Copper-based metal-organic frameworks (Cu-MOFs) offer several benefits, including routes for ion diffusion and adsorption sites for ions from the electrolyte, owing to their large surface area, porosity, structural configurations, and composition. Recent advancements in this area highlight the potential to achieve high energy and power densities, improved cycle stability, and enhanced energy-storage capabilities in high-performance supercapacitors (SCs) using Cu-MOFs and their composites. Selecting appropriate metal ions and organic ligands for the MOFs enables tailoring of their conductivity, redox properties, surface area, functionality, stability, and porosity. Several approaches can be used to improve their electrochemical performance by synthesizing derivatives and composites incorporating metal oxides, chalcogenides, carbon, and conducting polymers. This review highlights recent advances in Cu-MOFs as potential SC electrodes and examines their structures, electrochemical processes, and potential for hybrid SCs. The review outlines key strategies to improve the electrochemical performance of Cu-based electrodes, including structural modification, compositional optimization, and composite design. While MOFs show substantial promise, challenges remain regarding economic feasibility, complex synthesis processes, scalability, and cyclic stability, all of which are summarized. Finally, it identifies current challenges and offers insights into the future development of Cu-based MOFs for SCs.
Partially coherent vortex fields combine optical singularities with controllable statistical correlations, forming an important research platform at the intersection of singular optics, statistical optics, and structured-light science. Since the publication of the 2019 review on vortex beams with low spatial coherence, the field has witnessed substantial advances. In particular, coherence has evolved from a statistical parameter that modifies vortex beams into a designable degree of freedom for engineering structured optical fields through tailored correlation functions. By manipulating second-order correlation structures, coherence engineering enables the generation of multidimensional optical states, the control of propagation dynamics, and the realization of functionalities beyond conventional field engineering approaches. This review summarizes major developments since 2019, highlighting progress in source engineering, coherence-controlled propagation physics, intelligent metrology, and emerging applications. Particular attention is given to correlation-engineered fields, robustness and angular-momentum transport in complex environments, machine-learning-assisted characterization, and applications in optical manipulation, communications, information security, imaging, and sensing. We further discuss emerging directions including multidimensional coherence engineering, coherence topology, spatiotemporal structured light, and intelligent photonics. These developments suggest that the field is undergoing a transition from field engineering toward correlation engineering, in which tailored correlation structures are becoming fundamental resources for controlling optical fields, information, and topology.
Surfaces and interfaces break the translational symmetry of a crystal lattice, giving rise to electronic and structural states that can differ dramatically from those of the bulk. These surface-specific states, often originating from unsaturated bonds, reconstructions, or reduced dimensionality, govern key aspects of chemical reactivity and device functionality. Low-dimensional and, in particular, 2D materials represent the most extreme case, where strong interactions and correlations can stabilize superconductivity or charge- and spin-density-wave phases. A microscopic understanding of the elementary processes that underlie such phenomena requires experimental access to their intrinsic dynamics on relevant time and length scales. To this end, an array of advanced techniques has been developed, providing direct insight into ultrafast dynamics in both the electronic and structural subsystems. Among these, time-resolved electron diffraction is uniquely suited to capture laser-induced atomic displacements, with dedicated implementations optimized for surface sensitivity. This review highlights recent advances in ultrafast surface-sensitive electron diffraction, tracing the methodological developments and showcasing applications to selected material systems. Particular attention is given to prototypical surface phenomena including charge-density-wave phase transitions, nanoscale heat transfer, and non-thermal phonon dynamics.
Photonic alloys (PAs) are artificial photonic materials inspired by condensed-matter alloying, where mixed constituents tailor electromagnetic dispersion beyond conventional photonic crystals. Initially introduced as random mixtures of plasmonic and polaritonic microspheres, PAs evolved through digital-alloy implementations enabling deterministic band-structure control via short-period superlattices. Recently, topological photonic alloys (TPAs) have emerged, exploiting disorder and non-periodicity to realize robust chiral edge states and nontrivial bandgaps at vanishing topological constituent concentrations. This review unifies the development of PAs from early random and digital realizations to contemporary topological implementations. We discuss physical mechanisms, theoretical frameworks, and experimental realizations across dimensionalities and platforms, highlighting disorder, band alignment, and effective-medium concepts. Finally, we outline future directions including disorder-resilient topological photonics, programmable metamaterials, and semiconductor-compatible topological devices.
