Recent superconductivity results + open positions at Rice

Much as I feel like I should write about the latest developments in US science policy, instead I want to point out two exciting recent superconductivity results.  Below I will also append a couple of other items, including open positions at Rice.

• 

  After Fig. 2b from here

  In this paper, researchers demonstrated high temperature superconductivity in a monolayer of Bi\(_2\)Sr\(_2\)CuO\(_{6+\delta}\) (Bi-2201).  The monolayer contains just a single CuO\(_2\) plane, and remarkably, the superconducting transition is only suppressed about 10% from the bulk value of around 35 K.  The authors were able to explore the phase diagram by tuning the oxygen content in situ, using vacuum annealing to drive out oxygen and ozone exposure to (seemingly gently) put it back in.  This allows them to examine a large swath of temperature/doping/magnetic field parameter space, showing evidence of critical scaling of the resistance near the transition as well as an anomalous metallic state.  There's a lot to digest here.  The mapped out zero-field phase diagram in a single device (shown here) is extremely impressive.  Studies like this can hopefully give new insights into what physics is truly essential to achieve high temperature superconductivity.
• In this paper, investigators placed exfoliated NbSe\(_2\) encapsulated by hBN in a split-ring resonator cavity, and they observed enhanced critical temperature (by 0.15 K out of 6.53 K, or an increase of 2.3%), critical field, and critical current when the resonance frequency of the cavity is such that it apparently couples to superconducting fluctuations in the material on the spatial scale of the cavity.  There is a ton of interest in using electromagnetic cavities to modify the properties of quantum materials - see this review.  As far as I know, this is the first time that coupling to the vacuum mode of a cavity has actually enhanced superconducting properties.  Exciting times.

It's worth noting that both of these papers come out of the same group (!) at USTC in China.  

In other news:

• 
  The NSF is going to make about half the number of awards this year as it did in The Before Times (2021-2024), according to this news article in Nature.  Figure 1 (shown here) is striking.  The claim is that the NSF leadership is taking clawed-back FY26 funding of around $1B and saving it for some as-yet unspecified, unannounced OSTP "grand challenges" project.  
  
• NSF also announced "new" funding opportunities here.  As described in that article linked above, these are not exactly new - it's essentially a reorganization/rebranding of much of the NSF's portfolio now that they've eliminated divisions and retired older funding solicitations.  Noteworthy is that the amount of funding mentioned in these solicitations is all considerably lower than what the aggregate of the older solicitations used to have.  As a non-expert, it looks a lot like these solicitations are being prepared as if the presidential budget requested funding levels (you know, the ones that want to cut NSF by more than half) are the baseline.

Meanwhile, at Rice we have some faculty searches underway:

• The Rice Advanced Materials Institute is searching for an assistant professor with an expertise in computational materials (including AI/ML).  See here.
• Our chemistry department is searching for an assistant professor position with an emphasis including physical chemistry.  See here. 
• There will also be an AMO physics position posted shortly - I'll update with the link when that becomes available.

Finally, Nano Letters is having a seed grant competition for grad students.  It's not much money, but it is good experience and can inspire graduate student creativity. (Full disclosure: I'm an associate editor for the journal.)

NSF - public comment, APS feedback opportunity

In case you weren't aware, in addition to the OMB proposed rule changes which just concluded their public comment period, the NSF has put forward proposed changes in their proposal procedures for public comment, and the last day for feedback is August 24.  The proposal and award policies and procedures guide (PAPPG) is to be replaced with the revised document called the "Guide for Financial Assistance" (GFA).

The proposed revised document is here: https://www.regulations.gov/document/NSF-2026-OTR-0001-0003 

The place to file a comment is here: https://www.regulations.gov/docket/NSF-2026-OTR-0001/document?withinCommentPeriod=true

The place read already-filed comments is here: https://www.regulations.gov/docket/NSF-2026-OTR-0001/comments

The Federation of American Societies for Experimental Biology has a brief summary of the proposed changes here.  There are a number of (IMO) problematic issues with the would-be revisions, not the least of which is they presumptively assume that the OMB changes are going into effect, including the very controversial ones that would allow termination of awards at any time, for any reason (including not aligning with presidential priorities), with no appeal.  It's a good idea to be aware of what's being proposed and to take advantage of the opportunity to provide feedback.  

