Insights into the cavitation morphology of rubber reinforced with a nano-filler

Notwithstanding the various uses of rubber, the fracture mechanism of filler-reinforced rubber remains unclear. This study used four-dimensional computed tomography (4D-CT) involving monochromatic synchrotron X-rays to examine the cavitation within silica-reinforced rubber quantitatively and systematically. The results suggested a threshold value of silica content for the cavitation morphology. Macroscopic fractures, such as those developed by void formation, occurred below the threshold value of silica content. Above this threshold, the density of rubber decreased but macroscopic voids rarely occurred. The lower-density rubber area in the high-silica-content rubber was reversible at the effective pixel size for 4D-CT. These results suggest that the growth of the damage points to macrosized voids could be stopped by the formation of a network of rigid polymer layers. This study allows the elucidation of the reinforcing mechanism and the cavitation morphology of filler-reinforced rubber.

The influence of single carbon atom impurity on the electronic transport of (6, 3) two side-closed single-walled boron nitride nanotubes

CONTEXT

In this study, the electronic transport of (6, 3) two side-closed single-walled boron nitride nanotubes ((6, 3) TSC-SWBNNTs) located between two electrodes of (5, 5) conductive carbon nanotubes is investigated. Introducing carbon impurities instead of nitrogen and boron atoms in different locations of two side-closed (6, 3) SWBNNTs would change the transmission spectrum and reduce the gap. As the bias voltage increases, the peaks of the transmission spectrum become sharper and narrower. Substituting carbon impurities instead of nitrogen atoms leads to larger currents than substituting carbon impurities instead of boron. For the carbon impurity instead of N atoms, the current in the center is observed to be larger than currents on the left and right sides. In addition, negative resistance can be seen in current-voltage diagrams, which are used in the construction of high-speed electronic switches in electrical circuits.

METHOD

Due to the larger number of atoms, the study of structures by the common approach is time-consuming and some times impossible. Hence, in this research, the Quantum ATK simulation software is used to investigate the characteristics of electronic transport. For this purpose, the Slater-Koster method and the tight-closure approximation are used. In this method, the non-equilibrium Green function (NEGF) approach is employed.

Ultrafast electron dynamics in a topological surface state observed in two-dimensional momentum space

We study ultrafast population dynamics in the topological surface state of Sb[Formula: see text]Te[Formula: see text] in two-dimensional momentum space with time- and angle-resolved two-photon photoemission spectroscopy. Linearly polarized mid-infrared pump pulses are used to permit a direct optical excitation across the Dirac point. We show that this resonant excitation is strongly enhanced within the Dirac cone along three of the six [Formula: see text]-[Formula: see text] directions and results in a macroscopic photocurrent when the plane of incidence is aligned along a [Formula: see text]-[Formula: see text] direction. Our experimental approach makes it possible to disentangle the decay of transiently excited population and photocurent by elastic and inelastic electron scattering within the full Dirac cone in unprecedented detail. This is utilized to show that doping of Sb[Formula: see text]Te[Formula: see text] by vanadium atoms strongly enhances inelastic electron scattering to lower energies, but only scarcely affects elastic scattering around the Dirac cone.

Observation of entanglement transition of pseudo-random mixed states

Random quantum states serve as a powerful tool in various scientific fields, including quantum supremacy and black hole physics. It has been theoretically predicted that entanglement transitions may happen for different partitions of multipartite random quantum states; however, the experimental observation of these transitions is still absent. Here, we experimentally demonstrate the entanglement transitions witnessed by negativity on a fully connected superconducting processor. We apply parallel entangling operations, that significantly decrease the depth of the pseudo-random circuits, to generate pseudo-random pure states of up to 15 qubits. By quantum state tomography of the reduced density matrix of six qubits, we measure the negativity spectra. Then, by changing the sizes of the environment and subsystems, we observe the entanglement transitions that are directly identified by logarithmic entanglement negativities based on the negativity spectra. In addition, we characterize the randomness of our circuits by measuring the distance between the distribution of output bit-string probabilities and the Porter-Thomas distribution. Our results show that superconducting processors with all-to-all connectivity constitute a promising platform for generating random states and understanding the entanglement structure of multipartite quantum systems.

Quantum transports in two-dimensions with long range hopping

We investigate the effects of disorder and shielding on quantum transports in a two dimensional system with all-to-all long range hopping. In the weak disorder, cooperative shielding manifests itself as perfect conducting channels identical to those of the short range model, as if the long range hopping does not exist. With increasing disorder, the average and fluctuation of conductance are larger than those in the short range model, since the shielding is effectively broken and therefore long range hopping starts to take effect. Over several orders of disorder strength (until [Formula: see text] times of nearest hopping), although the wavefunctions are not fully extended, they are also robustly prevented from being completely localized into a single site. Each wavefunction has several localization centers around the whole sample, thus leading to a fractal dimension remarkably smaller than 2 and also remarkably larger than 0, exhibiting a hybrid feature of localization and delocalization. The size scaling shows that for sufficiently large size and disorder strength, the conductance tends to saturate to a fixed value with the scaling function [Formula: see text], which is also a marginal phase between the typical metal ([Formula: see text]) and insulating phase ([Formula: see text]). The all-to-all coupling expels one isolated but extended state far out of the band, whose transport is extremely robust against disorder due to absence of backscattering. The bond current picture of this isolated state shows a quantum version of short circuit through long hopping.

Topological antichiral surface states in a magnetic Weyl photonic crystal

Chiral edge states that propagate oppositely at two parallel strip edges are a hallmark feature of Chern insulators which were first proposed in the celebrated two-dimensional (2D) Haldane model. Subsequently, counterintuitive antichiral edge states that propagate in the same direction at two parallel strip edges were discovered in a 2D modified Haldane model. Recently, chiral surface states, the 2D extension of one-dimensional (1D) chiral edge states, have also been observed in a photonic analogue of a 3D Haldane model. However, despite many recent advances in antichiral edge states and chiral surface states, antichiral surface states, the 2D extension of 1D antichiral edge states, have never been realized in any physical system. Here, we report the experimental observation of antichiral surface states by constructing a 3D modified Haldane model in a magnetic Weyl photonic crystal with two pairs of frequency-shifted Weyl points (WPs). The 3D magnetic Weyl photonic crystal consists of gyromagnetic cylinders with opposite magnetization in different triangular sublattices of a 3D honeycomb lattice. Using microwave field-mapping measurements, unique properties of antichiral surface states have been observed directly, including the antichiral robust propagation, tilted surface dispersion, a single open Fermi arc connecting two projected WPs and a single Fermi loop winding around the surface Brillouin zone (BZ). These results extend the scope of antichiral topological states and enrich the family of magnetic Weyl semimetals.