The origins of quantum theory are intimately connected to thermodynamics. In addressing the problem of blackbody radiation, Max Planck introduced the hypothesis of energy quantization, thereby establishing the foundations of quantum physics. This review revisits the deep conceptual links between quantum theory and the thermodynamics of small systems, where classical thermodynamic assumptions—particularly extensivity and additivity—break down. Particular emphasis is placed on the role of the subdivision potential in accounting for non-extensive contributions and on Tsallis entropy as a generalized framework capable of capturing the intrinsic non-extensivity of finite and strongly correlated systems, thereby extending thermodynamic reasoning beyond the macroscopic limit.
The construction of large quantum beam facilities such as synchrotron radiation and high-intensity proton accelerator facilities has provided access to high-intensity, high-energy quantum beams that are indispensable for the structural analyses of disordered materials via diffraction measurements. By the complementary use of X-rays, which are sensitive to heavy elements, and neutrons, which are sensitive to light elements, along with the advances in computer simulations and topological analysis techniques, we have achieved a deep understanding of the intermediate-range structure of disordered materials. In this review, we introduce the recent results obtained by the complementary use of X-ray and neutron diffraction. In particular, we discuss the differences among tetrahedrally coordinated disordered materials in comparison with dense random packing metallic glass to understand the origin of the three-peak structure, the first sharp diffraction peak (FSDP, Q 1), principal peak (PP, Q 2), and Q 3 observed in quantum beam diffraction data. Moreover, we demonstrate that comparing persistent homology analysis data with the ring size distributions of silica (SiO2) glass and crystals is important for understanding the low-energy excitations observed in inelastic neutron scattering data.
Perovskite oxides ([Formula: see text]O[Formula: see text]) have long been central to the advancement of modern condensed matter physics, owing to their rich and tunable electronic and magnetic properties. The quest to understand their various entangled phases has spurred the development of both cutting-edge experimental tools and innovative theoretical frameworks. In recent times, the emergence of high entropy oxides - materials in which five or more elements share a single crystallographic site - has introduced a powerful new paradigm in materials design. Embedding such extreme chemical disorder within the perovskite framework has opened vast opportunities for realizing novel physical phenomena inaccessible in conventional oxides. This review surveys the rapid advances in the synthesis, characterisation, and exploration of the electronic and magnetic properties of compositionally complex perovskite oxides, offering key insights and highlighting promising avenues for future research.
Contemporary complex systems research faces a structural imbalance between the abundance of high-dimensional network data and our limited capacity to model or interpret the resulting dynamics. This disparity, commonly referred to as the ‘curse of dimensionality,’ motivates the search for principled reduction frameworks. This review provides a comprehensive synthesis of the methodologies developed to resolve this paradox by extracting low-dimensional ‘macroscopic theories’ from complex systems. We classify these approaches into three distinct methodological lineages: Structural Coarse graining, which utilizes spectral and topological renormalization to physically contract the network graph; Analytical-Based Reduction, which employs rigorous ansatzes (such as Watanabe-Strogatz and Ott-Antonsen) and moment closures to derive reduced differential equations; and Data-Driven Reduction, which leverages manifold learning and operator-theoretic frameworks (e.g. Koopman analysis) to infer latent dynamics from observational trajectories. We posit that the selection of a reduction strategy is governed by a fundamental ‘No Free Lunch’ theorem, establishing a Pareto frontier between computational tractability and physical fidelity. Furthermore, we identify a growing epistemological schism between equation-based derivations that preserve causal mechanisms and black-box inference that prioritizes prediction. We conclude by highlighting emerging frontiers: Higher-Order Laplacian Renormalization for simplicial complexes and hybrid scientific machine learning architectures that integrate analytical priors with deep learning to address the closure problem.
Atomic-scale friction is significantly influenced by the sliding direction. In this review, we introduce early experimental investigations and other representative studies of this phenomenon that, in the past three decades, have unambiguously demonstrated the occurrence of friction anisotropy at interfaces formed by only a few atoms in contact. Sharp nanotips elastically driven on inorganic and molecular crystals, graphene and other 2D materials, including heterostructures and moiré patterns, have been the main subjects of this research. The discussion is corroborated by computational investigations that shed light on the molecular mechanisms ruling friction anisotropy and provide a robust interpretative background to the experimental results. Applications of these concepts to the nanomanipulation of organic molecules on crystal surfaces conclude the review.
