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When we teach undergraduates about materials and measuring electrical resistance, we tend to gloss over the fact that there are specialized techniques for this - it's more than just hooking up a battery and an ammeter.  If you want to get high precision results, such as measuring the magnetoresistance \(\Delta R(B)\), where \(B\) is a magnetic field, to a part in \(10^{5}\) or better, more sophisticated tools are needed.  Bridge techniques compose a class of these, where instead of, say, measuring the voltage drop across a sample with a known current, instead you measure the difference between that voltage drop and the voltage drop across a known reference resistor.    Why is this good?  Well, imagine that your sample resistance is something like 1 kOhm, and you want to look for changes in that resistance on the order of 10 milliOhms.  Often we need to use relatively low currents because in condensed matter physics we are doing low temperature measurements and don't want to heat up...
10 months ago

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More from nanoscale views

Science slow down - not a simple question

I participated in a program about 15 years ago that looked at science and technology challenges faced by a subset of the US government. I came away thinking that such problems fall into three broad categories. Actual science and engineering challenges, which require foundational research and creativity to solve. Technology that may be fervently desired but is incompatible with the laws of nature, economic reality, or both.  Alleged science and engineering problems that are really human/sociology issues. Part of science and engineering education and training is giving people the skills to recognize which problems belong to which categories.  Confusing these can strongly shape the perception of whether science and engineering research is making progress.  There has been a lot of discussion in the last few years about whether scientific progress (however that is measured) has slowed down or stagnated.  For example, see here: https://www.theatlantic.com/science/archive/2018/11/diminishing-returns-science/575665/  https://news.uchicago.edu/scientific-progress-slowing-james-evans https://www.forbes.com/sites/roberthart/2023/01/04/where-are-all-the-scientific-breakthroughs-forget-ai-nuclear-fusion-and-mrna-vaccines-advances-in-science-and-tech-have-slowed-major-study-says/ https://theweek.com/science/world-losing-scientific-innovation-research A lot of the recent talk is prompted by this 2023 study, which argues that despite the world having many more researchers than ever before (behold population growth) and more global investment in research, somehow "disruptive" innovations are coming less often, or are fewer and farther between these days.  (Whether this is an accurate assessment is not a simple matter to resolve; more on this below.) There is a whole tech bro culture that buys into this, however.  For example, see this interview from last week in the New York Times with Peter Thiel, which points out that Thiel has been complaining about this for a decade and a half.   On some level, I get it emotionally.  The unbounded future spun in a lot of science fiction seems very far away.  Where is my flying car?  Where is my jet pack?  Where is my moon base?  Where are my fusion power plants, my antigravity machine, my tractor beams, my faster-than-light drive?  Why does the world today somehow not seem that different than the world of 1985, while the world of 1985 seems very different than that of 1945? Some of the folks that buy into this think that science is deeply broken somehow - that we've screwed something up, because we are not getting the future they think we were "promised".  Some of these people have this as an internal justification underpinning the dismantling of the NSF, the NIH, basically a huge swath of the research ecosystem in the US.  These same people would likely say that I am part of the problem, and that I can't be objective about this because the whole research ecosystem as it currently exists is a groupthink self-reinforcing spiral of mediocrity.   Science and engineering are inherently human ventures, and I think a lot of these concerns have an emotional component.  My take at the moment is this: Genuinely transformational breakthroughs are rare.  They often require a combination of novel insights, previously unavailable technological capabilities, and luck.  They don't come on a schedule.   There is no hard and fast rule that guarantees continuous exponential technological progress.  Indeed, in real life, exponential growth regimes never last. The 19th and 20th centuries were special.   If we think of research as a quest for understanding, it's inherently hierarchal.  Civilizational collapses aside, you can only discover how electricity works once.   You can only discover the germ theory of disease, the nature of the immune system, and vaccination once (though in the US we appear to be trying really hard to test that by forgetting everything).  You can only discover quantum mechanics once, and doing so doesn't imply that there will be an ongoing (infinite?) chain of discoveries of similar magnitude. People are bad at accurately perceiving rare events and their consequences, just like people have a serious problem evaluating risk or telling the difference between correlation and causation.  We can't always recognize breakthroughs when they happen.  Sure, I don't have a flying car.  I do have a device in my pocket that weighs only a few ounces, gives me near-instantaneous access to the sum total of human knowledge, let's me video call people around the world, can monitor aspects of my fitness, and makes it possible for me to watch sweet videos about dogs.  The argument that we don't have transformative, enormously disruptive breakthroughs as often as we used to or as often as we "should" is in my view based quite a bit on perception. Personally, I think we still have a lot more to learn about the natural world.  AI tools will undoubtedly be helpful in making progress in many areas, but I think it is definitely premature to argue that the vast majority of future advances will come from artificial superintelligences and thus we can go ahead and abandon the strategies that got us the remarkable achievements of the last few decades. I think some of the loudest complainers (Thiel, for example) about perceived slowing advancement are software people.  People who come from the software development world don't always appreciate that physical infrastructure and understanding are hard, and that there are not always clever or even brute-force ways to get to an end goal.  Solving foundational problems in molecular biology or quantum information hardware or  photonics or materials is not the same as software development.  (The tech folks generally know this on an intellectual level, but I don't think all of them really understand it in their guts.  That's why so many of them seem to ignore real world physical constraints when talking about AI.).  Trying to apply software development inspired approaches to science and engineering research isn't bad as a component of a many-pronged strategy, but alone it may not give the desired results - as warned in part by this piece in Science this week.   More frequent breakthroughs in our understanding and capabilities would be wonderful.  I don't think dynamiting the US research ecosystem is the way to get us there, and hoping that we can dismantle everything because AI will somehow herald a new golden age seems premature at best.