Improving the prediction of glassy dynamics by pinpointing the local cage

The relationship between structure and dynamics in glassy fluids remains an intriguing open question. Recent work has shown impressive advances in our ability to predict local dynamics using structural features, most notably due to the use of advanced machine learning techniques. Here, we explore whether a simple linear regression algorithm combined with intelligently chosen structural order parameters can reach the accuracy of the current, most advanced machine learning approaches for predicting dynamic propensity. To achieve this, we introduce a method to pinpoint the cage state of the initial configuration-i.e., the configuration consisting of the average particle positions when particle rearrangement is forbidden. We find that, in comparison to both the initial state and the inherent state, the structure of the cage state is highly predictive of the long-time dynamics of the system. Moreover, by combining the cage state information with the initial state, we are able to predict dynamic propensities with unprecedentedly high accuracy over a broad regime of time scales, including the caging regime.

Tomography of Feshbach resonance states

Feshbach resonances are fundamental to interparticle interactions and become particularly important in cold collisions with atoms, ions, and molecules. In this work, we present the detection of Feshbach resonances in a benchmark system for strongly interacting and highly anisotropic collisions: molecular hydrogen ions colliding with noble gas atoms. The collisions are launched by cold Penning ionization, which exclusively populates Feshbach resonances that span both short- and long-range parts of the interaction potential. We resolved all final molecular channels in a tomographic manner using ion-electron coincidence detection. We demonstrate the nonstatistical nature of the final-state distribution. By performing quantum scattering calculations on ab initio potential energy surfaces, we show that the isolation of the Feshbach resonance pathways reveals their distinctive fingerprints in the collision outcome.

Long-distance hormone transport via the phloem

Several key plant hormones are synthesised in the shoot and are advected within the phloem to the root tip. In the root tip, these hormones regulate growth and developmental processes, and responses to environmental cues. However, we lack understanding of how environmental factors and biological parameters affect the delivery of hormones to the root tip. In this study, we build on existing models of phloem flow to develop a mathematical model of sugar transport alongside the transport of a generic hormone. We derive the equations for osmotically driven flow in a long, thin pipe with spatially varying membrane properties to capture the phloem loading and unloading zones. Motivated by experimental findings, we formulate solute membrane transport in terms of passive and active components, and incorporate solute unloading via bulk flow (i.e. advection with the water efflux) by including the Staverman reflection coefficient. We use the model to investigate the coupling between the sugar and hormone dynamics. The model predicts that environmental cues that lead to an increase in active sugar loading, an increase in bulk flow sugar unloading or a decrease in the relative root sugar concentration result in an increase in phloem transport velocity. Furthermore, the model reveals that such increases in phloem transport velocity result in an increase in hormone delivery to the root tip for passively loaded hormones.

Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry

Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.

Uncovering the bridging role of slow atoms in unusual caged dynamics and β-relaxation of binary metallic glasses

The origin of β-relaxation in metallic glasses is still not fully understood, and the guidance of slow atoms for caged dynamics and β-relaxation is rarely mentioned. Using molecular dynamics simulations, we reveal the bridging role of slow atoms on unusual caged dynamics and β-relaxation. In the stage of unusual caged dynamics, slow atoms are bounded by neighboring atoms. It is difficult for the slow atoms to break the cage, producing more high-frequency vibration, which causes more atoms to jump out of the cage randomly in the next stage. Precisely, the movement of the slow atoms changes from individual atoms vibrating inside the cage and gradually breaking out of the cage into a string-like pattern. The string-like collective atomic jumps cause decay of the cages, inducing β-relaxation. This situation generally exists in binary systems with the large atomic mass difference. This work offers valuable insights for understanding the role of slow atoms in unusual caged dynamics and β-relaxation, complementing studies on the origin of β-relaxation in metallic glasses and their glass-forming liquids.

Time-reversal even charge hall effect from twisted interface coupling

Under time-reversal symmetry, a linear charge Hall response is usually deemed to be forbidden by the Onsager relation. In this work, we discover a scenario for realizing a time-reversal even linear charge Hall effect in a non-isolated two-dimensional crystal allowed by time reversal symmetry. The restriction by Onsager relation is lifted by interfacial coupling with an adjacent layer, where the overall chiral symmetry requirement is fulfilled by a twisted stacking. We reveal the underlying band geometric quantity as the momentum-space vorticity of layer current. The effect is demonstrated in twisted bilayer graphene and twisted homobilayer transition metal dichalcogenides with a wide range of twist angles, which exhibit giant Hall ratios under experimentally practical conditions, with gate voltage controlled on-off switch. This work reveals intriguing Hall physics in chiral structures, and opens up a research direction of layertronics that exploits the quantum nature of layer degree of freedom to uncover exciting effects.

Extreme ultraviolet metalens by vacuum guiding

Extreme ultraviolet (EUV) radiation is a key technology for material science, attosecond metrology, and lithography. Here, we experimentally demonstrate metasurfaces as a superior way to focus EUV light. These devices exploit the fact that holes in a silicon membrane have a considerably larger refractive index than the surrounding material and efficiently vacuum-guide light with a wavelength of ~50 nanometers. This allows the transmission phase at the nanoscale to be controlled by the hole diameter. We fabricated an EUV metalens with a 10-millimeter focal length that supports numerical apertures of up to 0.05 and used it to focus ultrashort EUV light bursts generated by high-harmonic generation down to a 0.7-micrometer waist. Our approach introduces the vast light-shaping possibilities provided by dielectric metasurfaces to a spectral regime that lacks materials for transmissive optics.

