Materials characterization techniques – a brief glossary

Suppose someone has synthesized or found what they think is a new material. How do people studying materials (condensed matter physicists, materials scientists, materials chemists) figure out what they have and understand its properties? That's the puzzle-solving aspect of working with materials: In general, solid matter involves an enormous number of interacting particles, and determining even something as basic as its structure and underlying excitations is not simple.

There are many, many materials characterization techniques available, each with its own peculiarities and limitations. (I think that the alphabet-soup collection of acronyms associated with these is part of condensed matter's general perception as complicated, obscure, and full of jargon, but the need for a variety of techniques is clear in practice.) For the class I'm teaching, I wrote up a brief glossary of these. Apologies for undoubtedly leaving out someone's favorite. Please let me know in the comments what I've missed or mis-stated. Wikipedia already does a creditable job explaining many of these, including with diagrams and citations to key literature. Hopefully sticking a lot of these in one place will be useful to some. -- DN

PS - the fact that there are so many different techniques that can be applied just to determine material structure and composition is a hint why trying to automate materials characterization in AI/ML-based materials synthesis and discovery has a long way to go.

Materials characterization techniques – a brief glossary

 

Microscopy

Optical microscopy:  provides optical information about structure on scales > ∼ 1 μm

 

Electron microscopy and related

Scanning electron microscopy (SEM):  electron beam (1-40 keV) rastered across sample; secondary electrons knocked out of the sample are detected as a function of beam position to create an image.  Sensitive to surface conditions, works best on conductive materials, larger signals from high Z materials.  Beam spot size typically nm scale; lateral resolution down to 1-2 nm possible.  Penetration depth into solid of 10s of nm, more with higher electron beam energy.  Typically requires sample in vacuum (or at least detector closer to sample than electron mean free path in background gas).  Best with conductive samples to avoid charging.

Related

Back-scatter electron diffraction (BSED):  back-scattered electrons from the beam used to create diffraction patterns from the surface crystal structure.

Energy (X-ray) dispersive spectroscopy (EDS):  x-ray fluorescence excited by electron beam is detected; can be used for elemental compositional analysis.

Electron microprobe analysis (EMPA): carefully calibrated cousin of EDS, allows precise elemental analysis.

Cathodoluminescence (CL): optical photons collected from e-beam excited sample as a function of beam position.  Can detect excitations of material like plasmons, excitons.

 

Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM):  sub-nm spot size electron beam (typically 100 keV and higher) passed through thin (∼ 100 nm thick) sample into a detector.  Can detect atomic-scale structural information.  EDS, CL can be performed as well. “Bright field” and “dark field” imaging modes possible.  Sample in vacuum.  Special sample holders available to allow measurements as a fn of temperature, strain, electronic biasing,

Related

Selective-area electron diffraction (SAED) – get electron diffraction from portions of the sample.

Electron energy loss spectroscopy (EELS) – measure energy loss of transmitted electrons, can infer excitations (e.g. plasmons) within the material.  Energy resolution down to sub-100 meV possible.

Lorentz electron microscopy (LEM) – can infer magnetic domain patterns from deflection of transmitted electron beam

 

Electron diffraction:

Reflection high energy electron diffraction (RHEED):  diffraction using grazing incidence electrons (10-30 keV).  Extremely sensitive to surface conditions, used for in situ characterization of thin film growth in molecular beam epitaxy (MBE) and pulsed laser deposition (PLD) systems.  Requires vacuum.

 

Low energy electron diffraction (LEED): low energy (20-300 eV) electrons diffracted in reflection off surfaces.  This is the original electron diffraction discovered by Davisson and Germer back in 1924.  Requires vacuum, very surface sensitive (nm scales), vulnerable to magnetic fields. 

Related

Auger electron spectroscopy (AES):   use keV electrons to knock out core electrons; as electron drops down to fill core hole, excess energy kicks out less bound electron, whose energy is measured.  Very surface sensitive. 

Low energy electron microscopy (LEEM) and spin-polarized LEEM (SPLEEM):  Doing electron microscopy using < 100 V electrons; extremely surface sensitive, SPLEEM good for local magnetic structure.

 

Scanned probe microscopy (SPM)

Category of microscopy methods that involves moving a sharp tip in close proximity to a material surface.  Typically involves piezoelectric transducers for sample/tip relative motion and scanning.  Examples:

Atomic force microscopy (AFM):  A sharp tip (down to a few nm in radius) at the end of a cantilever or tuning fork structure is moved relative to the sample surface.  In contact mode, changes in surface topography cause deflection of the cantilever, which is typically detected optically.  In non-contact (tapping) mode, the tip is oscillated at the cantilever resonance frequency.  The short-range interaction between tip and sample alters the frequency and phase of the cantilever motion.  Feedback of tip height above sample is used to maintain tip-sample separation and map topography.  Can be performed in ambient conditions.  If performed in vacuum, with molecule-functionalized tips, it is possible to perform atomic-resolution imaging and “see” molecular orbitals.  Versions of AFM may be performed in fluid environments as well.

Related

Lateral force microscopy (LFM):  looks at sideways forces on tip as it is scanned over the sample surface; sensitive to changes in local friction and elastic properties.

Piezoresponse force microscopy (PFM): uses a conductive tip and an applied ac current to map piezoelectric response of sample.

Conducting probe AFM:  In contact mode, allows mapping of electronic properties of the sample, though care is required for interpretation.

Scanning capacitance microscopy (SCM): Using conductive tip as effective capacitor plate, maps capacitance of sample.  Useful for mapping carrier concentration in semiconductor materials.

Magnetic force microscopy (MFM):  Uses a ferromagnetically coated tip.  Scanning a line in close non-contact mode to get topography, and rescanning back over the line with tip elevated a fixed amount so that long-range magnetic forces are mapped.  One challenge:  magnetic field from tip can perturb magnetic domains in sample. 

Electrostatic force microscopy (EFM): Conductive AFM tip is used and held at a particular potential relative to the sample.  As in MFM, mapping at a fixed tip-sample distance can reveal local electric field forces between tip and sample.

Kelvin probe force microscopy (KPFM): Feedback is performed, so that the conductive AFM tip potential is adjusted to null out any long-range electric field forces between tip and sample.  This can be used to map out the local contact potential or work function difference between tip and sample.   

Magnetic resonance force microscopy (MRFM): Uses radio frequency (RF) excitation and a magnetic tip to drive magnetic resonance (either electron spin resonance or nuclear magnetic resonance) of spins in the sample, detected via the cantilever motion. 