yesterday 2 votes
Cryogenic CMOS - a key need for solid state quantum information processing

The basis for much of modern electronics is a set of silicon technologies called CMOS, which stands for complementary metal oxide semiconductor devices and processes.  "Complementary" means using semiconductors (typically silicon) that is locally chemically doped so that you can have both n-type (carriers are negatively charged electrons in the conduction band) and p-type (carriers are positively charged holes in the valence band) material on the same substrate.  With field-effect transistors (using oxide gate dielectrics), you can make very compact, comparatively low power devices like inverters and logic gates.   There are multiple different approaches to try to implement quantum information processing in solid state platforms, with the idea that the scaling lessons of microelectronics (in terms of device density and reliability) can be applied.  I think that essentially all of these avenues require cryogenic operating conditions; all superconducting qubits need ultracold conditions for both superconductivity and to minimize extraneous quasiparticles and other decoherence sources.  Semiconductor-based quantum dots (Intel's favorite) similarly need thermal perturbations and decoherence to be minimized.  The wealth of solid state quantum computing research is the driver for the historically enormous (to me, anyway) growth of dilution refrigerator manufacturing (see my last point here). So you eventually want to have thousands of error-corrected logical qubits at sub-Kelvin temperatures, which may involve millions of physical qubits at sub-Kelvin temperatures, all of which need to be controlled.  Despite the absolute experimental fearlessness of people like John Martinis, you are not going to get this to work by running a million wires from room temperature into your dil fridge.   Fig. 1 from here. The alternative people in this area have converged upon is to create serious CMOS control circuitry that can work at 4 K or below, so that a lot of the wiring does not need to go from the qubits all the way to room temperature.  The materials and device engineering challenges in doing this are substantial!  Power dissipation really needs to be minimized, and material properties to work at cryogenic conditions are not the same as those optimized for room temperature.  There have been major advances in this - examples include Google in 2019, Intel in 2021, IBM in 2024, and this week, folks at the University of New South Wales supported by Microsoft.   In this most recent work, the aspect that I find most impressive is that the CMOS electronics are essentially a serious logic-based control board operating at milliKelvin temperatures right next to the chip with the qubits (in this case, spins-in-quantum-dots).  I'm rather blown away that this works and with sufficiently low power dissipation that the fridge is happy.  This is very impressive, and there is likely a very serious future in store for cryogenic CMOS.

3 days ago 6 votes
Brief items - fresh perspectives, some news bits

As usual, I hope to write more about particular physics topics soon, but in the meantime I wanted to share a sampling of news items: First, it's a pleasure to see new long-form writing about condensed matter subjects, in an era where science blogging has unquestionably shrunk compared to its heyday.  The new Quantum Matters substack by Justin Wilson (and William Shelton) looks like it will be a fun place to visit often. Similar in spirit, I've also just learned about the Knowmads podcast (here on youtube), put out by Prachi Garella and Bhavay Tyagi, two doctoral students at the University of Houston.  Fun Interviews with interesting scientists about their science and how they get it done.   There have been some additional news bits relevant to the present research funding/university-govt relations mess.  Earlier this week, 200 business leaders published an open letter about how the slashing support for university research will seriously harm US economic competitiveness.  More of this, please.  I continue to be surprised by how quiet technology-related, pharma, and finance companies are being, at least in public.  Crushing US science and engineering university research will lead to serious personnel and IP shortages down the line, definitely poor for US standing.  Again, now is the time to push back on legislators about cuts mooted in the presidential budget request.   The would-be 15% indirect cost rate at NSF has been found to be illegal, in a summary court judgment released yesterday.  (Brief article here, pdf of the ruling here.) Along these lines, there are continued efforts for proposals about how to reform/alter indirect cost rates in a far less draconian manner.  These are backed by collective organizations like the AAU and COGR.  If you're interested in this, please go here, read the ideas, and give some feedback.  (Note for future reference:  the Joint Associations Group (JAG) may want to re-think their acronym.  In local slang where I grew up, the word "jag" does not have pleasant connotations.) The punitive attempt to prevent Harvard from taking international students has also been stopped for now in the courts.