A multi-fragment real-time extension of projected density matrix embedding theory: Non-equilibrium electron dynamics in extended systems

In this work, we derive a multi-fragment real-time extension of the projected density matrix embedding theory (pDMET) designed to treat non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static pDMET, the real time pDMET partitions the total system into many fragments; the coupling between each fragment and the rest of the system is treated through a compact representation of the environment in terms of a quantum bath. The real-time pDMET involves simultaneously propagating the wavefunctions for each separate fragment–bath embedding system along with an auxiliary mean-field wavefunction of the total system. The equations of motion are derived by (i) projecting the time-dependent Schrödinger equation in the fragment and bath space associated with each separate fragment and by (ii) enforcing the pDMET matching conditions between the global 1-particle reduced density matrix (1-RDM) obtained from the fragment calculations and the mean-field 1-RDM at all points in time. The accuracy of the method is benchmarked through comparisons to time-dependent density-matrix renormalization group and time-dependent Hartree–Fock (TDHF) theory; the methods were applied to a one- and two-dimensional single-impurity Anderson model and multi-impurity Anderson models with ordered and disordered distributions of the impurities. The results demonstrate a large improvement over TDHF and rapid convergence to the exact dynamics with an increase in fragment size. Our results demonstrate that the real-time pDMET is a promising and flexible method that balances accuracy and efficiency to simulate the non-equilibrium electron dynamics in heterogeneous systems of large size.

Higher-order Rayleigh-quotient gradient effect on electron correlations

The incomplete understanding of electron correlation is still profound due to the lack of exact solutions of the Schrödinger equation of many electron systems. In this work, we present the correlation-induced changes in the calculated many-electron systems beyond the standard residual. To locate the minimum of the Rayleigh quotient, each iteration is to seek the lowest eigenpairs in a subspace spanned by the current wave function and its gradient of the Rayleigh-quotient as well as the upcoming higher-order residual. Consequently, as the upcoming errors can be introduced and circumvented with the search in the higher-order residual, a concomitant improved performance in terms of number of iterations, convergence rate, and total elapsed time is very significant. The correlation energy components obtained with the original residual are corrected with the higher-order residual application, satisfying the correlation virial theorem with much improved accuracy. The comparison with the original residual, the higher-order residual significantly improves the electron binding, favoring the localization of electrons’ distribution, revealed with the increasing peak of the distribution and correlation function and the reduced interelectron distance and its angle.

Testing electron-phonon coupling for the superconductivity in kagome metal CsV3Sb5

In crystalline materials, electron-phonon coupling (EPC) is a ubiquitous many-body interaction that drives conventional Bardeen-Cooper-Schrieffer superconductivity. Recently, in a new kagome metal CsV₃Sb₅, superconductivity that possibly intertwines with time-reversal and spatial symmetry-breaking orders is observed. Density functional theory calculations predicted weak EPC strength, λ, supporting an unconventional pairing mechanism in CsV₃Sb₅. However, experimental determination of λ is still missing, hindering a microscopic understanding of the intertwined ground state of CsV₃Sb₅. Here, using 7-eV laser-based angle-resolved photoemission spectroscopy and Eliashberg function analysis, we determine an intermediate λ=0.45-0.6 at T = 6 K for both Sb 5p and V 3d electronic bands, which can support a conventional superconducting transition temperature on the same magnitude of experimental value in CsV₃Sb₅. Remarkably, the EPC on the V 3d-band enhances to λ~0.75 as the superconducting transition temperature elevated to 4.4 K in Cs(V_0.93Nb_0.07)₃Sb₅. Our results provide an important clue to understand the pairing mechanism in the kagome superconductor CsV₃Sb₅.

Zwitterionic Bergman cyclization triggered polymerization gives access to metal-graphene nanoribbons using a boron metal couple

With the rapid growth in artificial intelligence, designing high-speed and low-power semiconducting materials is of utmost importance. This investigation provides a theoretical basis to access covalently bonded transition metal-graphene nanoribbon (TM-GNR) hybrid semiconductors whose DFT-computed bandgaps were much narrower than the commonly used pentacene. Systematic optimization of substrates containing remotely placed boryl groups and the transition metals produced the zwitterions via ionic Bergman cyclization (i-BC) and unlocked the polymerization of metal-substituted polyenynes. Aside from i-BC, the subsequent steps were barrierless, which involved structureless transition regions. Multivariate analysis revealed the strong dependence of activation energy and the cyclization mode on the electronic nature of boron and Au(I). Consequently, three regions corresponding to radical Bergman (r-BC), ionic Bergman (i-BC), and ionic Schreiner-Pascal (i-SP) cyclizations were identified. The boundaries between these regions corresponded to the mechanistic shift induced by the three-center-three-electron (3c-3e) hydrogen bond, three-center-four-electron (3c-4e) hydrogen bond, and vacant p-orbital on boron. The ideal combination for cascade polymerization was observed near the boundary between i-BC and i-SP.

State-Specific Configuration Interaction for Excited States

We introduce and benchmark a systematically improvable route for excited-state calculations, labeled state-specific configuration interaction (ΔCI), which is a particular realization of multiconfigurational self-consistent field and multireference configuration interaction. Starting with a reference built from optimized configuration state functions, separate CI calculations are performed for each targeted state (hence, state-specific orbitals and determinants). Accounting for single and double excitations produces the ΔCISD model, which can be improved with second-order Epstein-Nesbet perturbation theory (ΔCISD+EN2) or a posteriori Davidson corrections (ΔCISD+Q). These models were gauged against a vast and diverse set of 294 reference excitation energies. We have found that ΔCI is significantly more accurate than standard ground-state-based CI, whereas close performances were found between ΔCISD and EOM-CC2 and between ΔCISD+EN2 and EOM-CCSD. For larger systems, ΔCISD+Q delivers more accurate results than EOM-CC2 and EOM-CCSD. The ΔCI route can handle challenging multireference problems, singly and doubly excited states, from closed- and open-shell species, with overall comparable accuracy and thus represents a promising alternative to more established methodologies. In its current form, however, it is reliable only for relatively low-lying excited states.