 

Near-field scanning optical microscopy (NSOM or SNOM): Using AFM-like control, a tip is brought into close proximity (nm to tens of nm) of the sample surface.  Near-field optical interactions are then mapped as a function of tip position.  Tip can be a tapered optical fiber or a contain a hole/waveguide, so that light travels through the tip to the sample surface.  Scattered light can be detected back through the tip or in the far field.  Alternately, light can be shined in via the far field and scattered into the tip or into another far-field detector.  Key idea is that the very small tip and tip-sample distance can scatter sub-diffraction-limit information into the far field.

Scanning single-electron transistor microscopy (SSETM): A tip is prepared (e.g., on a drawn optical fiber) with a single-electron transistor (SET, a device based on “Coulomb blockade”, consisting of a metal “island” with tunnel junctions to a source and a drain electrode, sometimes with an additional “gate” electrode that is capacitively coupled to the island) at the tip apex.  The tip is positioned close to the sample using AFM-like techniques to avoid crashing into the surface.  The electronic transport through the SET as a function of biasing conditions and the tip position.  The surface potential of the sample acts as a “gate” that modulates conduction through the island in the Coulomb blockade regime.  By modulating the tip position and biasing conditions, can be used to measure local charge density and electronic compressibility.  Typical spatial resolution 10s of nm at best, because of diameter of island and positioning precision.  Requires cryogenic temperatures to operate.

Scanning SQUID microscopy: A superconducting quantum interference device (SQUID) is fabricated on a tip (e.g., on a drawn optical fiber).  The tip is again positioned near the sample using AFM-like techniques.  The SQUID, consisting of a superconducting loop with Josephson junction weak links, is used to detect magnetic flux from the sample.  This can be used to map current distributions in operating devices.  Requires cryogenic temperatures to operated, does not work well with magnetic fields.

Scanning Hall probe microscopy: A 2D electronic system is patterned into a Hall configuration on some kind of tip and positioned (using AFM-like methods) close to a sample of interest, to act as a magnetic field detector. 

Scanning NV center microscopy:  A nitrogen-vacancy center in a diamond crystal has optical transitions that are highly sensitive to local magnetic fields.  Incorporating NV centers into diamond films on SPM tips enables high resolution (tens of nm) measurements of local fields including direction, and the inference of current distributions.

Microwave Impedance Microscopy (MIM): A microwave resonator is made and incorporated so that a conductive AFM-like tip is part of the resonant circuit.  Scanning the tip over a device changes the Q of the resonator, allowing mapping (with 10s of nm resolution) of the microwave frequency (say hundreds of MHz to GHz) dielectric properties of the sample. 

Scanning thermal microscopy (SThM): Scanning a special temperature-sensitive probe tip over a sample to assess local thermal conduction properties or local temperature.  Several variants depending on the type of thermally sensitive probe used (e.g. thermocouple, phase change material, optical defect center with T-dependent lifetime).

 

Scanning tunneling microscopy (STM):  Tunneling current between metallic tip (sometimes Pt, W) and conductive sample used for z-positioning feedback.  Because of the exponential distance dependence of tunneling, atomic resolution is possible.  Can be performed at ambient conditions, but by far the best results are obtained in vacuum and at low temperatures. 

Related

Scanning tunneling spectroscopy (STS):  At each tip position over the sample, z feedback is turned off and tunneling I-V curves are obtained at a nominally fixed tip height (usually including dI/dV vs. V and sometimes d2I/dV2 vs. V).   The d2I/dV2 vs. V data is used to perform inelastic electron tunneling spectroscopy (IETS), and can detect local excitations like vibrations.

Quasiparticle interference (QI):  From STS maps, spatial Fourier transforms of the (fixed energy) maps of conductance vs. position are performed.  For itinerant quasiparticles that can move around on the sample surface, quantum interference between trajectories that bounce off scattering sites and the tip mean that the QI transforms make it possible to infer E(k) for the surface states of the sample. 

Spin-polarized STM (SPSTM): Requires a magnetic/spin-polarized tip.  Can reveal local magnetic information due to spin-dependent tunneling between tip and sample.

 

X-ray methods

X-ray diffraction (XRD):  gives crystal structure (spatial frequencies of atomic stacking) of materials via coherent scattering of x-rays.  Powder XRD = gives bright rings as a function of angle away from forward scattering (linear combination of many spots).  Obeys Bragg condition.  Single-crystal XRD = gives discrete spots.  A Laue single-crystal diffractometer can be used to find the crystal orientation of single crystals.

X-ray reflectometry (XRR):  rather like optical ellipsometry; looking at x-ray reflections at grazing incidence with respect to a multilayered surface.  Can be used to infer layer thicknesses (assuming there is x-ray contrast between different layers)

X-ray absorption spectroscopy (XAS) and x-ray absorption fine structure (XAFS):  Using tunable x-ray sources (e.g. beam from a synchrotron), it is possible to measure x-ray absorption in detail, allowing determination of chemical structure and valence in materials.  Also related: x-ray absorption near edge structure (XANES), gives more detailed chemical information.

Inelastic x-ray scattering (IXS): Angle- and energy-resolved x-ray scattering, allowing measurement of absorption edges and detection of excitations launched in the material at some known energy and momentum transfer.

Resonant inelastic x-ray scattering (RIXS):  Angle- and energy-resolved x-ray scattering where the incident wavelength is chosen to be close to an x-ray line of an element in the target.  Needs tunable x-ray source (free electron laser (FEL), e.g.)  Since it is sensitive to electron density, it can be used with small sample volumes, and can be used to look for dispersive excitations in the material.  There is hope that RIXS can be used to detect magnetic excitations as an alternative to neutron scattering for small amounts of sample material. 

X-ray magnetic circular dichroism (XMCD): Difference of XAS between left- and right-circularly polarized x-ray beams.  Can be used to infer magnetic moments of atoms in the sample.  Can be resonantly enhanced if x-rays are chosen to be at transitions of the core electrons of the magnetic atoms in the material.  Typically needs a synchrotron to get high brightness beams.

Related →

X-ray magnetic linear dichroism (XMLD): Difference of XAS between x- and y-polarized x-ray beams.  Closely related to XMCD, useful for looking at charge order and orbital order in magnetic materials.

 

Photoemission

X-ray photoemission spectroscopy (XPS) and ultraviolet photoemission spectroscopy (UPS):  Uses x-ray or UV light to eject electrons from sample and analyzes the energy of the ejected electrons.  This gives the energies of the core levels of the constituents relative to the vacuum, which encodes the valence state of the elements.  Sample in vacuum.  Surface-sensitive, very useful for determining chemical composition.  Can be combined with etching to do depth profiling of composition. 

