issues are but to us
many of us have little or no training in biology and medicine they can explain the fundamentals
and then what the issue is and we get very you know the people who propose the solutions
turn out to come from completely different fields the first person to pose an idea for
the gene editing solution was a mechanical engineer working how and how light couples
into nanostructures when we had a project on chronic pain the person who came up with
the best ideas was the writer and director of kung fu panda and he's amazing and we learned
from him all these all these concepts about perception and how you you know you take your
audience and direct their their brain and what they're taking in in a way that scientists
should really be taught and other you know all educators at least and speakers should
be taught to do when you're engaging an audience yeah there was i think there was a show of
maybe over a decade ago on either discovery channel or national geographic and it was
a measure of different types of intelligence so it was emotional like you like you had
to wear goggles that made the world upside down and you had to make a basketball things
like that and the people were were like there was like an air force pilot there were like
all of these people in that group like heavy heavy hitting scientists and at the end of
the day when they did all of the tests and they summed up the totals of the numbers the
winner was this woman from los angeles who writes horror movies she had like overall
iq it was brilliant yeah those writers are smart yeah yeah they got something going for
it's interesting yeah yeah the actor alan alda you know got a little frustrated when
he when he was the host of the show scientific american frontiers so he developed a program
to teach scientists to engage with different audiences whether it's you know your mother
or a legislator or the public or people from different fields or your field we ran a program
with him here at ucla where we brought in nanoscientists neuroscientists and astrophysicists
because those are the areas that the cavoli foundation supports and they are the ones
championing it for us and it was it was really phenomenal to uh you know use ideas from improvisational
comedy to to riff off one another and see what you know understand what your audience
is thinking and really tell a more personal story about why you're interested in a problem
it brings it brings an audience in much closer than they would otherwise be if you were just
you know showing one uh one slide after another actually going back to ferris bueler i guess
yeah i don't know why that one's stuck in my brain right now but apparently it is i see
that it's almost like you watched it yesterday i think mentally we were going to talk earlier
in the week and now that that analogy keeps sticking uh how do you how do you keep up
paul how do you keep up because you know i go to the swiss plasma institute and i mention
your name and they're like oh yeah we know paul and we we're in barcelona and where we
talk to random people and we're like oh i'm here with paul and they're like i know paul
and then i'm in la and i remember meeting constantine right after i might do i think
about two or almost three years ago and it's like yeah i know paul and so there are people
that just know paul there are people at oakridge national labs are like oh paul yeah we love
paul they don't just know you they love you they love you and they see you as a person
who remembers the important things about them is like great to collaborate with highly intelligent
and so how do you make time to turn to me to a piece to have so many people think of
you as so exceptional and and how do you do it i have no idea okay great i thought there
would be my my life is chaos i think you know i'm very sort of the key to my happiness and
i'm very forgetful in a way i think whatever's in front of me is what i'm working on and
so we can have these divergent you know pieces in our group and you know i can work with
cronos your company our company and then go work on growing meat and fish in the laboratory
and then go back to trying to figure out how you know charge moves through biomolecules
and how we might take advantage of that it's just kind of whatever i keep a list of things
i'm supposed to do and then when something pops to the top i'll just focus on that completely
i think i'm curious about the you know the world and the connections in it and there
are some really part of that's the nano you know the whole nano view that that i talked
about where it's much bigger than nano we're responsible for doing more because we have
developed these special skills and and maybe i've maybe i've exploited that more than most
people i've started and ran this journal that let me see whatever in the world was doing
i towards the end the rate of submissions was i think 12 000 manuscripts a year and
i'd read and rate every one of them and so by knowing what people were doing it really
helped to see how everything fit and could fit together and so i'm still after that but
now in different ways you know part of that is cronos and some of the other startups that
seems to use the same part of the brain that i used as an editor yeah that's that's so
that's awesome it's almost as if like you do the things that make you happy and that
have like great purpose in the world and and doing well well that's my advice to young
scientists they that they should figure out what makes them want to get out of bed in
the morning and get in the lab and you know for your i did something completely different
for my phd you're not stuck with that forever but a phd i just finished teaching the you
know top 40 freshmen at ucla in science and engineering and got them all on laboratories
and you know you can change your mind later you can learn from what you did what you like
and what you don't like and that's also that's also important but if you're going to go spend
five years on something for her phd it ought to be something you really enjoy because that's
a big chunk your life it shouldn't just be oh this is important to work with this famous
scientist or that you know at that you know institution that's ranked higher than another
one find what's just so exciting you can't wait to do it again i think one of the beautiful
parts of academics is we get to do that every day and we can we can morph and change or
add things or stop doing things we have the freedom to to explore there and then in my
group especially we use everybody's brains you know we're much smarter as a team than
than any one of us by far and so we're always batting around ideas and we ask everybody
in the lab from high school students through visiting professors to pitch ideas and defend
them and say here's what would matter you know here's why this would matter here's what
we need to do it here the resources we need here's what we need to stop doing and that's
just the philosophy of how the group of how the group works and everyone is expected to
do that later if someone's going into academics that's the way you get a job as you say this
is the most important problem in the world and i'm the only one who can tackle it or
if you're in a company then you say here's what we ought to be doing and here are the
sources i'll need to lead it and then that's how you end up having a group and running
it we have people who've become lawyers out of the group and they use those same gun arguments
in their firms yeah you gotta you gotta love what you do i i'm i'm very grateful for that
with chronos i've had hundreds of jobs but and some i've loved others i've not loved
and the ones that i've always done well are the ones i loved so it's obvious in in working
with you i'm like how important this is to you and how much joy it brings you and us
it's fun to work together and one of the one of my great great pleasures is learning about
magnet problems from carl and seeing what we might be able to do that's novel there
that'll that'll move the whole field forward right yeah i'm definitely excited about that
we could we could close off with the chronos question and yeah what what how do you feel
about fusion energy hall have i made you more gung-ho about it in these last three years
uh you know we i i think you are the third person to ever join our company so you've
been with us from from very very early days and you've been with us since i think of even
like two months before carl joined us so amazing yeah yeah i think that's been that's really
it's been extraordinary to to identify what the key challenges are and then of course
we're not operating in a vacuum if you're part of an expression seeing how the other
startups in the area are approaching the the problems and where they've tripped up and
where they've moved forward and so it's a it's a very exciting time to say okay we could
solve this problem this problem this problem in fact there are a lot of analogies to some
of the other big programs that we've undertaken as humans you know in the human genome project
there were a couple of leaps that were identified and then a quite small number of people figured
out the solution to those and i'm seeing echoes of that in what we're doing as well and so
i i see great promise and and particularly the team we have and how we're approaching
those problems so i'm very excited about it