In clean two-dimensional (2D) systems, electrons are expected to self-organize into a regular lattice, a Wigner crystal, when their mutual Coulomb repulsion overwhelms kinetic energy. Understanding the Wigner crystal at zero magnetic field is a long-sought goal in physics, thanks to its fundamental simplicity and possible connection to the density-driven metal-insulator transition. To date, evidence for such a crystal has been reported across various platforms. However, the AC conductivity of a zero-field Wigner crystal, a key observable characterizing its electrodynamics, has never been measured. Here, we develop an ultrasensitive on-chip terahertz (THz) spectroscopy technique to probe the AC conductivity in electrostatically gated monolayer MoSe2 encapsulated in hexagonal boron nitride. We observe a sub-THz resonance corresponding to the pinning mode of a zero-field Wigner crystal, whose frequency is orders of magnitude higher than those under high magnetic fields. Using the pinning mode as an indicator, we reveal that moderate disorder notably stabilizes the Wigner crystal. With increasing density towards melting, we find that the pinning mode of the Wigner crystal coexists with a growing Drude component characteristic of an electron liquid, and the competition between these two components in the conductivity spectra leads to the insulator-metal transition of the 2D electron system. Our findings not only elucidate the low-energy electrodynamics of a zero-field Wigner crystal, but also establish on-chip THz spectroscopy as a powerful probe for correlated quantum phases in two-dimensional materials.

Understanding transport processes in complex nanoscale systems, like ionic conductivities in nanofluidic devices or heat conduction in low dimensional solids, poses the problem of examining fluctuations of currents within nonequilibrium steady states and relating those fluctuations to nonlinear or anomalous responses. We have developed a systematic framework for computing distributions of time integrated currents in molecular models and relating cumulants of those distributions to nonlinear transport coefficients. The approach elaborated upon in this perspective follows from the theory of dynamical large deviations, benefits from substantial previous formal development, and has been illustrated in several applications. The framework provides a microscopic basis for going beyond traditional hydrodynamics in instances where local equilibrium assumptions break down, which are ubiquitous at the nanoscale.

We present a method to probe rare molecular dynamics trajectories directly using reinforcement learning. We consider trajectories that are conditioned to transition between regions of configuration space in finite time, like those relevant in the study of reactive events, as well as trajectories exhibiting rare fluctuations of time-integrated quantities in the long time limit, like those relevant in the calculation of large deviation functions. In both cases, reinforcement learning techniques are used to optimize an added force that minimizes the Kullback-Leibler divergence between the conditioned trajectory ensemble and a driven one. Under the optimized added force, the system evolves the rare fluctuation as a typical one, affording a variational estimate of its likelihood in the original trajectory ensemble. Low variance gradients employing value functions are proposed to increase the convergence of the optimal force. The method we develop employing these gradients leads to efficient and accurate estimates of both the optimal force and the likelihood of the rare event for a variety of model systems.

We use prompt engineering to guide ChatGPT in the automation of text mining of metal-organic frameworks (MOFs) synthesis conditions from diverse formats and styles of the scientific literature. This effectively mitigates ChatGPT's tendency to hallucinate information -- an issue that previously made the use of Large Language Models (LLMs) in scientific fields challenging. Our approach involves the development of a workflow implementing three different processes for text mining, programmed by ChatGPT itself. All of them enable parsing, searching, filtering, classification, summarization, and data unification with different tradeoffs between labor, speed, and accuracy. We deploy this system to extract 26,257 distinct synthesis parameters pertaining to approximately 800 MOFs sourced from peer-reviewed research articles. This process incorporates our ChemPrompt Engineering strategy to instruct ChatGPT in text mining, resulting in impressive precision, recall, and F1 scores of 90-99%. Furthermore, with the dataset built by text mining, we constructed a machine-learning model with over 86% accuracy in predicting MOF experimental crystallization outcomes and preliminarily identifying important factors in MOF crystallization. We also developed a reliable data-grounded MOF chatbot to answer questions on chemical reactions and synthesis procedures. Given that the process of using ChatGPT reliably mines and tabulates diverse MOF synthesis information in a unified format, while using only narrative language requiring no coding expertise, we anticipate that our ChatGPT Chemistry Assistant will be very useful across various other chemistry sub-disciplines.

