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Complementary XFEL methods reveal O 2 reaction intermediates and global protein dynamics during Isopenicillin N synthase catalysis.
We report that lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in organic solvents (especially propylene carbonate) has demonstrated extraordinary pseudocapacitive performance as an electrolyte in the supercapacitor configuration. However, the influence of the solvated ions on the diffusivity of the solvent molecules is yet to be understood. We examine the impact of LiTFSI on the diffusivity in five organic solvents: acetonitrile (ACN), tetrahydrofuran (THF), methanol (MeOH), dimethyl sulfoxide (DMSO), and propylene carbonate (PC) using a combination of neutron scattering, conductivity measurements, and molecular dynamics simulations. The extent of the diffusivity reduction in the concentration regime of ≤1 M directly correlates with the solvent mole fraction at which the solvation shells around Li + ions are of similar size in all the solvents, resulting in a universal ~50% reduction in the solvent diffusivity. These results provide guidance for formulation of the new electrolytes to enhance the performance of energy storage devices.
Collective neutrino oscillations play a crucial role in transporting lepton flavor in astrophysical settings like supernovae and neutron star binary merger remnants, which are characterized by large neutrino densities. In these settings, simulations in the mean-field approximation show that neutrino-neutrino interactions can overtake vacuum oscillations and give rise to fast collective flavor evolution on time-scales t ∝ μ –1 , with μ proportional to the local neutrino density. In this work, we study the full out-of-equilibrium flavor dynamics in simple multi-angle geometries displaying fast oscillations in the mean field linear stability analysis. Focusing on simple initial conditions, we analyze the production of pair correlations and entanglement in the complete many-body-dynamics as a function of the number N of neutrinos in the system, for up to thousands of neutrinos. Similarly to simpler geometries with only two neutrino beams, we identify three regimes: stable configurations with vanishing flavor oscillations, marginally unstable configurations with evolution occurring on long time scales τ ≈ µ –1 $\sqrt{N}$, and unstable configurations showing flavor evolution on short time scales τ ≈ μ –1 log(N). Here, we present evidence that these fast collective modes are generated by the same dynamical phase transition which leads to the slow bipolar oscillations, establishing a connection between these two phenomena and explaining the difference in their time scales. We conclude by discussing a semi-classical approximation which reproduces the entanglement entropy at short to medium time scales and can be potentially useful in situations with more complicated geometries where classical simulation methods starts to become inefficient.
Recovering properties of correlation functions is typically challenging. On one hand, experimentally, it requires measurements with a temporal resolution finer than the system's dynamics. On the other hand, analytical or numerical analysis requires solving the system evolution. Here, we use recent results of quantum metrology with continuous measurements to derive general lower bounds on the relaxation and second-order correlation times that are both easy to calculate and measure. These bounds are based solely on steady-state expectation values and their derivatives with respect to a control parameter, and can be readily extended to the autocorrelation of arbitrary observables. We validate our method on two examples of critical quantum systems: a critical driven-dissipative resonator, where the bound matches analytical results for the dynamics, and the infinite-range Ising model, where only the steady state is solvable and thus the bound provides information beyond the reach of existing analytical approaches. Our results can be applied to experimentally characterize ultrafast systems, and to theoretically analyze many-body models with dynamics that are analytically or numerically hard.
Recovering properties of correlation functions is typically challenging. On one hand, experimentally, it requires measurements with a temporal resolution finer than the system's dynamics. On the other hand, analytical or numerical analysis requires solving the system evolution. Here, we use recent results of quantum metrology with continuous measurements to derive general lower bounds on the relaxation and second-order correlation times that are both easy to calculate and measure. These bounds are based solely on steady-state expectation values and their derivatives with respect to a control parameter, and can be readily extended to the autocorrelation of arbitrary observables. We validate our method on two examples of critical quantum systems: a critical driven-dissipative resonator, where the bound matches analytical results for the dynamics, and the infinite-range Ising model, where only the steady state is solvable and thus the bound provides information beyond the reach of existing analytical approaches. Our results can be applied to experimentally characterize ultrafast systems, and to theoretically analyze many-body models with dynamics that are analytically or numerically hard.