On good encodings for quantum annealer and digital optimization solvers

Several optimization solvers inspired by quantum annealing have been recently developed, either running on actual quantum hardware or simulating it on traditional digital computers. Industry and academics look at their potential in solving hard combinatorial optimization problems. Formally, they provide heuristic solutions for Ising models, which are equivalent to quadratic unconstrained binary optimization (QUBO). Constraints on solutions feasibility need to be properly encoded. We experiment on different ways of performing such an encoding. As benchmark we consider the cardinality constrained quadratic knapsack problem (CQKP), a minimal extension of QUBO with one inequality and one equality constraint. We consider different strategies of constraints penalization and variables encoding. We compare three QUBO solvers: quantum annealing on quantum hardware (D-Wave Advantage), probabilistic algorithms on digital hardware and mathematical programming solvers. We analyze their QUBO resolution quality and time, and the persistence values extracted in the quantum annealing sampling process. Our results show that a linear penalization of CQKP inequality improves current best practice. Furthermore, using such a linear penalization, persistence values produced by quantum hardware in a generic way allow to match a specific CQKP metric from literature. They are therefore suitable for general purpose variable fixing in core algorithms for combinatorial optimization.

Active layer dynamics drives a transition to biofilm fingering

The emergence of spatial organisation in biofilm growth is one of the most fundamental topics in biofilm biophysics and microbiology. It has long been known that growing biofilms can adopt smooth or rough interface morphologies, depending on the balance between nutrient supply and microbial growth; this 'fingering' transition has been linked with the average width of the 'active layer' of growing cells at the biofilm interface. Here we use long-time individual-based simulations of growing biofilms to investigate in detail the driving factors behind the biofilm-fingering transition. We show that the transition is associated with dynamical changes in the active layer. Fingering happens when gaps form in the active layer, which can cause local parts of the biofilm interface to pin, or become stationary relative to the moving front. Pinning can be transient or permanent, leading to different biofilm morphologies. By constructing a phase diagram for the transition, we show that the controlling factor is the magnitude of the relative fluctuations in the active layer thickness, rather than the active layer thickness per se. Taken together, our work suggests a central role for active layer dynamics in controlling the pinning of the biofilm interface and hence biofilm morphology.

Quantum-resistance in blockchain networks

The advent of quantum computing threatens blockchain protocols and networks because they utilize non-quantum resistant cryptographic algorithms. When quantum computers become robust enough to run Shor's algorithm on a large scale, the most used asymmetric algorithms, utilized for digital signatures and message encryption, such as RSA, (EC)DSA, and (EC)DH, will be no longer secure. Quantum computers will be able to break them within a short period of time. Similarly, Grover's algorithm concedes a quadratic advantage for mining blocks in certain consensus protocols such as proof of work. Today, there are hundreds of billions of dollars denominated in cryptocurrencies and other digital assets that rely on blockchain ledgers as well as thousands of blockchain-based applications storing value in blockchain networks. Cryptocurrencies and blockchain-based applications require solutions that guarantee quantum resistance in order to preserve the integrity of data and assets in these public and immutable ledgers. The quantum threat and some potential solutions are well understood and presented in the literature. However, most proposals are theoretical, require large QKD networks, or propose new quantum-resistant blockchain networks to be built from scratch. Our work, which is presented in this paper, is pioneer in proposing an end-to-end framework for post-quantum blockchain networks that can be applied to existing blockchain to achieve quantum-resistance. We have developed an open-source implementation in an Ethereum-based (i.e., EVM compatible) network that can be extended to other existing blockchains. For the implementation we have (i) used quantum entropy to generate post-quantum key pairs, (ii) established post-quantum TLS connections and X.509 certificates to secure the exchange of information between blockchain nodes over the internet without needing a large QKD network, (iii) introduced a post-quantum second signature in transactions using Falcon-512 post-quantum keys, and (iv) developed the first on-chain verification of post-quantum signatures using three different mechanisms that are compared and analyzed: Solidity smart-contracts run by the validators for each transaction, modified EVM Opcode, and precompiled smart contracts.

Survival strategies of artificial active agents

Artificial cells can be engineered to display dynamics sharing remarkable features in common with the survival behavior of living organisms. In particular, such active systems can respond to stimuli provided by the environment and undertake specific displacements to remain out of equilibrium, e.g. by moving towards regions with higher fuel concentration. In spite of the intense experimental activity aiming at investigating this fascinating behavior, a rigorous definition and characterization of such "survival strategies" from a statistical physics perspective is still missing. In this work, we take a first step in this direction by adapting and applying to active systems the theoretical framework of Transition Path Theory, which was originally introduced to investigate rare thermally activated transitions in passive systems. We perform experiments on camphor disks navigating Petri dishes and perform simulations in the paradigmatic active Brownian particle model to show how the notions of transition probability density and committor function provide the pivotal concepts to identify survival strategies, improve modeling, and obtain and validate experimentally testable predictions. The definition of survival in these artificial systems paves the way to move beyond simple observation and to formally characterize, design and predict complex life-like behaviors.

Encounter rates prime interactions between microorganisms

Properties of microbial communities emerge from the interactions between microorganisms and between microorganisms and their environment. At the scale of the organisms, microbial interactions are multi-step processes that are initiated by cell-cell or cell-resource encounters. Quantification and rational design of microbial interactions thus require quantification of encounter rates. Encounter rates can often be quantified through encounter kernels-mathematical formulae that capture the dependence of encounter rates on cell phenotypes, such as cell size, shape, density or motility, and environmental conditions, such as turbulence intensity or viscosity. While encounter kernels have been studied for over a century, they are often not sufficiently considered in descriptions of microbial populations. Furthermore, formulae for kernels are known only in a small number of canonical encounter scenarios. Yet, encounter kernels can guide experimental efforts to control microbial interactions by elucidating how encounter rates depend on key phenotypic and environmental variables. Encounter kernels also provide physically grounded estimates for parameters that are used in ecological models of microbial populations. We illustrate this encounter-oriented perspective on microbial interactions by reviewing traditional and recently identified kernels describing encounters between microorganisms and between microorganisms and resources in aquatic systems.