a week ago 8 votes
So you want to build a science/engineering laboratory building

A very quick summary of some non-negative news developments: The NSF awarded 500 more graduate fellowships this week, bringing the total for this year up to 1500.  (Apologies for the X link.)  This is still 25% lower than last year's number, and of course far below the original CHIPS and Science act target of 3000, but it's better than the alternative.  I think we can now all agree that the supposed large-scale bipartisan support for the CHIPS and Science act was illusory. There seems to be some initial signs of pushback on the senate side regarding the proposed massive science funding cuts.  Again, now is the time to make views known to legislators - I am told by multiple people with experience in this arena that it really can matter. There was a statement earlier this week that apparently the US won't be going after Chinese student visas.  This would carry more weight if it didn't look like US leadership was wandering ergodically through all possible things to say with no actual plan or memory. On to the main topic of this post.  Thanks to my professional age (older than dirt) and my experience (overseeing shared research infrastructure; being involved in a couple of building design and construction projects; and working on PI lab designs and build-outs), I have some key advice and lessons learned for anyone designing a new big science/engineering research building.  This list is by no means complete, and I invite readers to add their insights in the comments.  While it seems likely that many universities will be curtailing big capital construction projects in the near term because of financial uncertainty, I hope this may still come in handy to someone.   Any big laboratory building should have a dedicated loading dock with central receiving.  If you're spending $100M-200M on a building, this is not something that you should "value engineer" away.  The long term goal is a building that operates well for the PIs and is easy to maintain, and you're going to need to be able to bring in big crates for lab and service equipment.  You should have a freight elevator adjacent to the dock.   You should also think hard about what kind of equipment will have to be moved in and out of the building when designing hallways, floor layouts, and door widths.  You don't want to have to take out walls, doorframes, or windows, or to need a crane to hoist equipment into upper floors because it can't get around corners. Think hard about process gasses and storage tanks at the beginning.  Will PIs need to have gas cylinders and liquid nitrogen and argon tanks brought in and out in high volumes all the time, with all the attendant safety concerns?  Would you be better off getting LN2 or LAr tanks even though campus architects will say they are unsightly?   Likewise, consider whether you should have building-wide service for "lab vacuum", N2 gas, compressed air, DI water, etc.  If not and PIs have those needs, you should plan ahead to deal with this. Gas cylinder and chemical storage - do you have enough on-site storage space for empty cylinders and back-up supply cylinders?  If this is a very chemistry-heavy building, think hard about safety and storing solvents.  Make sure you design for adequate exhaust capacity for fume hoods.  Someone will always want to add more hoods.  While all things are possible with huge expenditures, it's better to make sure you have capacity to spare, because adding hoods beyond the initial capacity would likely require a huge redo of the building HVAC systems. Speaking of HVAC, think really hard about controls and monitoring.  Are you going to have labs that need tight requirements on temperature and humidity?  When you set these up, put have enough sensors of the right types in the right places, and make sure that your system is designed to work even when the outside air conditions are at their seasonal extremes (hot and humid in the summer, cold and dry in the winter).  Also, consider having a vestibule (air lock) for the main building entrance - you'd rather not scoop a bunch of hot, humid air (or freezing, super-dry air) into the building every time a student opens the door. Still on HVAC, make sure that power outages and restarts don't lead to weird situations like having the whole building at negative pressure relative to the outside, or duct work bulging or collapsing. Still on HVAC, actually think about where the condensate drains for the fan units will overflow if they get plugged up or overwhelmed.  You really don't want water spilling all over a rack of networking equipment in an IT closet.  Trust me. Chilled water:  Whether it's the process chilled water for the air conditioning, or the secondary chilled water for lab equipment, make sure that the loop is built correctly.   Incompatible metals (e.g., some genius throws in a cast iron fitting somewhere, or joints between dissimilar metals) can lead to years and years of problems down the line.  Make sure lines are flushed and monitored for cleanliness, and have filters in each lab that can be checked and maintained easily. Electrical - design with future needs in mind.  If possible, it's a good idea to have PI labs with their own isolation transformers, to try to mitigate inter-lab electrical noise issues.  Make sure your electrical contractors understand the idea of having "clean" vs. "dirty" power and can set up the grounding accordingly while still being in code. Still on electrical, consider building-wide surge protection, and think about emergency power capacity.  For those who don't know, emergency power is usually a motor-generator that kicks in after a few seconds to make sure that emergency lighting and critical systems (including lab exhaust) keep going. Ceiling heights, duct work, etc. - It's not unusual for some PIs to have tall pieces of equipment.  Think about how you will accommodate these.  Pits in the floors of basement labs?  5 meter slab-to-slab spacing?  Think also about how ductwork and conduits are routed.  You don't want someone to tell you that installation of a new apparatus is going to cost a bonus $100K because shifting a duct sideways by half a meter will require a complete HVAC redesign. Think about the balance between lab space and office space/student seating.  No one likes giant cubicle farm student seating, but it does have capacity.  In these days of zoom and remote access to experiments, the way students and postdocs use offices is evolving, which makes planning difficult.  Health and safety folks would definitely prefer not to have personnel effectively headquartered directly in lab spaces.  Seriously, though, when programming a building, you need to think about how many people per PI lab space will need places to sit.  I have yet to see a building initially designed with enough seating to handle all the personnel needs if every PI lab were fully occupied and at a high level of research activity.  Think about maintenance down the line.  Every major building system has some lifespan.  If a big air handler fails, is it accessible and serviceable, or would that require taking out walls or cutting equipment into pieces and disrupting the entire building?  Do you want to set up a situation where you may have to do this every decade?  (Asking for a friend.) Entering the realm of fantasy, use your vast power and influence to get your organization to emphasize preventative maintenance at an appropriate level, consistently over the years.  Universities (and national labs and industrial labs) love "deferred maintenance" because kicking the can down the road can make a possible cost issue now into someone else's problem later.  Saving money in the short term can be very tempting.  It's also often easier and more glamorous to raise money for the new J. Smith Laboratory for Physical Sciences than it is to raise money to replace the HVAC system in the old D. Jones Engineering Building.  Avoid this temptation, or one day (inevitably when times are tight) your university will notice that it has $300M in deferred maintenance needs. I may update this list as more items occur to me, but please feel free to add input/ideas.