DNA is a re-configurable, biological information-storage unit, and much remains to be learned about its heterogeneous structural dynamics. For example, while it is known that molecular dyes templated onto DNA exhibit increased photostability, the mechanism by which the structural dynamics of DNA affect the dye photophysics remains unknown. Here, we use femtosecond, two-dimensional electronic spectroscopy measurements of a cyanine dye, Cy5, to probe local conformations in samples of single-stranded DNA (ssDNA–Cy5), double-stranded DNA (dsDNA–Cy5), and Holliday junction DNA (HJ–DNA–Cy5). A line shape analysis of the 2D spectra reveals a strong excitation–emission correlation present in only the dsDNA–Cy5 complex, which is a signature of inhomogeneous broadening. Molecular dynamics simulations support the conclusion that this inhomogeneous broadening arises from a nearly degenerate conformer found only in the dsDNA–Cy5 complex. These insights will support future studies on DNA’s structural heterogeneity.
Periodically driven quantum systems can host non-equilibrium phenomena without static analogs, including in their entanglement dynamics. Here, we discover (TET) in a Floquet spin chain, which correspond to a quantum phase transition in the spectrum of the entanglement Hamiltonian and are signaled by dynamical spontaneous symmetry breaking. We identify the symmetry principles underlying these transitions: they appear when the driven Hamiltonian preserves global symmetry (here, ℤ2), the initial state respects this symmetry, and the reduced density matrix carries weight in both subsystem-parity sectors, with TET occurring precisely when the sector weights become equal (given the previous two conditions are also satisfied). Intriguingly, we find these transitions across a broad range of driving frequencies (from adiabatic to high-frequency regime) and independently of drive details, where they manifest as periodic, sharp entanglement spectrum reorganizations marked by the Schmidt-gap closure, a vanishing entanglement echo, and symmetry-quantum-number flips, while remaining invisible to conventional local observables. At high frequencies, the entanglement Hamiltonian acquires an intrinsic timescale decoupled from the drive period, rendering the transitions genuine steady-state features. Finite-size scaling reveals universal critical behavior with correlation-length exponent 𝜈 = 1, matching equilibrium Ising universality despite its emergence from purely dynamical mechanisms decoupled from static criticality. Furthermore, our work establishes TET as novel features in Floquet quantum matter.
The structure and ultrafast dynamics of the electric double layer (EDL) are central to chemical reactivity and physical properties at solid/aqueous interfaces. While the Gouy–Chapman–Stern model is widely used to describe EDLs, it is solely based on the macroscopic electrostatic attraction of electrolytes for the charged surfaces. Structure and dynamics in the Stern layer are, however, more complex because of competing effects due to the localized surface charge distribution, surface–solvent–ion correlations, and the interfacial hydrogen bonding environment. Here, we report combined time-resolved vibrational sum frequency generation (TR-vSFG) spectroscopy with ab initio DFT-based molecular dynamics simulations (AIMD/DFT-MD) to get direct access to the molecular-level understanding of how ions change the structure and dynamics of the EDL. We show that innersphere adsorbed ions tune the hydrophobicity of the silica–aqueous interface by shifting the structural makeup in the Stern layer from dominant water–surface interactions to water–water interactions. This drives an initially inhomogeneous interfacial water coordination landscape observed at the neat interface toward a homogeneous, highly interconnected in-plane 2D hydrogen bonding (2D-HB) network at the ionic interface, reminiscent of the canonical, hydrophobic air–water interface. This ion-induced transformation results in a characteristic decrease of the vibrational lifetime (T 1 ) of excited interfacial O–H stretching modes from T 1 ~ 600 fs to T 1 ~ 250 fs. Hence, we propose that the T 1 determined by TR-vSFG in combination with DFT-MD simulations can be widely used for a quantitative spectroscopic probe of the ion kosmotropic/chaotropic effect at aqueous interfaces as well as of the ion-induced surface hydrophobicity.