The emergence of topological photonics has revolutionized the paradigm of photonic device design, with its core principle being the utilization of topological invariants to achieve robust control over light propagation and localization. In recent years, this concept has been successfully introduced into fiber optics, giving rise to topological photonic crystal fibers (TPCFs). The Dirac-vortex TPCFs, based on the Jackiw-Rossi zero mode, are realized by introducing a generalized Kekulé modulation in their cross section. This approach exhibits remarkable properties, including a controllable number of modes, a large bandwidth for single-polarization single-mode operation, and robustness against structural disorder. In this paper, we give a comprehensive overview of recent advances in Dirac-vortex TPCFs, including the physical mechanisms with its origin of topological photonic crystals and photonic crystal fibers, theoretical design, and experimental realization. We also discuss opportunities and challenges of Dirac-vortex TPCFs for future applications.
The last three decades have seen major breakthroughs in single-molecule biophysical techniques, which have advanced our understanding of biological processes across various scales from molecules to cells and tissues. The need to manipulate, control and monitor the dynamics of biomolecules simultaneously motivated the combination of complementary single-molecule methods. One of the most successful examples of such a combination is integrated optical tweezers (OT) force-fluorescence microscopy. OT is capable of immobilizing individual molecules, typically DNA, using optically trapped micron-sized beads, applying precisely controlled stretching forces, and monitoring kinetic processes in real time. Integration with fluorescence microscopy allows simultaneous monitoring of the identity and dynamics of molecules interacting with tethered DNA. A research field that particularly benefits from advanced OT force–fluorescence microscopy is the investigation of DNA replication, a crucial biological process involving complex protein‒DNA and protein‒protein interactions. In this review, we summarize the recent technical developments in OT force–fluorescence spectroscopy and associated advancements in biochemical sample preparation; briefly introduce the viral, bacterial and eukaryotic DNA replication machinery; and discuss the applications of OT force–fluorescence spectroscopy in the investigations of DNA replication mechanisms.
Lipid membrane fusion is a fundamental process underlying numerous biological functions in both physiological and pathological conditions. Understanding the physico-chemical mechanisms governing fusion, from the minimal molecular and structural requirements to the factors regulating its progression, is essential for elucidating complex biological phenomena and developing new biomedical and synthetic biology strategies. In this review, we adopt an interdisciplinary perspective to analyze how lipid composition, environmental conditions, and fusogenic agents influence the different stages of the fusion process, from membrane docking to fusion pore formation. We critically examine the main in vitro membrane models, discussing their advantages and limitations, and integrate experimental results with contributions from molecular simulations, which have allowed us to resolve the fusion intermediates and the underlying energy landscape at the nanoscale level. Particular emphasis is placed on synthetic fusogenic agents, including peptides, nucleic acids, nanoparticles, and polymers, highlighting their mechanisms of action and possibilities for rational design. Finally, we discuss emerging applications of membrane fusion in synthetic biology and biomedicine, with a focus on biomimetic systems, controlled drug delivery, and fusogenic lipid particles that promote endosomal escape. Overall, this review aims to provide a unifying conceptual framework linking fundamental principles of membrane fusion with advanced technological applications.
Free-electron interactions with light and matter have long served as a cornerstone for exploring the quantum and ultrafast dynamics of material excitation. In recent years, this paradigm has evolved from a classical description of radiation and acceleration toward a fully quantum framework, transforming our understanding of light-matter interactions at the single-electron level. These advances have opened new opportunities in high-resolution imaging, ultrafast spectroscopy, interferometry, and the coherent shaping of electron wavepackets. This review surveys stimulated interactions between slow electrons and light, encompassing free-space and near-field mediated mechanisms. We discuss how free-space optical fields coherently modulate electron momentum and energy, and how near-field coupling in nanophotonic and plasmonic structures enables strong, phase-matched, efficient momentum exchange with the electron wavepacket. We further describe electron recoil, which is significant in the slow-electron regime, and temporal and spatial wavepacket shaping that enhances coupling efficiency and extends access to quantum-coherent regimes. Building on these foundations, we outline emerging frameworks including hybrid optical-electrostatic modulation, ponderomotive laser-based aberration correction, and optical electron interferometry. By unifying these developments, stimulated electron-light interactions provide a versatile route to precise beam control, quantum-state engineering, and tailored light-matter coupling, with implications for ultrafast spectroscopy, nanoscale metrology, attosecond pulse generation, electron-photon entanglement, and the creation of nonclassical states of light.