2 weeks ago 11 votes
A precision measurement science mystery - new physics or incomplete calculations?

Again, as a distraction from persistently concerning news, here is a science mystery of which I was previously unaware. The role of approximations in physics is something that very often comes as a shock to new students.  There is this cultural expectation out there that because physics is all about quantitative understanding of physical phenomena, and the typical way we teach math and science in K12 education, we should be able to get exact solutions to many of our attempts to model nature mathematically.   In practice, though, constructing physics theories is almost always about approximations, either in the formulation of the model itself (e.g. let's consider the motion of an electron about the proton in the hydrogen atom by treating the proton as infinitely massive and of negligible size) or in solving the mathematics (e.g., we can't write an exact analytical solution of the problem when including relativity, but we can do an order-by-order expansion in powers of \(p/mc\)).  Theorists have a very clear understanding of what means to say that an approximation is "well controlled" - you know on both physical and mathematical grounds that a series expansion actually converges, for example.   Some problems are simpler than others, just by virtue of having a very limited number of particles and degrees of freedom, and some problems also lend themselves to high precision measurements.  The hydrogen atom problem is an example of both features.  Just two spin-1/2 particles (if we approximate the proton as a lumped object) and readily accessible to optical spectroscopy to measure the energy levels for comparison with theory.  We can do perturbative treatments to account for other effects of relativity, spin-orbit coupling, interactions with nuclear spin, and quantum electrodynamic corrections (here and here).  A hallmark of atomic physics is the remarkable precision and accuracy of these calculations when compared with experiment.  (The \(g\)-factor of the electron is experimentally known to a part in \(10^{10}\) and matches calculations out to fifth order in \(\alpha = e^2/(4 \pi \epsilon_{0}\hbar c)\).).   The helium atom is a bit more complicated, having two electrons and a more complicated nucleus, but over the last hundred years we've learned a lot about how to do both calculations and spectroscopy.   As explained here, there is a problem.  It is possible to put helium into an excited metastable triplet state with one electron in the \(1s\) orbital, the other electron in the \(2s\) orbital, and their spins in a triplet configuration.  Then one can measure the ionization energy of that system - the minimum energy required to kick an electron out of the atom and off to infinity.  This energy can be calculated to seventh order in \(\alpha\), and the theorists think that they're accounting for everything, including the finite (but tiny) size of the nucleus.  The issue:  The calculation and the experiment differ by about 2 nano-eV.  That may not sound like a big deal, but the experimental uncertainty is supposed to be a little over 0.08 nano-eV, and the uncertainty in the calculation is estimated to be 0.4 nano-eV.  This works out to something like a 9\(\sigma\) discrepancy.  Most recently, a quantitatively very similar discrepancy shows up in the case of measurements performed in 3He rather than 4He.   This is pretty weird.  Historically, it would seem that the most likely answer is a problem with either the measurements (though that seems doubtful, since precision spectroscopy is such a well-developed set of techniques), the calculation (though that also seems weird, since the relevant physics seems well known), or both.  The exciting possibility is that somehow there is new physics at work that we don't understand, but that's a long shot.  Still, something fun to consider (as my colleagues (and I) try to push back on the dismantling of US scientific research.)