The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO 2 + ) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO 2 + ) is an important factor to consider with spectrophotometric applications but has often been overlooked. Optical Vis-NIR absorption spectra (400–1700 nm) of Np(V) (0.017–0.89 M) in 1 M nitric acid were evaluated with varying temperatures (T = 10–80 °C). The intensity, position, and overall shape of the bands were sensitive to interactions with the solvent and coordination environment. Numerous temperature-induced isosbestic points were identified resulting from dynamic, overlapping peak shifts. Spectral variations were characterized using principal component analysis (PCA) and 2D correlation spectroscopy (COS). 2D-COS revealed that the absorption band near 1095 nm likely consists of two bands centered near 1087 and 1096 nm, which cannot be explained by current computational methods. 2D-COS analysis also provided an unambiguous assignment of unresolved peaks in the visible region for comparison with computational predictions. PCA was used to identify nonlinearity in the spectral response at elevated Np(V) concentrations ≥ 0.5 M. This unique experimental data and interpretation will foster a deeper understanding of the absorption spectra for complex actinyl ions.
The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.
To gain insight into crystalline protein dynamics, we performed molecular-dynamics (MD) simulations of a periodic 2 × 2 × 2 supercell of staphylococcal nuclease. We used the resulting MD trajectories to simulate X-ray diffraction and to study collective motions. The agreement of simulated X-ray diffraction with the data is comparable to previous MD simulation studies. We studied collective motions by analyzing statistically the covariance of alpha-carbon position displacements. The covariance decreases exponentially with the distance between atoms, which is consistent with a liquidlike motions (LLM) model, in which the protein behaves like a soft material. To gain finer insight into the collective motions, we examined the covariance behavior within a protein molecule (intraprotein) and between different protein molecules (interprotein). The interprotein atom pairs, which dominate the overall statistics, exhibit LLM behavior; however, the intraprotein pairs exhibit behavior that is consistent with a superposition of LLM and rigid-body motions (RBM). Our results indicate that LLM behavior of global dynamics is present in MD simulations of a protein crystal. They also show that RBM behavior is detectable in the simulations but that it is subsumed by the LLM behavior. Finally, the results provide clues about how correlated motions of atom pairs both within and across proteins might manifest in diffraction data. Overall, our findings increase our understanding of the connection between molecular motions and diffraction data and therefore advance efforts to extract information about functionally important motions from crystallography experiments.
High statistics data sets from experiments at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC) with small and large collision species have enabled a wealth of new flow measurements, including the event-by-event correlation between observables. One exciting such observable $ρ(v^2_n, [p_T])$ gauges the correlation between the mean transverse momentum of particles in an event and the various flow coefficients (v n ) in the same event [P. Bozek, Phys. Rev. C 93, 044908 (2016)]. Recently it has been proposed that very low multiplicity events may be sensitive to initial-state glasma correlations [G. Giacalone, B. Schenke, and C. Shen, Phys. Rev. Lett. 125, 192301 (2020)] rather than flow-related dynamics. We find utilizing the ip-jazma framework that the color domain explanation for the glasma results are incomplete. We then explore predictions from pythia8, and the version for including nuclear collisions called pythia-angantyr, which have only nonflow correlations, and from the ampt model which has both nonflow and flow-type correlations. We find that pythia-angantyr has nonflow contributions to $ρ(v^2_n, [p_T])$ in p + O, p + Pb, and O + O collisions that are positive at low multiplicity and comparable to the glasma correlations. It is striking that in pythia8 in p + p collisions there is actually a sign change from positive to negative $ρ(v^2_n, [p_T])$ as a function of multiplicity. The ampt results match the experimental data general trends in Pb+Pb collisions at the LHC, except at low multiplicity where ampt has the opposite sign. In p + Pb collisions, ampt has the opposite sign from experimental data and we explore this within the context of parton geometry. Predictions for p + O, O + O, and Xe + Xe are also presented.