Update:  The APS has also put together a guide to the proposed changes.

Speaking of feedback, the American Physical Society is doing a broad survey (beyond just physicists) asking for input about up to three things that people think the NSF does well and up to three things that the NSF should do differently.  It's open to everyone, and the response spaces are brief (500 char ea.). Again, if this is something that matters to you, I encourage you to contribute - it's quick.  

Reproducibility in materials research, and an anecdote

Yesterday I attended the 40th annual summer research colloquium of the Smalley-Curl Institute at Rice, a fun internal conference that provides a great opportunity for undergrads (including visitors), graduate students, and a few postdocs to present their work.  The keynote speaker was our EVPR, Prof. David Sholl, who gave a very informative talk about reproducibility in the chemical engineering/materials literature.  We hear a lot these days about crises of reproducibility in scientific research, and Prof. Sholl rightly points out that in some fields the expectation of reproducible results is high - no one would spend $1B on a chemical engineering plant if they weren't very sure that the catalytic processes were going to work as expected at scale.  Keys to reproducibility include, unsurprisingly, repeated results and independent replication.  One metaresult that was interesting is this paper, looking at the literature on metal-organic frameworks and how often there are published replications of syntheses; not as often as you would think or want!  

A truly surprising (to me, anyway) result is this one.  The Brunauer–Emmett–Teller (BET) (yes, that Teller) method is a long-established technique that uses gas adsorption measurements to infer the surface area of porous materials.  Many research groups were given identical raw adsorption isotherms and asked to calculate the specific surface areas, resulting in a surprisingly large spread of results (Fig 1 of the paper).  Clearly not everyone had the same analysis procedures even for a technique developed in the 1930s!

Some take-away lessons from this are encapsulated here, in an article titled "Five easy ways to make your research more reproducible".  Good stuff.  The talk raised a number of questions relevant to our present era of huge enthusiasm about AI-based materials research and "self-driving" labs.  If the AI models are all trained on the literature, and the literature is not representative of complete and reproducible procedures, that's a problem.  

One personal anecdote about reproducibility and its challenges in materials synthesis.  Twenty years ago (!), I was working with a colleague who had a postdoc who was synthesizing Fe3O4 (magnetite) nanoparticles via wet chemistry methods (see here). We did some fun electronic transport experiments bridging very closely spaced electrodes with such nanoparticles, and we saw some very dramatic hysteretic response kick in as \(T\) was reduced below about 120 K.  That's the temperature of the Verwey transition in magnetite, where the material enters a more insulating low temperature phase.  Basically all of the devices we made with that batch of nanoparticles showed this phenomenon.  Then the postdoc took up a faculty position and a senior grad student came in and took over the synthesis, and for several months, subsequent batches of nanoparticles just didn't seem to show the effect.  The key issue is oxygen stoichiometry.  Get a little oxygen rich, and you form nanoparticles that include some \(\gamma\)-Fe2O3, which doesn't have the Verwey physics and in nanoparticle form looks really similar in x-ray diffraction to the desired magnetite.  Anyway, we started working with a collaborator who could grow epitaxial Fe3O4 films, and in those devices the electronic effect was there all the time.  All this led to this publication and subsequent papers, and I still think it's a cool set of results about a nonequilibrium transition in a correlated material.  In the end, after several months the chemistry grad student did get back to making nanoparticle batches that showed the transition. It turns out that at some point he had changed the length of a piece of tubing in the gas manifold, and unexpectedly that had altered the reaction kinetics just a little.  Changing it back got the synthesis to be reliable again.  This is an example of how finicky materials synthesis can be!

PhDs - how long a doctorate should take, and a new pilot program

I think it's safe to say that most people who've considered the issue think that a doctoral degree in the sciences and engineering in the US often takes too long.  

How long?  According to the latest data (see here, Table 1-12), the median time to degree in the physical sciences, for example, is 5.7 years after starting the program, while in all of engineering it's 5.3 years.  