Double-transmembrane domain of SNAREs decelerates the fusion by increasing the protein-lipid mismatch

SNARE is the essential mediator of membrane fusion that highly relies on the molecular structure of SNAREs. For instance, the protein syntaxin-1 involved in neuronal SNAREs, has a single transmembrane domain (sTMD) leading to fast fusion, while the syntaxin 17 has a V-shape double TMDs (dTMDs), taking part in the autophagosome maturation. However, it is not clear how the TMD structure influences the fusion process. Here, we demonstrate that the dTMDs significantly reduce fusion rate compared with the sTMD by using an in vitro reconstitution system. Through theoretical analysis, we reveal that the V-shape dTMDs can significantly increase protein-lipid mismatch, thereby raising the energy barrier of the fusion, and that increasing the number of SNAREs can reduce the energy barrier or protein-lipid mismatch. This study provides a physicochemical mechanistic understanding of SNARE-regulated membrane fusion.

Atomistic nonlinear carrier dynamics in Ge

An atomistic technique to successfully demonstrate the ultrafast carrier dynamics in Ge photoconductive samples is reported here. The technique is validated against the experimental findings and with the Drude conductivities. The impact of the various different scattering mechanisms is used to calibrate the experimental results. It is observed that the total scattering rate is not a constant parameter as contrast to Drude model which uses constant scattering rate as the fitting parameter to demonstrate the ultrafast carrier dynamics, but strongly dependent on the applied peak THz field strength. It also contradicts with the relaxation time approximation (RTA) method which uses scattering rate chosen on the empirical basis as the fitting parameter to demonstrate the ultrafast carrier dynamics. On the other hand the limitations and challenges offered by various types of density functional theories (DFT) pose lot of challenges. In current manuscript various types of scattering mechanisms i.e. acoustic, intervalley, Coulomb and impact ionization on the behavior of carrier conductivity are studied in details. The proposed technique has shown capability to extract low and high frequency conductivities accurately which is impossible through the Drude model or DFT based theories. It is observed that the free carrier absorption coefficient depends on the refractive index of the material at low THz frequencies. The solution of Boltzmann transport equation through Monte Carlo technique provides valuable insights for better understanding of ultrafast carrier transportation mechanism. The free carrier absorption spectra are found to be in good agreement with the experimental results at various THz field strengths.

Calculation of Excited State Internal Conversion Rate Constant Using the One-Effective Mode Marcus-Jortner-Levich Theory

In this article, the one-effective mode Marcus-Jortner-Levich (MJL) theory and the classical Marcus theory for electron transfer were applied to estimate the internal conversion rate constant, k_IC, of organic molecules and a Ru-based complex, all belonging to the Marcus inverted region. For this, the reorganization energy was calculated using the minimum energy conical intersection point to account for more vibrational levels, correcting the density of states. The results showed good agreement with experimental and theoretically determined k_IC, with a small overestimation by the Marcus theory. Also, molecules less dependent on the solvent effects, like benzophenone, presented better results than molecules with an expressive dependence, like 1-aminonaphthalene. Moreover, the results suggest that each molecule possesses unique normal modes leading to the excited state deactivation that does not necessarily match the X-H bond stretching, as previously suggested.

Ultrasound-Responsive Biomimetic Superhydrophobic Drug-Loaded Mesoporous Silica Nanoparticles for Treating Prostate Tumor

Interfacial nanobubbles on a superhydrophobic surface can serve as ultrasound cavitation nuclei for continuously promoting sonodynamic therapy, but their poor dispersibility in blood has limited their biomedical application. In this study, we proposed ultrasound-responsive biomimetic superhydrophobic mesoporous silica nanoparticles, modified with red blood cell membrane and loaded with doxorubicin (DOX) (F-MSN-DOX@RBC), for RM-1 tumor sonodynamic therapy. Their mean size and zeta potentials were 232 ± 78.8 nm and −35.57 ± 0.74 mV, respectively. The F-MSN-DOX@RBC accumulation in a tumor was significantly higher than in the control group, and the spleen uptake of F-MSN-DOX@RBC was significantly reduced in comparison to that of the F-MSN-DOX group. Moreover, the cavitation caused by a single dose of F-MSN-DOX@RBC combined with multiple ultrasounds provided continuous sonodynamic therapy. The tumor inhibition rates in the experimental group were 71.5 8 ± 9.54%, which is significantly better than the control group. DHE and CD31 fluorescence staining was used to assess the reactive oxygen species (ROS) generated and the broken tumor vascular system induced by ultrasound. Finally, we can conclude that the combination of anti-vascular therapy, sonodynamic therapy by ROS, and chemotherapy promoted tumor treatment efficacy. The use of red blood cell membrane-modified superhydrophobic silica nanoparticles is a promising strategy in designing ultrasound-responsive nanoparticles to promote drug-release.

Modern Manufacturing Enables Magnetic Field Cycling Experiments and Parahydrogen-Induced Hyperpolarization with a Benchtop NMR

Benchtop NMR (btNMR) spectrometers are revolutionizing the way we use NMR and lowering the cost drastically. Magnetic field cycling (MFC) experiments with precise timing and control over the magnetic field, however, were hitherto not available on btNMRs, although some systems exist for high-field, high-resolution NMR spectrometers. Still, the need and potential for btNMR MFC is great─e.g., to perform and analyze parahydrogen-induced hyperpolarization, another method that has affected analytical chemistry and NMR beyond expectations. Here, we describe a setup that enables MFC on btNMRs for chemical analysis and hyperpolarization. Taking full advantage of the power of modern manufacturing, including computer-aided design, three-dimensional printing, and microcontrollers, the setup is easy to reproduce, highly reliable, and easy to adjust and operate. Within 380 ms, the NMR tube was shuttled reliably from the electromagnet to the NMR isocenter (using a stepper motor and gear rod). We demonstrated the power of this setup by hyperpolarizing nicotinamide using signal amplification by reversible exchange (SABRE), a versatile method to hyperpolarize a broad variety of molecules including metabolites and drugs. Here, the standard deviation of SABRE hyperpolarization was between 0.2 and 3.3%. The setup also allowed us to investigate the field dependency of the polarization and the effect of different sample preparation protocols. We found that redissolution of the activated and dried Ir catalyst always reduced the polarization. We anticipate that this design will greatly accelerate the ascension of MFC experiments for chemical analysis with btNMR─adding yet another application to this rapidly developing field.