Related →

Inverse photoemission spectroscopy (IPES): Low energy (< 20 eV) electrons interact with low-lying unoccupied electronic states, sometimes generating emitted photons.  Probes states above the Fermi level of materials. 

Photoemission electron microscopy (PEEM):  With a scannable optical source, it is possible to map spatial nonuniformity in photoemitted electrons.

 

Angle-resolved photoemission spectroscopy (ARPES):  Uses incident x-rays or UV at precisely known energy and momenta to eject electrons from sample; hemispherical analyzer is used to measure energy and momenta of ejected electrons with high precision (energy resolution can be as sharp as 1 meV in synchrotron facilities).  Sample in ultrahigh vacuum, typically requires surfaces cleaved in vacuo. This is the primary technique for measuring electronic band structure.  Like all photoemission techniques, it works best on conductive samples to avoid charging problems.  Variations include spin-polarized ARPES (polarization of detected electrons is found) and time-resolved ARPES (optical pump followed by time-delayed x-ray/UV pulse to do the photoemission).  There is also a related technique in terms of hardware called momentum-resolved EELS, where incident electrons of known energy and momentum are bounced off the material of interest and their final energy and momenta are measured.

 

Neutrons

Neutron diffraction:  Neutron scattering, requires beam of monoenergetic neutrons (prepared from a reactor via moderation + diffraction off a known crystal to act as a monochromator) (or broad-band neutrons but with time-of-flight to assess neutron energy).  Sensitive to lattice structure (nuclei).  Magnetic dipole interactions with electrons allows neutron diffraction to be sensitive to magnetic order.  Variations:  cold neutrons (prepared by scattering off cryogenic material) for higher sensitivity to magnetic systems; polarized neutrons, with polarized detection for higher sensitivity to magnetic systems.  Because neutron scattering cross-sections are generally small, neutron scattering historically requires large quantities (many milligrams) of material, and single-crystal diffraction is typical (with magnetic structure measurements requiring careful alignment of sample material via XRD first).  High brightness sources are improving the situation. Another challenge:  some elements and isotopes have large absorption cross-sections for neutrons and thus cannot readily be measured via neutron scattering. A positive flipside of this is that neutron scattering is very sensitive to hydrogen and lithium, of interest in batteries and other energy-related applications.

Related

Inelastic neutron scattering (INS):  Momentum- and energy-resolved neutron scattering, with change in neutron energy and momentum recorded.  Similar in spirit to ARPES, for mapping out dispersion relations of excitations within the sample material.  This is the primary method of tracing out phonon dispersions in solids, as well as the means of identifying and quantifying magnons.  Spin-polarized INS is possible, though any neutron scattering technique that requires preparation or detection of neutrons in particular spin states is more demanding (takes longer, requires higher initial flux) because of loss of neutrons during preparation and detection. 

Neutron reflectometry:  Diffraction of reflected neutrons, rather analogous to EBSD, though also sensitive to magnetic scattering.

Small-angle neutron scattering (SANS):  Analogous to SAXS, but with grazing-incidence neutrons.  Strongly sensitive to light elements (because they have bigger neutron scattering cross-sections) and magnetic structure.

 

Optical spectroscopy

Note that many optical techniques can be combined with microscopy to achieve spatial resolution and mapping of responses over sample surfaces.  A good review article on some of these is this.

UV/Vis/IR absorption:  A sample is illuminated in a transmission geometry with broadband light, and by measuring the transmitted spectrum, electronic transitions can be identified and band structure can be constrained.  Selection rules constrain what transitions can be seen.

Fourier transform infrared (FTIR) spectroscopy and microscopy:  Using a broadband mid- to far-IR light source and incorporating the sample into one arm of an interferometer, it is possible to measure absorption out to longer wavelengths (10 μm, e.g.).  Good for identifying “infrared active” (e.g. involving polar displacements) low energy vibrational modes in solids.

Ellipsometry and spectroscopic ellipsometry: Incident light of known wavelength, measuring reflected light from a surface as a function of angle of incidence (and wavelength of incident light, in the spectroscopic case). Allows determination of dielectric function/index of refraction, interpretation through modeling.  Great for quantifying layer thicknesses for dielectric multilayers.

THz spectroscopy:  Using THz sources and detection, can look at transmission and reflection in the mm-wave (very far IR; not quite the microwave).  Great for identifying vibrational modes, low-energy excitations as in superconductivity and some magnetic states. CW sources now exist for THz using quantum cascade lasers. Time-resolved THz (THz time-domain spectroscopy) is often used, as broadband THz pulses can be created using pulsed lasers and photoconductive antennas. 

Optical conductivity:  By measuring real and imaginary parts of the dielectric function (through light scattering, ellipsometry, absorption measurements) and using the Kramers-Kronig relations, it is possible to infer the frequency-dependent conductivity σ(ω), which can reveal a lot about dynamics of charged excitations.

Faraday rotation:  In transmission, the polarization of light can be rotated due to magnetization of the sample.  Provides information about magnetic structure of materials.

Magneto-optic Kerr effect (MOKE):  In reflection, the polarization of light can be rotated due to magnetization of the sample. 

Raman spectroscopy:  This is inelastic light scattering, often applied to molecules or optical phonons in solids.  An incoming photon of angular frequency ω0.  Elastic scattering is called Rayleigh scattering.  If the photon excites a vibration or another excitation of energy ℏω, the (“Stokes”) scattered photon comes out with frequency ω0 – ω.  If the system is already excited, the (“anti-Stokes”) scattered photon can grab energy from the excitation and come out with frequency ω0 + ω. Raman scattering can take place if the polarizability tensor of the system α depends on the displacements of the atoms.  In Raman spectroscopy of solid crystalline materials, with polarization control of the incoming light and known incident angle vs. the crystallographic orientation, it is possible to gain insight into dispersion of excitations.  Detection is usually done with a grating spectrometer + CCD or CMOS camera.  Variation: magnetoRaman, where sample is in an applied magnetic field.

Brillouin light scattering: Inelastic light scattering at quite low energy transfers, better suited for looking at acoustic phonons, magnons, etc. in solids.  Energy transfers are sufficiently small that detection is usually done with an interferometer.

Photoluminescence (PL): Optical spectroscopy in which incident light electronically excites the sample, and the sample then emits photons of energies characteristic of the electronic excitations. This is a standard way to characterize excitons and related excitations in semiconductors. Variations include time-resolved PL (to look at dynamics of excitations and their lifetimes) using pulsed excitation and timed detection; and two-photon PL (TPPL), in which high intensity lower energy excitation is used to nonlinearly excite the sample. (Nonlinear optical processes depend critically on symmetries of the underlying material.) When applied to molecular systems (or semiconductor nanocrystals) in the context of chemistry, PL is often referred to as fluorescence spectroscopy.