3 weeks ago 13 votes

More in science

The Hidden Engineering of Liquid Dampers in Skyscrapers

[Note that this article is a transcript of the video embedded above.] There’s a new trend in high-rise building design. Maybe you’ve seen this in your city. The best lots are all taken, so developers are stretching the limits to make use of space that isn’t always ideal for skyscrapers. They’re not necessarily taller than buildings of the past, but they are a lot more slender. “Pencil tower” is the term generally used to describe buildings that have a slenderness ratio of more than around 10 to 1, height to width. A lot of popular discussion around skyscrapers is about how tall we can build them. Eventually, you can get so tall that there are no materials strong enough to support the weight. But, pencil towers are the perfect case study in why strength isn’t the only design criterion used in structural engineering. Of course, we don’t want our buildings to fall down, but there’s other stuff we don’t want them to do, too, including flex and sway in the wind. In engineering, this concept is called the serviceability limit state, and it’s an entirely separate consideration from strength. Even if moderate loads don’t cause a structure to fail, the movement they cause can lead to windows breaking, tiles cracking, accelerated fatigue of the structure, and, of course, people on the top floors losing their lunch from disorientation and discomfort. So, limiting wind-induced motions is a major part of high-rise design and, in fact, can be such a driving factor in the engineering of the building that strength is a secondary consideration. Making a building stiffer is the obvious solution. But adding stiffness requires larger columns and beams, and those subtract valuable space within the building itself. Another option is to augment a building’s aerodynamic performance, reducing the loads that winds impose. But that too can compromise the expensive floorspace within. So many engineers are relying on another creative way to limit the vibrations of tall buildings. And of course, I built a model in the garage to show you how this works. I’m Grady, and this is Practical Engineering. One of the very first topics I ever covered on this channel was tuned mass dampers. These are mechanisms that use a large, solid mass to counteract motion in all kinds of structures, dissipating the energy through friction or hydraulics, like the shock absorbers in vehicles. Probably the most famous of these is in the Taipei 101 building. At the top of the tower is a massive steel pendulum, and instead of hiding it away in a mechanical floor, they opened it to visitors, even giving the damper its own mascot. But, mass dampers have a major limitation because of those mechanical parts. The complex springs, dampers, and bearings need regular maintenance, and they are custom-built. That gets pretty expensive. So, what if we could simplify the device? This is my garage-built high-rise. It’s not going to hold many conference room meetings, but it does do a good job swaying from side to side, just like an actual skyscraper. And I built a little tank to go on top here. The technical name for this tank is a tuned liquid column damper, and I can show you how it works. Let’s try it with no water first. Using my digitally calibrated finger, I push the tower over by a prescribed distance, and you can see this would not be a very fun ride. There is some natural damping, but the oscillation goes on for quite a while before the motion stops. Now, let’s put some water in the tank. With the power of movie magic, I can put these side by side so you can really get a sense of the difference. By the way, nearly all of the parts for this demonstration were provided by my friends at Send-Cut-Send. I don’t have a milling machine or laser cutter, so this is a really nice option for getting customized parts made from basically any material - aluminum, steel, acrylic - that are ready to assemble. Instead of complex mechanical devices, liquid column dampers dissipate energy through the movement of water. The liquid in the tank is both the mass and the damper. This works like a pendulum where the fluid oscillates between two columns. Normally, there’s an orifice between the two columns that creates the damping through friction loss as water flows from one side to the other. To make this demo a little simpler, I just put lids on the columns with small holes. I actually bought a fancy air valve to make this adjustable, but it didn’t allow quite enough airflow. So instead, I simplified with a piece of tape. Very technical. Energy transferred to the water through the building is dissipated by the friction of the air as it moves in and out of the columns. And you can even hear this as it happens. Any supplemental damping system starts with a design criterion. This varies around the world, but in the US, this is probability-based. We generally require that peak accelerations with a 1-in-10 chance of being exceeded in a given year be limited to 15-18 milli-gs in residential buildings and 20-25 milli-gs in offices. For reference, the lateral acceleration for highway curve design is usually capped at 100 milli-gs, so the design criteria for buildings is between a fourth and a sixth of that. I think that makes intuitive sense. You don’t want to feel like you’re navigating a highway curve while you sit at your desk at work. It’s helpful to think of these systems