Phononic engineering at gigahertz (GHz) frequencies form the foundation of microwave acoustic filters, acousto-optic modulators, and quantum transducers. Terahertz (THz) phononic engineering could lead to acoustic filters and modulators at higher bandwidth and speed, as well as quantum circuits operating at higher temperatures. Despite its potential, methods for engineering THz phonons have been limited due to the challenges of achieving the required material control at sub-nanometer precision and efficient phonon coupling at THz frequencies. Here, we demonstrate efficient generation, detection, and manipulation of THz phonons through precise integration of atomically thin layers in van der Waals heterostructures. We employ few-layer graphene (FLG) as an ultrabroadband phonon transducer, converting femtosecond near-infrared pulses to acoustic phonon pulses with spectral content up to 3 THz. A monolayer WSe$_2$ is used as a sensor, where high-fidelity readout is enabled by the exciton-phonon coupling and strong light-matter interactions. Combining these capabilities in a single heterostructure and detecting responses to incident mechanical waves, we perform THz phononic spectroscopy. Using this platform, we demonstrate high-Q THz phononic cavities and show that a monolayer WSe$_2$ embedded in hexagonal boron nitride (hBN) can efficiently block the transmission of THz phonons. By comparing our measurements to a nanomechanical model, we obtain the force constants at the heterointerfaces. Our results could enable THz phononic metamaterials for ultrabroadband acoustic filters and modulators, and open novel routes for thermal engineering.

The exceptional tunability of two-dimensional van der Waals materials offers unique opportunities for exploring novel superconducting phases. However, in such systems, the measurement of superfluid phase stiffness, a fundamental property of a superconductor, is challenging because of the mesoscopic sample size. Here, we introduce a contact-free technique for probing the electrodynamic response, and thereby the phase stiffness, of atomically thin superconductors using on-chip superconducting microwave resonators. We demonstrate this technique on 4Hb-TaS$_2$, a van der Waals superconductor whose gap structure under broken mirror symmetry is under debate. In our cleanest few-layer device, we observe a superconducting critical temperature comparable to that of the bulk. The temperature evolution of the phase stiffness features nodeless behavior in the presence of broken mirror symmetry, inconsistent with the scenario of nodal surface superconductivity. With minimal fabrication requirements, our technique enables microwave measurements across wide ranges of two-dimensional superconductors.

Phononic engineering at gigahertz (GHz) frequencies form the foundation of microwave acoustic filters, acousto-optic modulators, and quantum transducers. Terahertz (THz) phononic engineering could lead to acoustic filters and modulators at higher bandwidth and speed, as well as quantum circuits operating at higher temperatures. Despite its potential, methods for engineering THz phonons have been limited due to the challenges of achieving the required material control at sub-nanometer precision and efficient phonon coupling at THz frequencies. Here, we demonstrate efficient generation, detection, and manipulation of THz phonons through precise integration of atomically thin layers in van der Waals heterostructures. We employ few-layer graphene (FLG) as an ultrabroadband phonon transducer, converting femtosecond near-infrared pulses to acoustic phonon pulses with spectral content up to 3 THz. A monolayer WSe$_2$ is used as a sensor, where high-fidelity readout is enabled by the exciton-phonon coupling and strong light-matter interactions. Combining these capabilities in a single heterostructure and detecting responses to incident mechanical waves, we perform THz phononic spectroscopy. Using this platform, we demonstrate high-Q THz phononic cavities and show that a monolayer WSe$_2$ embedded in hexagonal boron nitride (hBN) can efficiently block the transmission of THz phonons. By comparing our measurements to a nanomechanical model, we obtain the force constants at the heterointerfaces. Our results could enable THz phononic metamaterials for ultrabroadband acoustic filters and modulators, and open novel routes for thermal engineering.

We propose a method to compute free energies from nonadiabatic alchemical transformations using diffusion-denoising generative models. The method, nonadiabatic force matching, hinges on estimating -- rather than minimizing -- the dissipation along an alchemical transition as the functional of a nonadiabatic potential, which plays the role of a diffusion-denoising protocol. Applying the algorithm to compute alchemical free energies of simple atomistic models shows it can significantly cut the simulation cost of a free-energy estimate at no loss of accuracy compared with thermodynamic integration.