 

Electronic transport

I-V characterization: Measuring the current as a function of voltage (or voltage as a function of current).  Depending on the material involved, considerable information may be inferred from such data.

Magnetoresistance/magnetoconductance:  Measuring electrical resistance or conductance as a function of applied magnetic field and temperature.  Conductance measurements = source a voltage, measure a current.  Resistance measurements = source a current, measure a voltage.  Best practice, if possible, is to perform a 4-terminal (or more) measurement, with current sourced via two leads and voltages measured with other leads.  Since an ideal voltage probe draws no current, contact resistances do not interfere with the voltage measurement. 

Differential conductance/differential resistance:  For differential conductance (dI/dV), the applied bias includes a small ac voltage in addition to an applied dc voltage Vdc, and an ac measurement (via a lock-in amplifier) allows the detection of the ac contribution to the current; this allows measurement of dI/dV as a function of Vdc.  Similarly, for differential resistance (dV/dI), the applied bias includes a small ac current in addition to an applied dc current Idc, and an ac measurement via lock-in allows detection of the ac contribution to the voltage; this allows measurement of dV/dI as a function of Idc.  Note that differential resistance measurements are appropriate for examining candidate superconductors, when it is possible that the sample may support nonzero current with zero voltage.

Hall effect:  By measuring longitudinal and transverse resistance (Rxx ≡ Vxx/Ix, Rxy ≡ Vxy/Ix) in the presence of a perpendicular magnetic field Bz, it is possible to infer the sign of the charge carriers, charge mobility, and carrier density (assuming an isotropic single-band conductor). 

Tunneling spectroscopy:  In a tunnel junction (between a conducting sample and a normal metal probe electrode), at zero temperature the differential tunneling conductance dI/dV is proportional to the electronic density of states of the probe at its Fermi energy and the density of states of the sample at E = EF,sample-eVdc, where Vdc is the bias voltage of the probe relative to the sample.  (For a superconducting probe, the probe density of states is very sharp but is also shifted relative to the normal state EF because of the superconducting energy gap.)

Related

Inelastic electron tunneling spectroscopy (IETS): Conventionally, in tunneling spectroscopy, when the bias energy scale eVdc crosses the energy ℏω required to inelastically excite an excitation of the sample, this adds a possible path for electron transport.  The result is a kink in I-V, equivalently a step in dI/dV vs. Vdc, and therefore a peak in d2I/dV2 (at positive Vdc) at Vdc=ℏω/e. A real excitation of the sample should result in antisymmetric d2I/dV2 features at Vdc=± ℏω/e.  This approach has been used to identify vibrations in molecules, optical phonons in solids, and also magnetic excitations in solids.  The IETS features are broadened by the finite electronic temperature (kBT), so cryogenic temperatures are best suited for this technique.

 

Thermodynamic and thermal measurements

Specific heat:  Adding a small amount of thermal energy to a sample via a heater and measuring the temperature rise of the sample using a local thermometer.  Because of the relationship between specific heat and entropy (Cp = (1/T)(∂S/∂T)|p), the specific heat as a function of temperature may be used to infer entropy.  First-order phase transitions show up as a huge feature in specific heat vs temperature, since the entropy is discontinuous across a first-order transition.  Second-order phase transitions show up as a singular feature (discontinuity) in heat capacity vs temperature because (∂S/∂T) is discontinuous across such a transition, and will show critical fluctuations approaching the transition temperature.  Specific heat of metals is linear in T at low temperatures and is used to infer the electronic density of states at the Fermi level.

Related

Differential scanning calorimetry (DSC): Temperature is measured as heat input to the sample is scanned.  Intended to reveal phase changes within the material.

Thermal conductivity: A known thermal energy current is applied through a sample, and the temperature drop across the sample is measured using local thermometers.  This is a measure of the transport of energy by all mobile excitations in the material.  In conductors, charge carriers are expected to transport an amount of energy proportional to their specific heat, leading in metals to the Wiedemann-Franz relation.

Thermal expansion: Changes in sample dimensions as a function of temperature are measured, giving insights into material structure and bonding.  Typically, thermal expansion relates to the anharmonicity of the interatomic potential, and it is related therefore to nonlinearities in the properties of phonons (see the Grüneisen parameter).

Thermopower/Seebeck coefficient:  Absolute Seebeck response = the change in voltage across a sample is measured as a function of the temperature difference imposed across the sample.  Electronic excitations (and phonons) tend to diffuse away from the hot side.  Seebeck response sign generally depends on sign of the charge carriers (electron-like or hole-like).  The Seebeck response in a conductor is proportional to the energy dependence of the conductivity (and hence the mean free path) of the carriers.

Nernst-Ettingshausen effect:  In a Hall-like geometry, the transverse voltage across a sample Vxy is propertional to the temperature gradient along the sample dT/dx and the mutually perpendicular magnetic field Bz, so that the Nernst coefficient is defined as ν = (Exy/Bz)/(dT/dx).  This gives information about the transverse scattering of heat-carrying excitations in the presence of a magnetic field.

 

Magnetic measurements

Magnetization: Measurements of M vs H may be performed using SQUID-based and other magnetometers, though knowledge of sample dimensions and geometry are required.  Characteristic features of M are expected for certain material types.  For example, near zero field, a superconductor is expected to show perfect diamagnetism.  Often measurements are also made of M vs T at fixed H, comparing field-cooled and zero-field-cooled responses.  Saturation of M vs H at low temperatures and high fields can reveal the magnetic state of elements hosting local magnetic moments.

Vibrating sample magnetometry (VSM): a particular type of magnetometer that vibrates the sample back and forth through pickup coils.

AC susceptibility:  An oscillating component of H is applied and the change in M is measured.

Nuclear magnetic resonance (NMR):  liquid (for molecules) or solid-state.  Applied magnetic field provides Zeeman energy splitting for spin states of nuclei, radio frequency pulse sequences (and continuous wave methods) used to determine nuclear spin properties (and because of hyperfine couplings, provides information about electronic states).  Specific effects in superconductors (Knight shift).  Care must be taken with conducting samples, as microwaves don’t necessarily penetrate into the bulk of the material.

Electron paramagnetic resonance (EPR) or electron spin resonance (ESR):  Applied magnetic field provides Zeeman energy splitting for spin states of electrons, microwave pulse sequences (and continuous wave methods) are applied to do spectroscopy of these.  Best in insulating materials with unpaired electrons.  Particularly handy in determining the g factors for local magnetic moments, which is affected by crystal fields (local chemical bonding environment) at the local spin-carrying atoms. 