in a simplified way. This is the most basic representation: a spring, a damper, and mass on a cart. We know the mass of the building. We can estimate its stiffness. And the building itself has some intrinsic damping, but usually not much. If we add the damping system onto the cart, it’s basically just the same thing at a smaller scale, and the design process is really just choosing the mass and damping systems for the remaining pieces of this puzzle to achieve the design goal. The mass of liquid dampers is usually somewhere between half a percent to two percent of the building’s total weight. The damping is related to the water’s ability to dissipate energy. And the spring needs to be tuned to the building. All buildings vibrate at a natural frequency related to their height and stiffness. Think of it like a big tuning fork full of offices or condos. I can estimate my model’s natural frequency by timing the number of oscillations in a given time interval. It’s about 1.3 hertz or cycles per second. In an ideal tuned damper, the oscillation of the damping system matches that of the building. So tuning the frequency of the damper is an important piece of the puzzle. For a tuned liquid column damper, the tuning mostly comes from the length of the liquid flow path. A longer path results in a lower frequency. The compression of the air above the column in my demo affects this too, and some types of dampers actually take advantage of that phenomenon. I got the best tuning when the liquid level was about halfway up the columns. The orifice has less of an effect on frequency and is used mostly to balance the amount of damping versus the volume of liquid that flows through each cycle. In my model, with one of the holes completely closed off, you can see the water doesn’t move, and you get minimal damping. With the tape mostly covering the hole, you get the most frictional loss, but not all the fluid flows from one side to the other each cycle. When I covered about half of one hole, I got the full fluid flow and the best damping performance. The benefit of a tuned column damper is that it doesn’t take up a lot of space. And because the fluid movement is confined, they’re fairly predictable in behavior. So, these are used in quite a few skyscrapers, including the Random House Tower in Manhattan, One Wall Center in Vancouver (which actually has many walls), and Comcast Center in Philadelphia. But, tuned column liquid dampers have a few downsides. One is that they really only work for flexible structures, like my demo. Just like in a pendulum, the longer the flow path in a column damper, the lower the frequency of the oscillation. For stiffer buildings with higher natural frequencies, tuning requires a very short liquid column, which limits the mass and damping capability to a point where you don’t get much benefit. The other thing is that this is still kind of a complex device with intricate shapes and a custom orifice between the two columns. So, we can get even simpler. This is my model tuned sloshing damper, and it’s about as simple as a damper can get. I put a weight inside the empty tank to make a fair comparison, and we can put it side by side with water in the tank to see how it works. As you can see, sloshing dampers dissipate energy by… sloshing. Again, the water is both the mass and the damper. If you tune it just right, the sloshing happens perfectly out of phase of the motion of the building, reducing the magnitude of the movement and acceleration. And you can see why this might be a little cheaper to build - it’s basically just a swimming pool - four concrete walls, a floor, and some water. There’s just not that much to it. But the simplicity of construction hides the complexity of design. Like a column damper, the frequency of a sloshing damper can be tuned, first by the length of the tank. Just like fretting a guitar string further down the neck makes the note lower, a tank works the same way. As the tank gets longer, its sloshing frequency goes down. That makes sense - it takes longer for the wave to get from one side to the other. But you can also adjust the depth. Waves move slower in shallower water and faster in deeper water. Watch what happens when I overfill the tank. The initial wave starts on the left as the building goes right. It reaches the right side just as the building starts moving left. That’s what we want; it’s counteracting the motion. But then it makes it back to the left before the building starts moving right. It’s actually kind of amplifying the motion, like pushing a kid on a swing. Pretty soon after that, the wave and the building start moving in phase, so there’s pretty much no damping at all. Compare it to the more properly tuned example where most of the wave motion is counteracting the building motion as it sways back and forth. You can see in my demo that a lot of the energy dissipation comes from the breaking waves as they crash against the sides of the tank. That is a pretty complicated phenomenon to predict, and it’s highly dependent on how big the waves are. And even with the level pretty well tuned to the frequency of the building, you can see there’s a lot of complexity in the motion with multiple modes of waves, and not all of them acting against the motion of the building. So, instead of relying on breaking waves, most sloshing dampers use flow obstructions like screens, columns, or baffles. I got a few different options cut out of acrylic so