We introduce a variational algorithm to estimate the likelihood of a rare event within a nonequilibrium molecular dynamics simulation through the evaluation of an optimal control force. Optimization of a control force within a chosen basis is made possible by explicit forms for the gradients of a cost function in terms of the susceptibility of driven trajectories to changes in variational parameters. We consider probabilities of time-integrated dynamical observables as characterized by their large deviation functions, and find that in many cases the variational estimate is quantitatively accurate. Additionally, we provide expressions to exactly correct the variational estimate that can be evaluated directly. We benchmark this algorithm against the numerically exact solution of a model of a driven particle in a periodic potential, where the control force can be represented with a complete basis. We then demonstrate the utility of the algorithm in a model of repulsive particles on a line, which undergo a dynamical phase transition, resulting in singular changes to the form of the optimal control force. In both systems, we find fast convergence and are able to evaluate large deviation functions with significant increases in statistical efficiency over alternative Monte Carlo approaches.

The phenomenological equations of hydrodynamics describe emergent behavior in many body systems. Their forms and the associated phenomena are well established when the quiescent state of the system is one of thermodynamic equilibrium, yet away from equilibrium relatively little is firmly established. Here, we deduce directly from first principles the hydrodynamic equations for a system far from equilibrium, a chiral active fluid in which both parity and time-reversal symmetries are broken. With our theory, we rationalize the emergence of a spontaneous boundary current in the confined fluid, a feature forbidden at equilibrium, which allows us to extract estimates of transport coefficients that we favorably compare to forced flows. The hydrodynamic solution reveals that the boundary current is analogous to a quasigeostrophic coastal current, a well known phenomenon in oceanography. Such currents are conjugate to a class of chiral waves called Kelvin waves. Motivated by this analogy, we demonstrate that an acoustic chiral Kelvin wave mode also exists in confined chiral active matter in the absence of an imposed rotation, originating from the spontaneous emergence of a Coriolis-like parameter in the bound modes of a chiral fluid.

We use path integral Monte Carlo to study the energetics of excitons in layered, hybrid organic-inorganic perovskites in order to elucidate the relative contributions of dielectric confinement and electron-phonon coupling. While the dielectric mismatch between polar perovskite layers and non-polar ligand layers significantly increases the exciton binding energy relative to their three dimensional bulk crystal counterparts, formation of exciton polarons attenuates this effect. The contribution from polaron formation is found to be a non-monotonic function of the lead halide layer thickness, which is clarified by a general variational theory. Accounting for both of these effects provides a description of exciton binding energies in good agreement with experimental measurements. By studying isolated layers and stacked layered crystals of various thicknesses, with ligands of varying polarity, we provide a systematic understanding of the excitonic behavior of this class of materials and how to engineer their photophysics.

Using a thermodynamically consistent, mesoscopic model for modern complementary metal-oxide-semiconductor transistors, we study an array of logical circuits and explore how their function is constrained by recent thermodynamic uncertainty relations when operating near thermal energies. For a single NOT gate, we find operating direction-dependent dynamics, and a trade-off between dissipated heat and operation time certainty. For a memory storage device, we find an exponential relationship between the memory retention time and energy required to sustain that memory state. For a clock, we find that the certainty in the cycle time is maximized at biasing voltages near thermal energy, as is the trade-off between this certainty and the heat dissipated per cycle. We identify a control mechanism that can increase the cycle time certainty without an offsetting increase in heat dissipation by working at a resonance condition for the clock. These results provide a framework for assessing thermodynamic costs of realistic computing devices, allowing for circuits to be designed and controlled for thermodynamically optimal operation.

We study diffusion-controlled processes in nonequilibrium steady states, where standard rate theory assumptions break down. Using transition path theory, we generalize the relations between reactive probability fluxes and measures of the rate of the reaction. Stochastic thermodynamics analysis reveals how work constrains the enhancement of rates relative to their equilibrium values. An analytically solvable ion pairing model under a strong electric field illustrates and validates our approach and theory. These findings provide deeper insights into diffusion-controlled reaction dynamics beyond equilibrium.

We evaluate the exponentially rare fluctuations of the ionic current for a dilute electrolyte by means of macroscopic fluctuation theory. We consider the fluctuating hydrodynamics of a fluid electrolyte described by a stochastic Poisson-Nernst-Planck equation. We derive the Euler-Lagrange equations that dictate the optimal concentration profiles of ions conditioned on exhibiting a given current, whose form determines the likelihood of that current in the long-time limit. For a symmetric electrolyte under small applied voltages, number density fluctuations are small, and ionic current fluctuations are Gaussian with a variance determined by the Nernst-Einstein conductivity. Under large applied potentials, where number densities vary, the ionic current distribution is generically non-Gaussian. Its structure is constrained thermodynamically by Gallavotti-Cohen symmetry and the thermodynamic uncertainty principle.