Ferromagnetic resonance (FMR): Conventionally, a radio frequency/microwave drive is applied to make the ferromagnetic magnetization M of a material precess around an external magnetic field.  Gives information about the magnetization dynamics and damping.  Recently, FMR in small devices has been driven via spin currents (from the spin Hall effect/spin-orbit torques or  spin transfer torques).

Mossbauer spectroscopy: This is really a nuclear physics-based technique, but given that the most famous Mössbauer material is iron, it has relevance for magnetism.  Gamma-ray spectroscopy using the Mössbauer effect (collective recoil or lack thereof of the entire lattice rather than individual atoms), gives extremely precise energetic information about nuclear environment of the particular isotopes, including hyperfine interactions.

Muon spin spectroscopy (μSR): Muons produced via an accelerator are implanted or transmitted through a material of interest. Decay of positive muons leads to emission of positrons, with directional asymmetry of emission related to the spin state of the muon. These measurements this give information about the magnetic environment within the material. Does not require pulsed fields.

 

Other techniques to assess composition

Secondary ion mass spectrometry (SIMS): Material is sputtered away from the sample, and the fragments are analyzed using mass spectrometry (e.g., ionized fragments are accelerated and curved in a magnetic field for detection, to determine their charge to mass ratio).

Inductively coupled plasma mass spectrometry (ICP-MS): Using an inductively coupled plasma source to ionize sample material for MS.

Atomic emission spectroscopy (AES): Material is heated or otherwise excited, and the emission spectra of the products is measured.  Modern version of old approach of looking at the color of flame produced by a bit of material.

Rutherford backscattering spectrometry (RBS): Ions (protons, alpha particles) are fired at the sample material and back-scattered ions are detected; can give depth-dependent compositional information.

Thermogravitic analysis (TGA): Destructive technique.  The sample is placed in a sensitive balance and heated through its decomposition, and the sample is weighed as the temperature is swept.  Different breakdown products will be produced at different temperatures.  Often combined with mass spectrometry to determine the molecular weight of the evolved products.

Other surface characterization methods

Helium atom scattering (HAS):  Diffraction of helium atoms off surfaces.  Extremely surface sensitive.

Field ion microscopy (FIM): A sharp tip is biased up to a high voltage.  Gas molecules impinge on the tip, ionize due to the strong electric field, and are repelled away to a detection screen.  Amazingly, this can give atomically precise information about the configuration of atoms at the tip.

Dye-sensitized solar cells - an idea whose time has finally come?

Dyes are generally small molecules that have electronic transitions with energies corresponding to the visible spectrum of light (around 1-3 eV).  Around 35 years ago, the idea was put forward, particularly by Michael Grätzel and Brian O'Regan, to couple dye molecules to semiconductors and electrolytes, so that when the dye molecules are excited by light, the electrons/holes can be captured and used for photovoltaic power.  This is the concept behind dye-sensitized solar cells, as demonstrated early on here.  I wrote a little about this a long while ago. 

Energy diagram of a dye-sensitized photovoltaic
cell, from this paper. 

This is a compelling idea, and a main selling point is the hope that devices based on this could be cheap and much less energy-intensive in their manufacturing, since they could be made with materials that don't require high temperature synthesis or high purity, like Si solar cells.  After many years of effort, end-to-end power conversion efficiencies are up around 13% for outdoor solar illumination-type conditions.  Here (link to NIH free version) is a good review from 2021 that is very complete in summarizing progress.

So, 13% is nice, but it's hard to see that being competitive with Si for bulk photovoltaics, and perovskites, also solution-processable, are up over 25%, similar to Si.  Still, outdoor solar is not the only application!  This paper from 2017 showed that it is possible for dye-sensitized cells to get power conversion efficiencies up to around 30% for indoor lighting conditions (much lower intensity, different spectra than solar illumination).  That seems to be the basis for this story in today's Wall Street Journal, pointing out that there are actual consumer products coming to market that have dye-sensitized cells for indoor operations.  Very cool to see this product really start to make it out of the lab!  If one of my readers has a good, clear explanation of why the power conversion efficiency is so much better for indoor lighting conditions, please leave it in the comments.  

Items of interest

For the first post of the new calendar year, here are a few items that I thought were interesting:

• Here is a feature article in Science that talks about the experimental quest for detecting Majorana fermions in solid state systems, bookended by the story of Majorana's disappearance. 

• 

  Adapted from PRX 12, 045501 (2022)

  This brief column is a good starting point with references if you want to learn about altermagnetism.  For a lengthier, more technical discussion, see this PRX paper.  Quickly:  in local-moment ferromagnetism, the spins (and therefore magnetic moments) of electrons on lattice sites in a material spontaneously align (at least, in a single domain).  Shifting over one lattice site leads to the same pattern of magnetic moments, so the ferromagnetic ordered state is "invariant under a lattice translation".  In a local moment antiferromagnet, the spins alternate up and down on neighboring sites.  Shifting over one lattice site + a 180 degree rotation gets back the same pattern of magnetic moments, so the antiferromagnetic ordered state is invariant under a one lattice site translation plus 180 degree rotation.  It turns out, there is a third possibility:  in an "altermagnet", neighboring spins alternate up and down, but their local environments are rotated by 90 degrees, so that the ordered state is invariant under a spin flip plus a 90 degree rotation.  This has neat consequences for band structure and could lead to technological applications.
  
• A statement in the press this week caused me to realize that I've never written a nicely accessible post about magnetism and how it works.  Thinking about how to do that brought me back to this classic video with Richard Feynman, explaining why this can be very challenging.  It seems necessary to ask a general reader simply to accept certain postulates - for example, that electrons, which are nominally point particles, have angular momentum called "spin", and that associated with that spin is a magnetic moment, so that electrons act in some sense like little magnetic dipoles.  That really is remarkable, and in trying to find a way to think about this that is more accessible, I found this classic paper (pdf here) by Ohanian.  My conclusion:  I still need to think about this further, particularly the connection between the classical dipolar \(1/r^{3}\) field from a magnetic dipole and the fact that spin for an electron is a quantum mechanical quantity that follows its particular rules.
• N. David Mermin posted a neat little autobiographical essay on the arxiv yesterday.  Fun to read, especially if you are familiar with his writing.