we can try this out. These baffles add drag, increasing the energy dissipation with the water, usually without changing the sloshing frequency. Here’s a side-by-side comparison of the performance without a baffle and with one. You can see that the improvement is pretty dramatic. The motion is more controlled and the behavior is more linear, making this much simpler to predict during the design phase. It’s kind of the best of both worlds since you get damping from the sloshing and the drag of the water passing through the screen. Almost all the motion is stopped in this demo after only three oscillations. I was pretty impressed with this. Here’s all three of the baffle runs side by side. Actually, the one with the smallest holes worked the best in my demo, but deciding the configuration of these baffles is a big challenge in the engineering of these systems because you can’t really just test out a bunch of options at full scale. Devices like this are in service in quite a few high-rise buildings, including Princess Tower in Dubai, and the Museum Tower in Dallas. With no moving parts and very little maintenance except occasionally topping it off to keep the water at the correct level, you can see how it would be easy to choose a sloshing damper for a new high-rise project. But there are some disadvantages. One is volumetric efficiency. You can see that not all the water in the tank is mobilized, especially for smaller movements, which means not all the water is contributing to the damping. The other is non-linearity. The amount of damping changes depending on the magnitude of the movement since drag is related to velocity squared. And even the frequency of the damper isn’t constant; it can change with the wave amplitude as well because of the breaking waves. So you might get good performance at the design level, but not so much for slower winds. Dampers aren’t just used in buildings. Bridges also take advantage of these clever devices, especially on the decks of pedestrian bridges and the towers of long-span bridges. This also happens at a grand scale between the Earth and moon. Tidal bulges in the oceans created by the moon’s tug on Earth dissipate energy through friction and turbulence, which is a big part of why our planet’s rotation is slowing over time. Days used to be a lot shorter when the Earth was young, but we have a planet-scale liquid damper constantly dissipating our rotational energy. But whether it’s bridges or buildings, these dampers usually don’t work perfectly right at the start. Vibrations are complicated. They’re very hard to predict, even with modern tools like simulation software and scale physical models. So, all dampers have to go through a commissioning process. Usually this involves installing accelerometers once construction is nearing completion to measure the structure’s actual natural frequency. The tuning of tuned dampers doesn’t just happen during the design phase; you want some adjustability after construction to make sure they match the structure’s natural frequency exactly so you get the most damping possible. For liquid dampers, that means adjusting the levels in the tanks. And in many cases, buildings might use multiple dampers tuned to slightly different frequencies to improve the performance over a range of conditions. Even in these two basic categories, there is a huge amount of variability and a lot of ongoing research to minimize the tradeoffs these systems come with. The truth is that, relatively speaking, there aren’t that many of these systems in use around the world. Each one is highly customized, and even putting them into categories can get a little tricky. There are even actively controlled liquid dampers. My tuning for the column damper works best for a single magnitude of motion, but you can see that once the swaying gets smaller, the damper isn’t doing a lot to curb it. You can imagine if I constantly adjusted the size of the orifice, I could get better performance over a broader range of unwanted motion. You can do this electronically by having sensors feed into a control system that adjusts a valve position in real-time. Active systems and just the flexibility to tune a damper in general also help deal with changes over time. If a building’s use changes, if new skyscrapers nearby change the wind conditions, or if it gets retrofits that change its natural frequency, the damping system can easily accommodate those changes. In the end, a lot of engineering decisions come down to economics. In most cases, damping is less about safety and more about comfort, which is often harder to pin down. Engineers and building owners face a balancing act between the cost of supplemental damping and the value of the space those systems take up. Tuned mass dampers are kind of household names when it comes to damping. A few buildings like Shanghai Center and Taipei 101 have made them famous. They’re usually the most space-efficient (since steel and concrete are more dense than water). But they’re often more costly to install and maintain. Liquid dampers are the unsung heroes. They take up more space, but they’re simple and cost-effective, especially if the fire codes already require you to have a big tank of water at the top of your building anyway. Maybe someday, an architect will build one out of glass or acrylic, add some blue dye and mica powder, and put it on display as a public showcase. Until then, we’ll just have to know it’s there by feel.