A quantum spin liquid candidate isolated in a two-dimensional CoIIRhIII bimetallic oxalate network

A quantum spin liquid (QSL) is an elusive state of matter characterized by the absence of long-range magnetic order, even at zero temperature, and by the presence of exotic quasiparticle excitations. In spite of their relevance for quantum communication, topological quantum computation and the understanding of strongly correlated systems, like high-temperature superconductors, the unequivocal experimental identification of materials behaving as QSLs remains challenging. Here, we present a novel 2D heterometallic oxalate complex formed by high-spin Co(ii) ions alternating with diamagnetic Rh(iii) in a honeycomb lattice. This complex meets the key requirements to become a QSL: a spin ½ ground state for Co(ii), determined by spin-orbit coupling and crystal field, a magnetically-frustrated triangular lattice due to the presence of antiferromagnetic correlations, strongly suppressed direct exchange interactions and the presence of equivalent interfering superexchange paths between Co centres. A combination of electronic paramagnetic resonance, specific heat and ac magnetic susceptibility measurements in a wide range of frequencies and temperatures shows the presence of strong antiferromagnetic correlations concomitant with no signs of magnetic ordering down to 15 mK. These results show that bimetallic oxalates are appealing QSL candidates as well as versatile systems to chemically fine tune key aspects of a QSL, like magnetic frustration and superexchange path geometries.

Extreme Enhanced Curie Temperature and Perpendicular Exchange Bias in Freestanding Ferromagnetic Superlattices

Most recently, the freestanding of an epitaxial single-crystal oxide has been greatly developed to its fundamental concerns and the possibility of integration with metal, two-dimensional, and organic materials for more promising functionalities. In an artificial ferromagnetic oxide heterostructure and superlattice, the release of the substrate constraint can induce a reasonable transformation of the magnetic structure because the change of the lattice field occurs. In this study, we have comprehensively investigated the evolution of magnetic properties of (La_0.7Ca_0.3MnO₃/SrRuO₃)_n [(LCMO/SRO)_n] ferromagnetic superlattices while they are epitaxially on SrTiO₃ and freestanding. It is found that the Curie temperature and the perpendicular exchange bias of the freestanding superlattices exhibit extreme sensitivity to the interface number and the thickness of LCMO and SRO, which can maximumly reach ∼293 K and ∼1150 Oe. These enhanced and bulk-beyond magnetic behaviors originate from the interfacial magnetic transition from ferromagnetic to antiferromagnetic via the charge reconstruction with the assistance of strain. Our study provides not only a reference for designing a high-performance flexible ferromagnetic architectural superlattice but also a deep understanding of the interfacial effect in freestanding ferromagnetic heterostructures benefiting flexible spintronics.

The role of nonequilibrium LO phonons, Pauli exclusion, and intervalley pathways on the relaxation of hot carriers in InGaAs/InGaAsP multi-quantum-wells

Under continuous-wave laser excitation in a lattice-matched In_0.53Ga_0.47As/In_0.8Ga_0.2As_0.44P_0.56 multi-quantum-well (MQW) structure, the carrier temperature extracted from photoluminescence rises faster for 405 nm compared with 980 nm excitation, as the injected carrier density increases. Ensemble Monte Carlo simulation of the carrier dynamics in the MQW system shows that this carrier temperature rise is dominated by nonequilibrium LO phonon effects, with the Pauli exclusion having a significant effect at high carrier densities. Further, we find a significant fraction of carriers reside in the satellite L-valleys for 405 nm excitation due to strong intervalley transfer, leading to a cooler steady-state electron temperature in the central valley compared with the case when intervalley transfer is excluded from the model. Good agreement between experiment and simulation has been shown, and detailed analysis has been presented. This study expands our knowledge of the dynamics of the hot carrier population in semiconductors, which can be applied to further limit energy loss in solar cells.

A new phase model of the spatiotemporal relationships between three circadian oscillators in the brainstem

Analysis of ex vivo Per2 bioluminescent rhythm previously recorded in the mouse dorsal vagal complex reveals a characteristic phase relationship between three distinct circadian oscillators. These signals represent core clock gene expression in the area postrema (AP), the nucleus of the solitary tract (NTS) and the ependymal cells surrounding the 4th ventricle (4Vep). Initially, the data suggests a consistent phasing in which the AP peaks first, followed shortly by the NTS, with the 4Vep peaking 8-9 h later. Wavelet analysis reveals that this pattern is not consistently maintained throughout a recording, however, the phase dynamics strongly imply that oscillator interactions are present. A simple phase model of the three oscillators is developed and it suggests that realistic phase dynamics occur between three model oscillators with coupling close to a synchronisation transition. The coupling topology suggests that the AP bidirectionally communicates phase information to the NTS and the 4Vep to synchronise the three structures. A comparison of the model with previous experimental manipulations demonstrates its feasibility to explain DVC circadian phasing. Finally, we show that simulating steadily decaying coupling improves the model's ability to capture experimental phase dynamics.

The fractal brain: scale-invariance in structure and dynamics

The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

A machine learning approach to discover migration modes and transition dynamics of heterogeneous dendritic cells

Dendritic cell (DC) migration is crucial for mounting immune responses. Immature DCs (imDCs) reportedly sense infections, while mature DCs (mDCs) move quickly to lymph nodes to deliver antigens to T cells. However, their highly heterogeneous and complex innate motility remains elusive. Here, we used an unsupervised machine learning (ML) approach to analyze long-term, two-dimensional migration trajectories of Granulocyte-macrophage colony-stimulating factor (GMCSF)-derived bone marrow-derived DCs (BMDCs). We discovered three migratory modes independent of the cell state: slow-diffusive (SD), slow-persistent (SP), and fast-persistent (FP). Remarkably, imDCs more frequently changed their modes, predominantly following a unicyclic SD→FP→SP→SD transition, whereas mDCs showed no transition directionality. We report that DC migration exhibits a history-dependent mode transition and maturation-dependent motility changes are emergent properties of the dynamic switching of the three migratory modes. Our ML-based investigation provides new insights into studying complex cellular migratory behavior.