Abstract The structural revolutions of non‐fullerene acceptors (NFAs) have driven continuous efficiency breakthroughs in organic solar cells (OSCs). Rational regulation of NFA structures toward efficient exciton dissociation and mitigated non‐radiative recombination is pivotal for OSCs. The incorporation of asymmetric side chains on NFAs can often achieve these goals by inducing a desirable aggregate state. However, it lacks the studies to directly correlate the side‐chain symmetry of NFAs with the exciton delocalization and triplet dynamics in OSCs. Herein, The influence of structural symmetry on the aggregate properties is systematically investigated and exciton/charge dynamics based on two developed biaxial‐conjugated NFAs with varied side‐chain symmetry. The symmetric NFA having diverse molecular packing orientations can form multiple charge transfer channels in its blend with polymer donor, which cannot be found in that comprising the asymmetric ones. Moreover, a slower rate and lower ratio of the spin‐triplet state are formed in the blend of symmetric NFA, resulting in a much lower non‐radiative voltage loss in corresponding OSCs. This study reveals the distinct advantages of symmetric NFAs in both aggregate properties and exciton/charge dynamics over those of asymmetric ones, paving the way for developing high‐performance OSCs using easier‐to‐prepare, low‐cost symmetric materials.
In the present study, we investigate different data-driven parameterizations for large eddy simulation of two-dimensional turbulence in the a priori settings. These models utilize resolved flow field variables on the coarser grid to estimate the subgrid-scale stresses. We use data-driven closure models based on localized learning that employs a multilayer feedforward artificial neural network with point-to-point mapping and neighboring stencil data mapping, and convolutional neural network fed by data snapshots of the whole domain. The performance of these data-driven closure models is measured through a probability density function and is compared with the dynamic Smagorinksy model (DSM). The quantitative performance is evaluated using the cross-correlation coefficient between the true and predicted stresses. We analyze different frameworks in terms of the amount of training data, selection of input and output features, their characteristics in modeling with accuracy, and training and deployment computational time. We also demonstrate computational gain that can be achieved using the intelligent eddy viscosity model that learns eddy viscosity computed by the DSM instead of subgrid-scale stresses. Here, we detail the hyperparameters optimization of these models using the grid search algorithm.
In spite of many years of research, the physical phenomena leading to the evolution of compacted graphite (CG) during solidification is still not fully understood. In particular, it is unknown how highly branched CG aggregates form and evolve in the semi-solid, and how local microstructural variations at micrometer length scale affect this growth process. We present here the first time-resolved synchrotron tomography combined with a bespoke high-temperature environmental cell that allows direct observation of the evolution of CG and relates this dynamic process to the local surrounding microstructures in a cast iron sample during repeated melting and solidification. Distinct processes are identified for the formation of CG involving the nucleation, growth, development of branches and interconnection of graphite particles, ultimately evolving into highly branched graphite aggregates with large sizes and low sphericities. CG is found to nucleate with a spheroidal or a plate-like shape, developing branches induced by high carbon concentration, e.g. thin melt channels. Additionally, CG grows much faster than spheroidal graphite during subsequent cooling in solid state. The direct visualization of the dynamic solidification process provides unprecedented new insights into formation mechanisms of CG and correlating factors such as local microstructural variations, and guides the development of CG iron solidification models.