Too long for what?  Well, life, basically.  Any decision to go to grad school is inherently a trade-off with opportunity costs.  Graduate stipends remain low compared to expected wages in entry-level (bachelors degree-qualified) positions in the sciences and engineering in industry.  The long duration of doctoral programs is certainly a powerful disincentive for many who might be interested but are under financial pressures.  Family considerations are also a major factor.  From the perspective of basically any career path, thanks to the time value of money and ideas of seniority, it's better to get going earlier if you have the qualifications for the particular job.  Companies would rather higher younger (cheaper) people.

So, there are already strong reasons to think about shortening doctoral programs.  Now, with the proposed change in duration of status of student visas (rule here, with plenty of editorializing; legal challenges very likely forthcoming in September) to four years, there is additional pressure. 

Why do US programs take so long?  Don't they give PhDs in three years in the UK and Europe?  In the UK and Europe, a student enters a doctoral program after already pursuing and receiving a masters degree, with grad level coursework taking place there.  Thus they go directly into research.  In the US, in contrast, it is far more common for students to go directly into the doctoral program.  Likewise, in the US, it is far more common for funding for students to go through PI-written research proposals, while in the UK, the students come funded, so to speak.  

Enter a new pilot program from NSF, the UIDP [University Industry Demonstrated Partnership] Industry-Integrated PhD Scholars Program (I-PhD). The idea is to shorten the doctorate to four years, with at least one of those years on-site at a company.  As the announcement says, "Students' first year of funding will be provided by their universities, with the remaining years covered by NSF. Industry partners will provide matching commitments to cover at least one year of practical experience conducting dissertation research at a company site. Students will be co-advised by academic and industry mentors, equipping them with critical skills for their future careers."  The initial plan is $47M over five years, and there will be a webinar (see here) next week about this.   (Up front, I do want to disagree with the framing that existing PhD programs are geared exclusively for academic careers.  It's well established that the fraction of PhDs in the sciences and engineering who go on to become faculty is low, and most go into industry.  Faculty PIs know this.  Students know this.  The problem solving and analytical skills taught in doctoral programs remain highly valued outside academia, at least until AI replaces us all.)

This is certainly a very interesting pilot program.  There are rumors that the DOE Genesis Mission is going to put something extremely similar in place as well.   The implementation details will be enormously important.  (For example:  Who is eligible?  Who handles the coordination between industry and the university - that is, who does the match-making and how?   At the department-company level and at the particular academic/industrial advisor level?   How will intellectual property be handled?  Publications?  Project design? If there are economic challenges, how committed are the companies?)  Given that this is a form of NSF fellowship, it seems highly likely that it will only be open to US citizens and permanent residents.  Obviously, not every discipline is well-suited to this, in terms of there being a ready supply of companies set to buy in.  Still, it is absolutely worth seeing how this works.

Update:  Thanks to one of my colleagues for pointing out the fine print, which is here.  In brief, as expected this is only open to US citizens and permanent residents.  No indirect costs allowed.  There is a $16K cost-of-education piece that looks like a substitute for grad tuition.  The intellectual property issues have to be ironed out between the university and the company before the start.  Perhaps not unexpectedly, this is most likely to work well for programs and PIs who already have close collaborations with particular companies.  Engineering disciplines are most likely to fit well here, it seems, while basic research farther away from applications will have more challenges.  (Question:  will finance companies or AI materials companies be interested in supporting theorist/computational scientists through this mechanism?)

Papers and news items

First, some science, clearing out a number of papers and articles that I've been collecting for some time in my far-too-numerous browser tabs:

• I've written before (here) about dimensional analysis and similarity, techniques commonly used in the engineering world that can seem quasi-miraculous at times.  This paper gets into why this approach works, and different categories of physical similarity.  I'd mentioned it when the book came out, but this kind of thinking is also a key component of Anthony Zee's Fly by Night Physics.
• This review article is about fundamental limits in photonics and electromagnetics.  This is a very handy review that I'm going to point my students toward.
• On a lighter note, a colleague pointed me to this collection of (AI-generated) songs related to thermodynamics.    
• Speaking of thermodynamics, here is a recent paper about the thermodynamic description of wealth inequality (treating the flow of money in a physics formalism - see here for a prior discussion.).  Edging closer....  
• There was a nice post on substack about Wojciech Zurek's approach to decoherence in quantum mechanics (quantum darwinism).   Cleanly written.  
• Along these lines, this paper is a survey/guide to issues in quantum foundations and interpretations of quantum mechanics.
• Lastly, Jim Freericks has a new quantum mechanics textbook out (for free!), with the challenging idea of making the subject accessible without calculus or differential equations.  (I'm jealous.  My textbook's UK publisher would not let me use Steve Martin's quote for a chapter epigraph, but Prof. Freericks was able to do it - well played.)