The nonlinearity of regulation in biological networks

The extent to which the components of a biological system are (non)linearly regulated determines how amenable they are to therapy and control. To better understand this property termed "regulatory nonlinearity", we analyzed a suite of 137 published Boolean network models, containing a variety of complex nonlinear regulatory interactions, using a probabilistic generalization of Boolean logic that George Boole himself had proposed. Leveraging the continuous-nature of this formulation, we used Taylor decomposition to approximate the models with various levels of regulatory nonlinearity. A comparison of the resulting series of approximations of the biological models with appropriate random ensembles revealed that biological regulation tends to be less nonlinear than expected, meaning that higher-order interactions among the regulatory inputs tend to be less pronounced. A further categorical analysis of the biological models revealed that the regulatory nonlinearity of cancer and disease networks could not only be sometimes higher than expected but also be relatively more variable. We show that this variation is caused by differences in the apportioning of information among the various orders of regulatory nonlinearity. Our results suggest that there may have been a weak but discernible selection pressure for biological systems to evolve linear regulation on average, but for certain systems such as cancer, on the other hand, to simultaneously evolve more nonlinear rules.

Signature of spin-triplet exciton condensations in LaCoO3 at ultrahigh magnetic fields up to 600 T

Bose-Einstein condensation of electron-hole pairs, exciton condensation, has been effortfully investigated since predicted 60 years ago. Irrefutable evidence has still been lacking due to experimental difficulties in verifying the condensation of the charge neutral and non-magnetic spin-singlet excitons. Whilst, condensation of spin-triplet excitons is a promising frontier because spin supercurrent and spin-Seebeck effects will be observable. A canonical cobaltite LaCoO₃ under very high magnetic fields is a propitious candidate, yet to be verified. Here, we unveil the exotic phase diagram of LaCoO₃ up to 600 T generated using the electromagnetic flux compression method and the state-of-the-art magnetostriction gauge. We found the continuous magnetostriction curves and a bending structure, which suggest the emergence of two distinct spin-triplet exciton condensates. By constructing a phenomenological model, we showed that quantum fluctuations of excitons are crucial for the field-induced successive transitions. The spin-triplet exciton condensation in a cobaltite, which is three-dimensional and thermally equilibrated, opens up a novel venue for spintronics technologies with spin-supercurrent such as a spin Josephson junction.

Predictive coding across the left fronto-temporal hierarchy during language comprehension

We used magnetoencephalography (MEG) and event-related potentials (ERPs) to track the time-course and localization of evoked activity produced by expected, unexpected plausible, and implausible words during incremental language comprehension. We suggest that the full pattern of results can be explained within a hierarchical predictive coding framework in which increased evoked activity reflects the activation of residual information that was not already represented at a given level of the fronto-temporal hierarchy ("error" activity). Between 300 and 500 ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), whereas implausible inputs produced a selectively enhanced response within inferior frontal cortex (prediction error at the level of the event model). Between 600 and 1,000 ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that produced top-down error), whereas highly implausible inputs activated left inferior frontal cortex, posterior fusiform (unsuppressed orthographic prediction error/reprocessing), and medial temporal cortex (possibly supporting new learning). Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.

Attosecond Monitoring of Nonadiabatic Molecular Dynamics by Transient X-ray Transmission Spectroscopy

Tracing the evolution of molecular coherences can provide a direct, unambiguous probe of nonadiabatic molecular processes, such as the passage through conical intersections of electronic states. Two techniques, attosecond transient absorption spectroscopy (ATAS) and Transient Redistribution of Ultrafast Electronic Coherences in Attosecond Raman Signals (TRUECARS), have been used or proposed for monitoring nonadiabatic molecular dynamics. Both techniques employ the transmission of a weak attosecond extreme-ultraviolet or X-ray probe to interrogate the molecule at controllable time delays with respect to an optical pump, thereby extracting dynamical information from transient spectral features. The connection between these techniques has not been firmly established yet. In this theoretical study, we provide a unified description of both transient transmission techniques, establishing their relationship as limits of the same pump-probe spectroscopy technique for different pulse parameter regimes. We demonstrate this by quantum dynamical simulations of thiophenol photodissociation and show how complementary coherence information can be revealed by the two techniques.

Investigation of Dynamic Behavior of Confined Ionic Liquid [BMIM]+[TCM]- in Silica Material SBA-15 Using NMR

The molecular dynamics of 1-butyl-3-methyl imidazolium tricyanomethanide ionic liquid [BMIM]+[TCM]- confined in SBA-15 mesoporous silica were examined using 1H NMR spin-lattice (T1) relaxation and diffusion measurements. An extensive temperature range (100 K-400 K) was considered in order to study both the liquid and glassy states. The hydrogen dynamics in the two states and the self-diffusion coefficients of the cation [BMIM]+ above the glass transition temperature were extracted from the experimental data. The results were then compared to the corresponding bulk substance. The effects of confinement on the dynamic properties of the ionic liquid clearly manifest themselves in both temperature regimes. In the high-temperature liquid state, the mobility of the confined cations reduces significantly compared to the bulk; interestingly, confinement drives the ionic liquid to the glassy state at a higher temperature Tg than the bulk ionic liquid, whereas an unusual T1 temperature dependence is observed in the high-temperature regime, assigned to the interaction of the ionic liquid with the silica-OH species.

Characterizing quantum circuits with qubit functional configurations

We develop a systematic framework for characterizing all quantum circuits with qubit functional configurations. The qubit functional configuration is a mathematical structure that can classify the properties and behaviors of quantum circuits collectively. Major benefits of classifying quantum circuits in this way include: 1. All quantum circuits can be classified into corresponding types; 2. Each type characterizes important properties (such as circuit complexity) of the quantum circuits belonging to it; 3. Each type contains a huge collection of possible quantum circuits allowing systematic investigation of their common properties. We demonstrate the theory's application to analyzing the hardware-efficient ansatzes of variational quantum algorithms. For potential applications, the functional configuration theory may allow systematic understanding and development of quantum algorithms based on their functional configuration types.