Very brief end of the year round-up

It's hard to believe that it's already the end of 2023.  It's been a busy year for condensed matter; it's unfortunate that two of the biggest stories (problems with high pressure superconductivity papers; the brief excitement about LK99, the not-actually-a-superconductor) were probably the field's highest profile events.  Still, hopefully the latter at least had the effect of bringing to the public a little bit of the excitement and potential of how condensed matter and materials physics affects our lives.  Physics World summarizes some of their picks for big materials-related stories of 2023 here.  Similarly, here are Quanta's choices for biggest physics stories of the year, and these are the choices from the editors of APS's Physics.  

It's been a busy year personally, with lots going on and too much proposal writing, but at least my blog posting was more frequent than in 2022.  It's still surprising to me that I've been writing this since mid-2005, enough to see almost the entire lifecycle of blogging.  Happy New Year to my readers, and if there are any particular topics about which you think I should write, please let me know in the comments.  I'm always looking for CM/materials concepts that I can try to explain on a non-specialist accessible level.  Still looking for the time and appealing perspective to write that popular book....

Anyway, I hope you have a very happy new year, and best wishes for a great 2024.

New paper - plasmons, excitons, and steering energy

We have a new paper out in Nano Letters (arxiv version here), and I wanted to explain a bit about it and why I think it's a really cool result.   

I've written before about the Purcell Effect.  When we study quantum mechanics, we learn that the rates of processes, like the spontaneous emission of light from an atom, are actually malleable.  The rate of a particular process is usually proportional to the number of ways that process can happen - this is quantified in something called Fermi's Golden Rule.  When we are talking about something like emission of light from an atom, the rate is proportional to the number of possible final states of the photon.  We know how to count those states in a given energy range in free space, and Purcell pointed out that by placing that atom in an optical cavity, we alter the density of final states as a function of frequency, \(\rho(\omega)\) from its empty space value, and hence can change the rate of emission.  Pretty wild that placing a system in a cavity can alter the flow of energy in that system away from what it would otherwise be.

I've also written before about what happens we take two resonators and couple them together - we get "hybridization" or "new normal modes".  If you take a mass on a spring (natural frequency \(\omega_0 = \sqrt{k/m}\)) and couple it mechanically to another identical mass on an identical spring, the coupled system will now have two resonances, one above and one below \(\omega_{0}\).  The chemistry analog of this is, bonding two hydrogen atoms (each with 1s orbitals) together leads to two \(\sigma\) orbitals, one bonding and one antibonding.  

In the new paper, we start with a little metal tunnel junction that hosts plasmonic resonances, like the junctions I wrote about here.  We showed in that paper and subsequent work that it is possible to use an applied voltage and current to get some of the electrons, right near where the electrodes almost touch, to become effectively so hot that they glow (emitting light at energies larger than the applied voltage), while the atomic lattice itself remains cold.  The light emission process here is the radiative recombination of hot electrons and holes in the metal, where an electron drops down in energy to fill in a hole and spit out a photon.  The plasmon resonances of the bare metal act like a sort of cavity, shaping the density of photon states \(\rho(\omega)\), as we also showed here.  The plasmons, set by the metal shape and electronic properties, actually affect the rate at which the electrons and holes in that same metal radiatively combine.

Left: A thin flake of WSe2 is placed on a plasmonic
Au junction.  Right: Overbias light emission from the
device at a particular emitted polarization shows a big
peak splitting right around where the exciton resonance
is of the WSe2 (orange curve).  Adapted from the
SI of this paper.

The wrinkle in the new paper is that we couple that metal plasmonic junction with a thin (few nm) layer of 2D semiconductor by placing the semiconductor on top of the metal.  The semiconductor can host excitons, bound electron-hole pairs, and if the semiconductor is excited with enough energy to create them, the excitons can radiatively annihilate, leading to a comparatively narrow resonance at an energy that overlaps the plasmon resonances of the metal junction.  Thanks to hybridization between the plasmons in the metal and the excitons in the semiconductor, the photon density of states now has a split peak structure ("upper and lower plexciton polariton resonances" if you are an expert).  Light emission in this device is still due to recombination of electrons and holes in the metal, but now the recombination dynamics of those electrons "feels" the strong coupling between the excitons and plasmons.  (The polarization of the emitted light is rather complicated because of the polarization properties of the plasmon resonances).  

There are a lot of interesting possibilities on where to go from here, but it's always amazing to me to see how this physics comes together.  In this case, by changing the optical environment of a metal structure, we can alter the fate of energy stored in the electrons of that metal.  Really neat.

AI/ML and condensed matter + materials science

Materials define the way we live.  That may sound like an exaggeration that I like to spout because I'm a condensed matter physicist, but it's demonstrably true.  Remember, past historians have given us terms like "Stone Age", "Bronze Age", and "Iron Age", and the "Information Age" has also been called the "Silicon Age".  (And who could forget plastics.)

Perhaps it's not surprising, then, that some of the biggest, most wealthy companies in the world are turning their attention to materials and the possibility that AI approaches could lead to disruptive changes.  As I mentioned last week, there have been recent papers (back to back in Nature) by the Google Deep Mind group on this topic.  The idea is to use their particular flavor of AI/machine learning to identify potential new compounds/solids that should be thermodynamically stable and synthesizable, and make predictions about their structures and properties.  This is not a new idea, in that the Materials Genome Initiative (started in 2011) has been working in this direction, compiling large amounts of data about solid materials and their properties, and the Materials Project has been pushing on efficient computational methods with the modest goal of computing "the properties of all inorganic materials and provid[ing] the data and associated analysis algorithms for every materials researcher free of charge".

In addition to the Google work, Microsoft has released on the arxiv their effort, MatterGen, which uses a generative AI approach to try to predict new stable materials with desirable properties, such as a target symmetry or chemical composition or mechanical/electronic/magnetic response.  An example from their paper is to try to find new magnetic materials that have industrially useful properties but do not involve rare earths.  

There is a long way to go on any of these projects, but it's easy to see why the approach is enticing.  Imagine saying, I want a material that's as electrically conductive and mechanically strong and workable as aluminum, but transparent in the visible, and having software give you a credible approach likely to succeed (rather than having to rely on a time-traveling Mr. Scott).  

I'd be curious to know readers' opinions of what constitute the biggest obstacles on this path.  Is it the reliability of computational methods at predicting formation energies and structures?  Is it the lack of rapid yet robust experimental screening approaches?  Is it that the way generative AI and related tools work is just not well-suited to finding truly new systems beyond their training sets?

Intriguing papers - exquisite thermal measurements + automated materials discovery/synthesis

It's a busy time, but I wanted to point out a couple of papers from this past week.