And more news/policy-related items:

• The presidential science advisor and head of OSTP, Michael Kratsios, appeared before the House science committee this week, timed to be coincident with the release of OSTP's new report, "Science: A New Golden Age".  A lot has already been written by many people about this report, which contains a number of actual proposals, some good and others of varying degrees of vagueness/underwear gnomes-level magical thinking.  Two pretty good (in my view) takes on this are this article in ars technica and this policy piece by Cole Donovan (former OSTPer).  It's important to remember:  This is a policy document, not something that has automatic impact, no matter how the Wall Street Journal frames its reporting on this.  (Hint:  This document alone does not somehow grant the president the authority or ability to redirect $200B in research funding.  Maybe their reporting on this would be better if they hadn't laid off all their science reporters.)  It's important to pay attention to what is said here, without giving it more oxygen than it deserves.  It's also unclear whether anything OSTP is saying and doing is aligned with what OMB is doing.  Declaring a new golden age of science while simultaneously proposing large cuts in all the science agencies is not exactly a sign of coherence.  Derek Lowe at Science has it right, essentially.  Nature reports that the mid-year budget clawbacks from NSF are apparently going toward some OSTP grand challenge initiative, something about which Kratsios denied all knowledge when talking to the House committee.  
• Holden Thorpe also raises a key point, that universities need to get their collective act together, have a plan about the future of research, and act on it, rather than scrambling for remaining scraps while trying hard not to be seen.  The AAU is important, but hoping that the AAU will accomplish difficult tasks without individual institutions having to take a public stand is unlikely to be successful as strategy.  Organizations like SUFS, UCS, and FAS are pushing the agenda; universities need to decide how they want to play this.
• The first round of DOE Genesis Mission awards were announced this week in DC as well.  
• SpaceX had a pretty successful test flight of their huge rocket, culminating with unexpectedly soft-landing the second stage ("Starship") in the Indian Ocean.  If they really can get this working at the level of reliability and reusability they've done with the Falcon 9, it truly would be game-changing for large-scale payload to orbit.  (Data centers in space still make no sense btw.)
• This week was also a big one in the world of mathematics, with an AI tool (Claude Fable) being used to find a counterexample to the previously outstanding Jacobian Conjecture.  Here is a write-up by Fields medalist Terence Tao, and here is a discussion among other mathematicians.  That wasn't alone.  Here (link to x) is a counterexample being found to a conjecture in graph theory, and it approaches "proof by intimidation" - the human basically harasses and bullies the AI tool into the solution without contributing any intellectual argument.  It seems like it's only a matter of time before some major theoretical physics result gets generated by these tools, though it's important to note that many physics problems are NP-hard/just not integrable.  AI tools are impressive, especially since they're trained on the entire corpus of technical literature, but they are not miraculous:  Claude can't somehow factor large numbers efficiently, or exactly solve the many-electron interacting Hamiltonian for the Hubbard model, because those are truly difficult problems.  Update:  Here are Terence Tao’s slides about AI and the future of mathematics.  As usual, these are excellent.

A brief serious note about mental health and well-being

I've been blogging for 21 years now (!!), and over that time I've had a wide variety of comments on here, but there have been a couple of anonymous ones in the last few weeks that really worried me.  It's the internet, so you can't readily tell when someone is trolling, but these made me concerned for the safety and emotional state of the commenter.   Just remember, there is always someone to talk to who is ready to listen, and we're all better with you than without you.  The 988 hotline (https://988lifeline.org/) is available 24/7/365, free and confidential.  Please take care.