Rashba effect on finite temperature magnetotransport in a dissipative quantum dot transistor with electronic and polaronic interactions

The Rashba spin-orbit coupling induced quantum transport through a quantum dot embedded in a two-arm quantum loop of a quantum dot transistor is studied at finite temperature in the presence of electron-phonon and Hubbard interactions, an external magnetic field and quantum dissipation. The Anderson-Holstein-Caldeira-Leggett-Rashba model is used to describe the system and several unitary transformations are employed to decouple some of the interactions and the transport properties are calculated using the Keldysh technique. It is shown that the Rashba coupling alone separates the spin-up and spin-down currents causing zero-field spin-polarization. The gap between the up and down-spin currents and conductances can be changed by tuning the Rashba strength. In the absence of a field, the spin-up and spin-down currents show an opposite behaviour with respect to spin-orbit interaction phase. The spin-polarization increases with increasing electron-phonon interaction at zero magnetic field. In the presence of a magnetic field, the tunneling conductance and spin-polarization change differently with the polaronic interaction, spin-orbit interaction and dissipation in different temperature regimes. This study predicts that for a given Rashba strength and magnetic field, the maximum spin-polarization in a quantum dot based device occurs at zero temperature.

Light-driven peristaltic pumping by an actuating splay-bend strip

Despite spectacular progress in microfluidics, small-scale liquid manipulation, with few exceptions, is still driven by external pumps and controlled by large-scale valves, increasing cost and size and limiting complexity. By contrast, optofluidics uses light to power, control and monitor liquid manipulation, potentially allowing for small, self-contained microfluidic devices. Here we demonstrate a soft light-propelled actuator made of liquid crystal gel that pumps microlitre volumes of water. The strip of actuating material serves as both a pump and a channel leading to an extremely simple microfluidic architecture that is both powered and controlled by light. The performance of the pump is well explained by a simple theoretical model in which the light-induced bending of the actuator competes with the liquid's surface tension. The theory highlights that effective pumping requires a threshold light intensity and strip width. The proposed system explores the benefits of shifting the complexity of microfluidic systems from the fabricated device to spatio-temporal control over stimulating light patterns.

Heavy tails and pruning in programmable photonic circuits for universal unitaries

Developing hardware for high-dimensional unitary operators plays a vital role in implementing quantum computations and deep learning accelerations. Programmable photonic circuits are singularly promising candidates for universal unitaries owing to intrinsic unitarity, ultrafast tunability and energy efficiency of photonic platforms. Nonetheless, when the scale of a photonic circuit increases, the effects of noise on the fidelity of quantum operators and deep learning weight matrices become more severe. Here we demonstrate a nontrivial stochastic nature of large-scale programmable photonic circuits-heavy-tailed distributions of rotation operators-that enables the development of high-fidelity universal unitaries through designed pruning of superfluous rotations. The power law and the Pareto principle for the conventional architecture of programmable photonic circuits are revealed with the presence of hub phase shifters, allowing for the application of network pruning to the design of photonic hardware. For the Clements design of programmable photonic circuits, we extract a universal architecture for pruning random unitary matrices and prove that "the bad is sometimes better to be removed" to achieve high fidelity and energy efficiency. This result lowers the hurdle for high fidelity in large-scale quantum computing and photonic deep learning accelerators.

Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.

Towards the ground state of molecules via diffusion Monte Carlo on neural networks

Diffusion Monte Carlo (DMC) based on fixed-node approximation has enjoyed significant developments in the past decades and become one of the go-to methods when accurate ground state energy of molecules and materials is needed. However, the inaccurate nodal structure hinders the application of DMC for more challenging electronic correlation problems. In this work, we apply the neural-network based trial wavefunction in fixed-node DMC, which allows accurate calculations of a broad range of atomic and molecular systems of different electronic characteristics. Our method is superior in both accuracy and efficiency compared to state-of-the-art neural network methods using variational Monte Carlo (VMC). We also introduce an extrapolation scheme based on the empirical linearity between VMC and DMC energies, and significantly improve our binding energy calculation. Overall, this computational framework provides a benchmark for accurate solutions of correlated electronic wavefunction and also sheds light on the chemical understanding of molecules.

Current-driven writing process in antiferromagnetic Mn2Au for memory applications

Current pulse driven Néel vector rotation in metallic antiferromagnets is one of the most promising concepts in antiferromagnetic spintronics. We show microscopically that the Néel vector of epitaxial thin films of the prototypical compound Mn₂Au can be reoriented reversibly in the complete area of cross shaped device structures using single current pulses. The resulting domain pattern with aligned staggered magnetization is long term stable enabling memory applications. We achieve this switching with low heating of ≈20 K, which is promising regarding fast and efficient devices without the need for thermal activation. Current polarity dependent reversible domain wall motion demonstrates a Néel spin-orbit torque acting on the domain walls.

A practical guide to pulsed laser deposition

Nanoscale thin films are widely implemented across a plethora of technological and scientific areas, and form the basis for many advancements that have driven human progress, owing to the high degree of functional tunability based on the chemical composition. Pulsed laser deposition is one of the multiple physical vapour deposition routes to fabricate thin films, employing laser energy to eject material from a target in the form of a plasma. A substrate, commonly a single-crystal oxide, is placed in the path of the plume and acts as a template for the arriving species from the target to coalesce and self-assemble into a thin film. This technique is tremendously useful to produce crystalline films, due to the wide range of atmospheric conditions and the extent of possible chemical complexity of the target. However, this flexibility results in a high degree of complexity, oftentimes requiring rigorous optimisation of the growth parameters to achieve high quality crystalline films with desired composition. In this tutorial review, we aim to reduce the complexity and the barrier to entry for the controlled growth of complex oxides by pulsed laser deposition. We present an overview of the fundamental and practical aspects of pulsed laser deposition, discuss the consequences of tailoring the growth parameters on the thin film properties, and describe in situ monitoring techniques that are useful in gaining a deeper understanding of the properties of the resultant films. Particular emphasis is placed on the general relationships between the growth parameters and the consequent structural, chemical and functional properties of the thin films. In the final section, we discuss the open questions within the field and possible directions to further expand the utility of pulsed laser deposition.