Various helium (He)-cooled solid-tungsten (W) divertor concepts have been proposed for long-pulse magnetic fusion energy reactors. Among these concepts, the He-cooled flat plate divertor (HCFP) modules have the largest plasma-facing surface area of ~0.2 m 2 . Simulations have shown that the most recent version of the design can withstand heat fluxes as great as 8 MW/m 2 . Earlier experimental studies of a single shortened HCFP cooling unit with a slot length of 7.6 cm used air at ambient temperature and pressures below 0.6 MPa. Here, we present initial experimental studies of a copper alloy and steel test section modeling a shortened HCFP cooling unit using He at prototypical pressure of 10 MPa, inlet temperatures T i ≤ 200 °C and steady-state incident heat fluxes q" ≤ 1.2 MW/m 2 . Results for Nusselt number Nu as a function of Reynolds number Re were obtained for Re = 1.2×10 4 –3.4×10 4 , and used to develop a Nu(Re) correlation and validate numerical models of the test section using commercial computational fluid dynamics (CFD) software. Simulations with this model are performed to evaluate the effect of the shortened slot. Furthermore, these analyses are used to estimate the thermal-fluids performance of the HCFP under prototypical conditions.
The metal halide ionic octahedron, represented as [MX 6 ] $n$- (M = metal cation, X = halide anion), serves as the basic structural unit in halide perovskites and plays a crucial role in determining their optoelectronic and chemical properties. Thus, it is possible to correlate the responses of metal halide perovskites to various environmental stimuli with the dynamic behaviors of the [MX 6 ] $n$- octahedra. In this study, with the temperature-dependent single-crystal X ray diffraction (SCXRD) measurements on Cs 3 Bi 2 Br 9 2D halide perovskites, we can identify two classes of distortions through the lowering of temperature: intraoctahedral distortion, which is the off-centering of Bi 3+ cation within a [BiBr 6 ] 3– octahedron due to the Bi 3+ 6s 2 lone pair electrons, and interoctahedral distortion, which is the collective misalignments among the [BiBr 6 ] 3– building blocks. Free exciton (FE) and self-trapped exciton (STE) models are used to study the relationship between the distortion of octahedra in Cs 3 Bi 2 Br 9 and the corresponding changes in its optoelectronic properties, which transform from dominating blue emission above 100 K to red emission at 4 K. In conclusion, this work provides new insights into the excitonic behaviors of perovskites and suggests a possibility that we can design and rationalize the optical properties of halide perovskites by regulating the environmental stimuli based on the knowledge of behaviors of the individual [MX 6 ] $n$- building blocks.
Solid polymer electrolytes (SPEs) hold great promise for the advancement of next-generation energy storage devices. However, the ion transport mechanism in SPEs remains poorly understood. In this study, we investigate blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (P(MTFSI)Li) of varying molar ratios to develop a mechanistic understanding of ionic conductivity in a miscible polyzwitterion/polyanion system. Polyanions can act as single-ion conductors, but conductivity is often prohibitively low due to the decreased segmental mobility and ion aggregation. Here, it is hypothesized that the introduction of a polyzwitterion would competitively interact with the polyanion charge groups to realize improvements in the conductivity. Attractive interactions between the polyanions and polyzwitterions are confirmed by the blend’s increased glass transition temperature using the Gordon–Taylor equation. Notably, an ordered local nanostructure (∼24 Å) emerged in the P2VPPS/P(MTFSI)Li system at certain compositions, as characterized by small-angle X-ray and neutron scattering (SAXS/SANS). Concurrent with the emergence of this structure, broadband dielectric spectroscopy confirmed improvements in ionic conductivity. The highest conductivity is observed at a specific blend ratio P2VPPS:P(MTFSI)Li = 0.2:1 in the glassy state and 0.3:1 in the rubbery state, corresponding to the lowest effective activation energy (E*). Coarse-grained molecular dynamics simulations further emphasize the role of complexation between polyzwitterion and polyanion chains, correlating with the emergence of a new peak in SAXS and SANS for the blends. This work provides a fresh perspective on the role of local structural design in developing SPEs and offers insights into the morphological effects on ionic conductivity.