Polaritons are half-light half-matter quasi particles resulting from the strong coupling between light and matter. This unique composition confers exceptional properties including low effective mass and pronounced nonlinearities arising from interactions of the matter part, facilitating high-temperature Bose-Einstein condensation. Ultrafast energy relaxation dynamics lies at the heart of the functionality of polaritons for various optoelectronic applications including low threshold polariton lasing, macroscopic quantum phenomena like superfluidity, all-optical switching, and long-range energy transport. Transient absorption/reflection spectroscopy has been widely used to probe the polariton dynamics. However, the existence of multiple resonances (lower polariton, upper polariton, exciton reservoir) makes it challenging to clearly disentangle the dynamics for different branches and elucidate their coupling. Ultrafast two-dimensional spectroscopy, providing simultaneously high time and frequency resolution, and the correlation between excitation and detection frequency, is more sensitive in studying such coupling systems. We review recent experimental two-dimensional spectroscopy study of polaritons dynamics, including incoherent relaxation and dissipation, coherent Rabi oscillation and its manipulation, and energy transfer dynamics within multi-component cavity polaritons.
Ultrafast nonlinear optical spectroscopy is a powerful tool for probing photo-induced processes such as exciton dynamics and interactions. Recent advances enable complete control over the interaction with the excitation pulses, allowing a full separation of the measured signals according to their order of nonlinearity. This capability provides unprecedented access to multi-exciton states and their dynamics. In this work, we review these developments in both coherently and action-detected spectroscopy, focusing on the signatures of multi-exciton effects. Among these, the most prominent process is exciton–exciton annihilation. By examining the spectra from a combined theoretical and experimental perspective, we identify which variants of current nonlinear spectroscopy are best suited to measure exciton transport and interaction, as well as the structure and properties of multi-exciton states.
Single-photon detectors capable of detecting short-wave infrared (SWIR) light have undergone significant research and development over the past 30 years. Most innovations in single-photon detectors have focused on two types of devices: superconducting nanowire single-photon detectors (SNSPDs) and semiconductor-based single-photon avalanche diode (SPAD) detectors. These sensitive, picosecond time-resolved photon detectors have been employed in a wide range of emerging applications near and in the SWIR region including use in light detection and ranging (LiDAR), quantum networks, quantum computing, and a variety of biophotonics applications. Emerging quantum technology applications require single-photon detectors with high detection efficiency, ultra-low dark count rates, high counting rates and low timing jitter. This review presents an overview of the state-of-the-art of SNSPDs and SPADs operating at a wavelength of 1310 nm or 1550 nm, both for single-pixels and arrayed detectors, as well as recent demonstrations of these extremely sensitive detectors in emerging applications. The main advantages and use-cases of each type of detector will be discussed, highlighting significant achievements and identifying areas for future development.
Coalescence (or sintering) of two or more nanoparticles into larger nanoparticles or particle aggregates is one of the fundamental processes that differentiate nano-matter from bulk matter, and plays a vital role in determining shape, size, structure, and resultant properties vital for various applications. Computational methods, especially atomistic simulations, have been employed over the past decades to reveal the dynamics of nanoparticle coalescence at the atomic level. Integrated findings from various simulations enhance our understanding of nanoparticle interaction and merging mechanisms. Understanding these mechanisms can guide the design of nanoparticles with tailored properties for diverse applications from printed and flexible electronics to catalysis and pigmentations, and from drug delivery and energy storage to nanoparticle-based neuromorphic computation devices. This review aspires to distil our current knowledge and understanding of nanoparticle coalescence in a compact and visual way, so that it can be used as reference and starting point for future computational studies and as guidance for the experimental fabrication of nanoparticulated matter.