First, I want to point to this preprint on the arxiv, where the Weizmann folks do an incredibly technically impressive thing.  I'd written recently about the thermal Hall effect, when a longitudinal heat current (and temperature gradient) in the presence of a magnetic field results in a transverse temperature gradient as well as the usual longitudinal one.  One of the most interesting ways this can happen is if there are edge modes, excitations that propagate around the perimeter of a 2D system and can carry heat (even if they are neutral and don't carry charge).  Unsurprisingly, to measure thermal transport requires putting thermometers at different places on the sample and carefully measuring temperature differences.  Well, these folks have done just exquisitely nice measurements of Johnson-Nyquist noise in particular contacts for thermometry, and they can see the incredibly tiny heat currents carried by rather exotic edge modes in some unusual fractional quantum Hall states.  It's just a technical tour de force.

Second, on a completely unrelated note, there are back to back papers in Nature this week from the Google deep mind folks - their own write-up is here.  The first paper uses their methods to predict a large number of what are expected to be new stable crystal structures.  The second paper talks about how they used an automated/robot-driven lab to try to synthesize a bunch of these in an automated way and characterize the resulting material.  This is certainly thought-provoking.  It is worth noting that detailed characterization (including confirming that you've made what you were trying to make) and optimized synthesis of new materials is very challenging and of concern here.  Update:  there is further discussion of the characterization here (on LinkedIn by the authors) as well, and more on Twitter here and here.

Third, this paper looks extremely interesting.  It’s long been a staple of condensed matter theory to try to capture complex materials with effective low energy models, like suggesting the Hubbard model as a treatment of the essential physics of the cuprate superconductors.  The authors here report that they’ve done a more orbital-based/ab initio version of this, solved these models numerically, and state that they can reproduce details of the phase diagram of four of the cuprates spanning a big range of superconducting transition temperatures.  Seems like this may bode well for gaining insights into these systems.

Noise in a strange metal - pushing techniques into new systems

Over the holiday weekend, we had a paper come out in which we report the results of measuring charge shot noise (see here also) in a strange metal.   Other write-ups of the work (here and especially this nice article in Quanta here) do a good job of explaining what we saw, but I wanted to highlight a couple of specific points that I think deserve emphasis.  

In thermal equilibrium at some temperature \(T\), there are current and voltage fluctuations in a conductor - this is called Johnson-Nyquist noise - and it is unavoidable.  Shot noise in electrical current results from the granularity of charge and, as shown in its original incarnation (pdf is in German), from the statistical variation in the arrival times of electrons.   Shot noise is an "excess" noise that appears in addition to this, only when a conductor is driven out of equilibrium by an applied voltage and carries a net current.

While the idea of shot noise is tunnel junctions and vacuum tubes had been worked out a long time ago (see the above 1918 paper by Schottky), it was in the 1990s when people really turned to the question of what one should see in noise measurements in small metal or semiconductor wires.  Why don't we see shot noise in macroscopic conductors like your house wiring?  Well, shot noise requires some deviation of the electrons from their thermal equilibrium response - otherwise you would just have Johnson-Nyquist noise.  The electrons in a metal or semiconductor are coupled to the vibrations of the atoms (phonons) - the clearest evidence for this is that the decrease in scattering of the electrons by the phonons explains why metals become more conductive as temperature is decreased.  In conductors large compared to the (temperature-dependent) electron-phonon scattering length, the electrons should basically be in good thermal equilibrium with the lattice at temperature \(T\), so all that should be detected is Johnson-Nyquist noise.  To see shot noise in a wire, you'd need the wire to be small compared to that e-ph length, typically on the order of a micron at low temperatures.  In the 1980s and 1990s, it was now possible to make structures on that scale.

Fig. 4 from the paper

The theory of what should be seen was worked out in a couple of different ways, initially assuming that it is safe to describe the conductor as a Fermi gas (ignoring electron-electron interactions).  One approach started from the conduction-as-wave-transmission picture of Landauer (see here and here for two examples).  A complementary approach (see here) calculated noise from the electronic distribution functions and got the same answer for non-interacting electrons, that the current noise should be 1/3 of the classic Schottky result.  That factor of 1/3 is called the Fano factor, \(F\).   If electron-electron interactions are "turned on", allowing the electrons to exchange energy amongst themselves but not lose energy to the lattice, the noise is actually a bit larger, \(F \rightarrow \sqrt{3}/4\).   It turns out that these values were verified in experiments in gold wires (see here and here, though one has to be careful in experimental design to see  \(F \rightarrow \sqrt{3}/4\)).  This confirmation is a great triumph of our understanding of physics at these mesoscopic scales.  (Interestingly, similar results are expected even with a non-degenerate electron gas - see here and here.)

We applied these same experimental approaches to nanowires we made from exquisite films of a strange metal, YbRh2Si2, and we found that the noise is much reduced from the usual result seen in Au wires (which we also confirmed).  We tested whether phonons could be responsible for the noise suppression, applying the same approach as had been done in the '90s (measurements on wires tens of microns long, where e-ph scattering should be important), and found (in addition to further confirming the e-ph energy loss results in Au from the '90s) that energy loss to phonons can't explain what we see in YbRhsSi2.  

Some further points of interest:

• Until recently there really has not been much attempt to push the theoretical analysis of these kinds of measurements beyond the 1990s/early 2000s results.  My colleague Qimiao Si and his group have looked at whether strong Fermi liquid corrections affect the expected noise, and the answer is "no".  Of course, there are all kinds of additional complications that one could imagine.
• This work was only possible because of the existence of high quality thin films of the material, and the ability to fabricate nanostructures from this stuff without introducing so much disorder or chemical change as to ruin the material.  My collaborator Silke Bühler-Paschen and her group have spent years learning how to grow this and related materials, and long-term support for materials growth is critically important.  My student, the lead author on the study, did great work figuring out the fabrication.  It's really not trivial.  
• I think it's worthwhile to consider pushing older techniques into new regimes and applying them to new materials systems.  The heyday of mesoscopics in the 1990s doesn't need to be viewed as a closed, somewhat completed subfield, but rather as a base from which to consider new ways to characterize the rich variety of materials and phases that we have to play with in condensed matter.  

Faculty positions at Rice - follow-up

I had mentioned about 6 weeks ago that my department at Rice is searching in the quantum/AMO space for experiment and theory.   Now I want to put the larger context of this out there - Rice has four quantum-related searches going on right now:

Quantum theory (PHYA): https://apply.interfolio.com/131379

Quantum experiment (PHYA): https://apply.interfolio.com/131378

Quantum engineering (ECE): https://apply.interfolio.com/133316

Quantum materials (MSNE): https://apply.interfolio.com/135086

Interested candidates, we hope you will apply!  It's an exciting time here, and our quantum initiative folks can help make sure applications end up in the right place.  