6 hours ago 2 votes
London Inches Closer to Running Transit System Entirely on Renewable Power

Under a new agreement, London will source enough solar power to run its light railway and tram networks entirely on renewable energy. Read more on E360 →

14 hours ago 1 votes
Science slow down - not a simple question

I participated in a program about 15 years ago that looked at science and technology challenges faced by a subset of the US government. I came away thinking that such problems fall into three broad categories. Actual science and engineering challenges, which require foundational research and creativity to solve. Technology that may be fervently desired but is incompatible with the laws of nature, economic reality, or both.  Alleged science and engineering problems that are really human/sociology issues. Part of science and engineering education and training is giving people the skills to recognize which problems belong to which categories.  Confusing these can strongly shape the perception of whether science and engineering research is making progress.  There has been a lot of discussion in the last few years about whether scientific progress (however that is measured) has slowed down or stagnated.  For example, see here: https://www.theatlantic.com/science/archive/2018/11/diminishing-returns-science/575665/  https://news.uchicago.edu/scientific-progress-slowing-james-evans https://www.forbes.com/sites/roberthart/2023/01/04/where-are-all-the-scientific-breakthroughs-forget-ai-nuclear-fusion-and-mrna-vaccines-advances-in-science-and-tech-have-slowed-major-study-says/ https://theweek.com/science/world-losing-scientific-innovation-research A lot of the recent talk is prompted by this 2023 study, which argues that despite the world having many more researchers than ever before (behold population growth) and more global investment in research, somehow "disruptive" innovations are coming less often, or are fewer and farther between these days.  (Whether this is an accurate assessment is not a simple matter to resolve; more on this below.) There is a whole tech bro culture that buys into this, however.  For example, see this interview from last week in the New York Times with Peter Thiel, which points out that Thiel has been complaining about this for a decade and a half.   On some level, I get it emotionally.  The unbounded future spun in a lot of science fiction seems very far away.  Where is my flying car?  Where is my jet pack?  Where is my moon base?  Where are my fusion power plants, my antigravity machine, my tractor beams, my faster-than-light drive?  Why does the world today somehow not seem that different than the world of 1985, while the world of 1985 seems very different than that of 1945? Some of the folks that buy into this think that science is deeply broken somehow - that we've screwed something up, because we are not getting the future they think we were "promised".  Some of these people have this as an internal justification underpinning the dismantling of the NSF, the NIH, basically a huge swath of the research ecosystem in the US.  These same people would likely say that I am part of the problem, and that I can't be objective about this because the whole research ecosystem as it currently exists is a groupthink self-reinforcing spiral of mediocrity.   Science and engineering are inherently human ventures, and I think a lot of these concerns have an emotional component.  My take at the moment is this: Genuinely transformational breakthroughs are rare.  They often require a combination of novel insights, previously unavailable technological capabilities, and luck.  They don't come on a schedule.   There is no hard and fast rule that guarantees continuous exponential technological progress.  Indeed, in real life, exponential growth regimes never last. The 19th and 20th centuries were special.   If we think of research as a quest for understanding, it's inherently hierarchal.  Civilizational collapses aside, you can only discover how electricity works once.   You can only discover the germ theory of disease, the nature of the immune system, and vaccination once (though in the US we appear to be trying really hard to test that by forgetting everything).  You can only discover quantum mechanics once, and doing so doesn't imply that there will be an ongoing (infinite?) chain of discoveries of similar magnitude. People are bad at accurately perceiving rare events and their consequences, just like people have a serious problem evaluating risk or telling the difference between correlation and causation.  We can't always recognize breakthroughs when they happen.  Sure, I don't have a flying car.  I do have a device in my pocket that weighs only a few ounces, gives me near-instantaneous access to the sum total of human knowledge, let's me video call people around the world, can monitor aspects of my fitness, and makes it possible for me to watch sweet videos about dogs.  The argument that we don't have transformative, enormously disruptive breakthroughs as often as we used to or as often as we "should" is in my view based quite a bit on perception. Personally, I think we still have a lot more to learn about the natural world.  AI tools will undoubtedly be helpful in making progress in many areas, but I think it is definitely premature to argue that the vast majority of future advances will come from artificial superintelligences and thus we can go ahead and abandon the strategies that got us the remarkable achievements of the last few decades. I think some of the loudest complainers (Thiel, for example) about perceived slowing advancement are software people.  People who come from the software development world don't always appreciate that physical infrastructure and understanding are hard, and that there are not always clever or even brute-force ways to get to an end goal.  Solving foundational problems in molecular biology or quantum information hardware or  photonics or materials is not the same as software development.  (The tech folks generally know this on an intellectual level, but I don't think all of them really understand it in their guts.  That's why so many of them seem to ignore real world physical constraints when talking about AI.).  Trying to apply software development inspired approaches to science and engineering research isn't bad as a component of a many-pronged strategy, but alone it may not give the desired results - as warned in part by this piece in Science this week.   More frequent breakthroughs in our understanding and capabilities would be wonderful.  I don't think dynamiting the US research ecosystem is the way to get us there, and hoping that we can dismantle everything because AI will somehow herald a new golden age seems premature at best.

yesterday 2 votes
Researchers Uncover Hidden Ingredients Behind AI Creativity

Image generators are designed to mimic their training data, so where does their apparent creativity come from? A recent study suggests that it’s an inevitable by-product of their architecture. The post Researchers Uncover Hidden Ingredients Behind AI Creativity first appeared on Quanta Magazine

yesterday 2 votes
Animals Adapting to Cities

Humans are dramatically changing the environment of the Earth in many ways. Only about 23% of the land surface (excluding Antarctica) is considered to be “wilderness”, and this is rapidly decreasing. What wilderness is left is also mostly managed conservation areas. Meanwhile, about 3% of the surface is considered urban. I could not find a […] The post Animals Adapting to Cities first appeared on NeuroLogica Blog.

yesterday 2 votes