Moiré systems made from stacked two-dimensional materials host novel correlated and topological states that can be electrically controlled via applied gate voltages. We have used this technique to manipulate Chern domains in an interaction-driven quantum anomalous Hall insulator made from twisted monolayer-bilayer graphene (tMBLG). This has allowed the wavefunction of chiral interface states to be directly imaged using a scanning tunneling microscope (STM). To accomplish this tMBLG carrier concentration was tuned to stabilize neighboring domains of opposite Chern number, thus providing topological interfaces completely devoid of any structural boundaries. STM tip pulse-induced quantum dots were utilized to induce new Chern domains and thereby create new chiral interface states with tunable chirality at predetermined locations. Theoretical analysis confirms the chiral nature of observed interface states and enables the determination of the characteristic length scale of valley polarization reversal across neighboring tMBLG Chern domains. tMBLG is shown to be a useful platform for imaging the exotic topological properties of correlated moiré systems.

We present a solution for the Green's function for the general case of a helical wormlike chain with twist-bend coupling, and demonstrate the applicability of our solution for evaluating general structural and mechanical chain properties. We find that twist-bend coupling renormalizes the persistence length and the force-extension curves relative to worm-like chains. Analysis of intrinsically twisted polymers shows that incorporation of twist-bend coupling results in the oscillatory behavior in principal tangent correlations that are observed in some studies of synthetic polymers. The exact nature of our solution provides a framework to evaluate the role of twist-bend coupling on polymer properties and motivates the reinterpretation of existing bio-polymer experimental data.

Combining Deep-UV second harmonic generation spectroscopy with molecular simulations, we confirm and quantify the specific adsorption of guanidinium cations to the air-water interface. Using a Langmuir analysis and measurements at multiple concentrations, we extract the Gibbs free energy of adsorption, finding it larger than typical thermal energies. Molecular simulations clarify the role of polarizability in tuning the thermodynamics of adsorption, and establish the preferential parallel alignment of guanidinium at the air-water interface. Guanidinium is the first polyatomic cation proven to exhibit a propensity for the air-water interface. As such, these results expand on the growing body of work on specific ion adsorption.

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using a custom built sample stage and automation program. The program is capable of operating over many hours without human intervention improving the statistics of high-resolution experiments.

The interplay between symmetry and topology in magnetic materials makes it possible to engineer exotic phases and technologically useful properties. A key requirement for these pursuits is achieving control over local crystallographic and magnetic structure, usually through sample morphology (such as synthesis of bulk crystals versus thin-films) and application of magnetic or electric fields. Here we show that V$_{1/3}$NbS$_2$ can be crystallized in two ordered superlattices, distinguished by the periodicity of out-of-plane magnetic intercalants. Whereas one of these structures is metallic and displays the hallmarks of altermagnetism, the other superlattice, which has not been isolated before in this family of intercalation compounds, is a semimetallic noncollinear antiferromagnet that may enable access to topologically nontrivial properties. This observation of an unconventional superlattice structure establishes a powerful route for tailoring the tremendous array of magnetic and electronic behaviors hosted in related materials.

The cobalt-intercalated transition metal dichalcogenide Co$_x$TaS$_2$ hosts a rich landscape of magnetic phases that depend sensitively on $x$. While the stoichiometric compound with $x=1/3$ exhibits a single magnetic transition, samples with $x\leq 0.325$ display two transitions with an anomalous Hall effect (AHE) emerging in the lower temperature phase. Here, we resolve the spin structure in each phase by employing a suite of magneto-optical probes that include the discovery of anomalous magneto-birefringence -- a spontaneous time-reversal sensitive rotation of the principal optic axes. A symmetry-based analysis identifies the AHE-active phase as an anisotropic (2+1)\textbf{Q} state, in which magnetic modulation at one wavevector (\textbf{Q}) differs in symmetry from that at the remaining two. The (2+1)\textbf{Q} state naturally exhibits scalar spin chirality as a mechanism for the AHE and expands the classification of multi-Q magnetic phases.