Postdoctoral opportunities at Rice

I will be sending some emails shortly, but I wanted to point out postdoctoral opportunities here at Rice University.

The Smalley-Curl Institute is having a competition for two two-year postdoctoral fellow slots.  Click on the link for the details.  The requirements for a candidate:

• Nomination by current SCI faculty member
• Ph.D. in a field related to an SCI focus areas
• Successful Ph.D. thesis defense before start of appointment
• Ph.D. completed no more than three years before the start of the appointment

I would be happy to work with an interested, competitive candidate on this, and the deadline for applying is December 31.  Research areas in my lab these days include:  nanostructure-based studies of correlated quantum materials, including noise-based measurements; studies of spin transport and thermally driven spin effects in insulating magnets, from basic science to applications in low-power electronics; plasmon-based nanophotonic light sources and plasmonic junctions for physical chemistry.  If you're a student finishing up and are interested, please contact me, and if you're a faculty member working with possible candidates, please feel free to point out this opportunity. 

Rice also has a university-wide endowed honorific postdoctoral program called the Rice Academy of Fellows.   Like all such things, it's very competitive, and it similarly has a deadline of January 3, 2024.  Again, applicants have to have a faculty mentor, so in case someone is interested in working with me on this, please contact me via email. 

Scientific publishing - where are we going?

I think it's safe to say that anyone involved in scientific publishing will tell you that it's a mess and the trends are worrisome.  This week, this news release/article came out about this preprint which shows a number of the issues.  In brief (not all of this is in the preprint; some is me editorializing):

Figure 1 from this preprint

• The number of scientific papers being published is growing at a rate that looks completely unsustainable.  In my opinion, it's problematic on multiple levels.  There aren't enough reviewers (though that doesn't bother all publishers) and the average paper gets smaller and smaller readership (raising the question of why bother to publish papers that no one reads).  Does it make sense that the number of papers is skyrocketing while the number of PhDs granted is falling?
• Some publishers (especially Frontiers, Hindawi, MDPI) have boosted this by drastically cranking up the number of papers that they publish, through launching specialized journals with "special issues" designed to have super-short review times (assuming that review is even truly part of the process).  Lest you think this is only the provenance of publishers previously accused of being predatory, this week alone I have received five different "special issue" announcements from AIP journals.
• Why do people do this?  To try to game the impact factor calculations.  I've aired my grievances before about why journal impact factor is a lousy metric.  
• Why do people want to inflate impact factors?  Because that's how journals keep score, and some countries put in place big-time incentives tied to impact factor.  A publisher worries that if its journal's impact factor falls below some threshold, then the government of China, for example, will no longer view that journal as important, and then thousands of authors will stop submitting....
• Open access is a complicating factor, with some publishers charging absolutely sky-high charges, while at the same time having very high profit margins.  In the US, at least, those charges can be much larger than what grants will support.
• Over all of this is the concern that massively inflating the amount of scientific literature lowers its quality and undermines the credibility of science in general.  

Coincidentally, this week we hosted Steinn Sigurðsson for a colloquium.  He is now the scientific director of the arxiv, the preprint archive that went from a quick and dirty preprint sharing site in 1991 to an enormously important part of the global scientific enterprise.  In his talk he hit on some wild numbers.  The arxiv is up to around 20,000 papers per month now (!) (in part because new disciplines like quantitative biology are using the arxiv).  Thankfully the arxiv has recently landed some good support.  Their annual operating budget is around $3.5M, and this is an enormous bargain by any measure.  The arxiv is partnering with volunteer developers who are adding some neat functionality.  Unsurprisingly, generative AI is a serious concern, even more so than for the publishing houses.  

It's a transformative time, for sure.  Maybe what we are seeing is analogous to the fluctuations that happen when approaching a 2nd order phase transition, and we are headed for a real change in the way publishing works.  It's hard to see how the current trends can continue unabated.

Strategic planning + departmental reviews

It's been a while since I've written a post about the ways of academia, so I thought it might be time, though it's not exactly glamorous or exciting.  There are certain cycles in research universities, and two interrelated ones are the cycle of departmental strategic planning and the cycle of external departmental reviews.

Strategic planning can be extremely important, as it allows departments to take stock of where things are, what opportunities exist for improvement (in terms of research, teaching, departmental operations), and how the department aspires to move forward.  Often this can involve a hiring plan, based on demographic trends in the department (e.g., how many faculty lines are expected to be available in the next, say, five to seven years?), rising field/school/university research priorities (e.g., there is likely to be enormous investment in AI/ML in the coming years).  Discussions for strategic planning can be frought, since even maintaining departmental faculty size means alloting new hires between different possible research areas in a zero sum.  Still, arriving at a departmental plan is often expected at one level up (that of a School or College, depending on the university's org chart labeling scheme), and having a plan that department members know and understand is helpful in transparency of how decisions get made that shape the future of the department.  It doesn't make sense to do reformulate these plans at too rapid a frequency, since the ability to implement the plan can be strongly perturbed by, e.g., economic events, global pandemics, or big changes in university leadership.

Very often, deans (or provosts) also value periodic reviews of departments by an external visiting committee.  The visiting committee is typically put together with input from the department (research areas that should be represented, suggestions of possible reviewers) and invited to come for a couple of days of interviews and departmental presentations.  These reviews are typically very broad, looking at research, teaching, departmental climate, staffing levels and organization, infrastructure and space needs, etc.  It's important to talk to all stakeholders (departmental leadership, TT and NTT faculty, staff, undergrad and grad students, postdocs, and of course the dean or equivalent who is the intended recipient of the report). The expected output of these visits is a report to the dean (or provost).  Such a report can be very helpful for the department to get feedback on their plans and operations, and to serve as a way of putting priorities forward to the dean/provost level.  Similarly, often deans find these things valuable as a way to make certain arguments up to higher levels.  It seems to be human nature that a statement made by a nominally objective external committee can get more traction than the same statement made by locals.  Like strategic plans, it only makes sense to do external reviews on a timescale sufficiently long that the department would have a chance to address issues raised from the previous visit before the next one.  For both of these things, every five years is on the edge of being too frequent, and every ten years would definitely be too long an interval.

Participating in external visits takes time, but I've found it to be a very valuable experience.  It's allowed me to meet and work with faculty from a variety of places, and it can be very helpful to see how other institutions do things (even at a level of learning about tools like software that can be useful for tracking degree progress, or organizations that work to facilitate career placement at the graduate level).