Recent advancements in nanoscale physics have resulted in a paradigm shift towards point-of-care (POC) complex healthcare diagnostics, enabling real-time biomolecular detection. These innovations are based on manipulating complex light–matter interactions at the nanoscale, where photons couple with plasmons, excitons, phonons, and resonant cavities to transduce biomolecular events into quantifiable optical signals. This review presents a physics-oriented overview and quantitative comparison of POC nano-optical biosensors based on the dominant fundamental light–matter interaction mechanism at the nanoscale. It includes surface plasmon resonance (localized, imaging, and long-range), interferometric methods (plasmon-assisted, dual-beam, and frequency-domain reflectometry), fluorescence and colorimetric assays, along with resonator-enabled architectures including whispering gallery modes, photonic crystals, Raman scattering, and optical coherence tomography. Emerging modalities, including photothermal, chemiluminescence, and nonlinear optical biosensors, are highlighted due to their wide and dynamic detection range, spanning from the micromolar to the challenging attomolar range. Besides, it details the advancements, device-miniaturization strategies, integration with advanced nanomaterials and microfluidics, and persistent challenges such as stability, non-specificity, and signal interference alongside proposed solutions. Finally, it presents future directions, including multi-modal sensing, wearable platforms, and AI-assisted predictive modelling, pointing towards next-generation of physics-enabled POC biosensors that can deliver accessible, accurate, and personalised healthcare.
Owing to their tunable optical, electronic, magnetic, and mechanical properties, nanostructured materials assembled from nanoparticles (NPs) have attracted growing interest. Their collective behavior is governed by NP size, shape, surface chemistry, and spatial organization. Bottom-up self-assembly provides a versatile fabrication route, typically requiring a soft medium to mediate NP interactions. Lipid membranes are particularly attractive scaffolds for NP assembly due to their low dimensionality, fluidity, and elasticity. NP adhesion to lipid membranes induces curvature deformation extending beyond the particle size. Overlap of these deformations generates effective multibody, curvature-mediated interactions that can drive NP self-assembly. This review summarizes recent coarse-grained molecular dynamics studies of NP self-assembly on planar lipid membranes and vesicles. Uniform NPs adhering to the inner leaflet of vesicles form quasi-two-dimensional, star-like nanoclusters stabilized by repulsive curvature-mediated interactions, whereas NPs on planar membranes or outer leaflet of vesicles assemble into linear close-packed chains. Introducing surface anisotropy through Janus modification overcomes these limitations by suppressing close-packed aggregation and endocytosis. Janus NPs on lipid vesicles form deltahedral nanoclusters, including some Platonic solids. On planar membranes, they assemble into triangular superlattices. Geometric anisotropy expands the range of accessible membrane-mediated assemblies. These findings highlight lipid membranes as adaptive scaffolds for reconfigurable nanostructures without direct NP-NP binding.
The fundamental question of when a static or dynamic system should be deemed intrinsically quantum remains a challenge to address in absolute terms. A rigorous criterion, however, can be established by focusing on the measurable or reconstructible features of the system. This determination transcends mere issues of a system's classical simulability or computational complexity. Instead, the critical requirement lies in the certification (ideally, in real-time) of the emergence and persistence of genuine quantum features, principally entanglement and quantum superposition. Quantum Non-Demolition Measurements (QNDM) serve as the appropriate instrument for this certification, both from a theoretical and experimental standpoint. In this review paper, we demonstrate, with accessible clarity, how the implementation of QNDM can be directly linked to a necessary and sufficient condition for the violation of macrorealism in finite-dimensional systems, establishing a conceptual parallel with Leggett-Garg inequalities. Using concrete examples that detail the detection of negative terms in the quasi-probability density function resulting from QNDM, we introduce the core concepts for certifying genuinely quantum features. As specific examples, we discuss an application where the quantum-to-classical transition due to the interaction with an environment can be tracked by QNDM. Moreover, we argue about the robustness of QNDM protocols in the presence of noise sources and their advantages with respect to the Leggett-Garg inequalities. Because of its straightforward implementation, the QNDM approach can be of direct relevance to both the foundations of quantum mechanics and quantum information theory, where a controlled generation and certification of genuinely quantum resources is a central concern.