A few optics/metamaterials highlights from META 2026

This past week I attended META 2026, the 16th International Conference on Metamaterials, Photonic Crystals and Plasmonics, at Trinity College, Dublin.  This was the first time I've ever gone to this conference, which has grown from somewhat blurry beginnings to a ~ 900+ person annual event.  Here are a few scientific highlights:

• Metasurfaces, built up from spatial arrays of dielectric (or sometimes semiconductor or plasmonic) resonators called "meta-atoms", have matured into very impressive, versatile tools.  In her plenary talk, Ruwen Peng from Nanjing showcased different approaches, combining angularly rotated meta-atoms ("Pencharatnam-Berry") and size-modulated meta-atoms.  The result can produce polarization-entangled photon beams, entangle photon spin and orbital angular momentum for quantum key distribution, and do full entanglement distribution over many channels.  Similarly, Federico Capasso gave a very impressive talk about the progress in the field, from visible wavelength flat optics ten years ago to compact platforms for sophisticated quantum tomography.
• Nikolay Zheludev gave a great overview about combining measurements + machine learning estimators (e.g., here) to achieve effective optical resolution far better than conventional limits.  This can be used to make optics-base estimates of nanowire lateral displacements down to the 100 pm level, for example.  Rather than looking at the flow of energy in an optical imaging system, one can look at the flow of Fisher information regarding the object being imaged.
• There were a series of talks throughout the meeting about chirality of optical scattering, what this means, and what it can lead to (including enantiomer-selective imaging and chemistry).  Note that it's important to distinguish between intrinsic chirality (e.g., the object scattering the light has a real structural handedness), extrinsic chirality (the object scattering the light is not chiral, but the experimental arrangement to do and measure the scattering introduces chirality into the measurement), and chirality in the fields themselves (think swirling Poynting vectors locally) that don't necessarily extend to the far field.  There are some neat probes of local effects, like this use of local polymerization.
• Roman Quidant gave a talk about metalenses that are also optomechanical structures (e.g., use a pump beam to excite mechanical deformation of the metalens to steer the focus of a probe beam).  This lets you do some pretty neat things, like control the sign of optical forces by dynamically tuning the relative importance of momentum transfer (pushing objects with light by direct momentum kick from photons) and polarization forces (the classical optical tweezer situation where polarizable objects "seek" regions of high intensity).  This can enable feedback control to do optical cooling of trapped, levitated particles, potentially down to the quantum level.
• Alessandra Boltasseva presented a variety of recent advances, including a look at how plasmonic ceramics like TiN and HfN have properties that can be dramatically tuned as their thickness gets down to the few-unit-cell level, a regime she and collaborators term "transdimensional" (to distinguish from atomically thin 2D van der Waals materials).  The possibility of Wigner crystallization in such systems is exciting, though disorder is a likely complication.  

• 

  A 4-channel wavelength division multiplexer
  made from etched Si3N4, from this paper.

  Jeremy Baumberg talked about building metamaterials out of molecularly-spaced nanoparticles, and how this has opened up real opportunities for chemical sensing based on surface-enhanced Raman and infrared absorption, as in this example.  Neat stuff.
• There were multiple talks about metasurfaces for nonlinear optics, including one by Igal Brener on cool ways to use GaAs metasurfaces to produce entangled photon pairs via bound states in the continuum.  
• Likewise, there were a number of presentations about inverse design, where computational tools are used to produce very funky looking structures which can act as, e.g., multichannel routers of optical signals.  Jelena Vuckovic presented an overview of this, showing how it can be done at scale to produce a chip that acts as a 1 TB/s optical router.  Structures produced this way always seem to me like some kind of eldritch geometry out of HP Lovecraft (see figure), but they work.  
  

As always, apologies to those whose work I didn't mention above; my note-taking was pretty uneven.

(I am trying to strike a balance between talking and educating people about science, which is basically the point of this blog, and keeping people informed/voicing some of my personal opinions about the crisis in the US research ecosystem (arguably the most consequential challenge facing US researchers today, with long-term implications that will be felt for many years).  There is still very exciting work being done in nanoscience, the physics of materials, etc. - we are just facing a future where if current trends continue the major advances may increasingly happen outside the US.)