Papers

We predict ultrafast switching in a chiral anti-ferromagnet that occurs at femtosecond times, nearly 5 orders of magnitude faster than the torque induced nanosecond switching previously observed. The physical mechanism, quite different from that which drives slow switching, involves the creation of massive effective magnetic fields by ultrafast spin current injection. Identifying these fields as key to femtosecond rotation, we establish simple practical rules for their maximisation with wide applicability to all magnetised materials. Employing state-of-the-art time-dependent density-functional theory and using the example of chiral magnet, Mn$_3$Sn, we induce ultrafast rotation enough to drive the switching of magnetic order between the six possible non-collinear ground states. We further demonstrate the possibility of undoing this switching by subsequent injection of oppositely polarized spin current. Our findings place chiral anti-ferromagnets as a materials platform for femtosecond Néel-vector switching, opening a route towards the manipulation of magnetic matter at ultrafast times.

Automated decision-making is becoming key for automated characterization including electron and scanning probe microscopies and nano indentation. Most machine learning driven workflows optimize a single predefined objective and tend to converge prematurely on familiar responses, overlooking rare but scientifically important states. More broadly, the challenge is not only where to measure next, but how to coordinate exploration across structural, spectral, and measurement spaces under finite experimental budgets while balancing target-driven optimization with novelty discovery. Here we introduce PATHFINDER, a framework for autonomous microscopy that combines novelty driven exploration with optimization, helping the system discover more diverse and useful representations across structural, spectral, and measurement spaces. By combining latent space representations of local structure, surrogate modeling of functional response, and Pareto-based acquisition, the framework selects measurements that balance novelty discovery in feature and object space and are informative and experimentally actionable. Benchmarked on pre acquired STEM EELS data and realized experimentally in scanning probe microscopy of ferroelectric materials, this approach expands the accessible structure property landscape and avoids collapse onto a single apparent optimum. These results point to a new mode of autonomous microscopy that is not only optimization-driven, but also discovery-oriented, broad in its search, and responsive to human guidance.

The dependence of mechanical properties on microscopic interactions remains a central problem in the physics of disordered solids near the jamming transition. We numerically and theoretically investigate the mechanical response of jammed cohesive granular materials using discrete element simulations and effective medium theory (EMT). We find that the shear modulus exhibits pronounced hysteresis under compression and decompression, even though the interparticle force law itself is strictly history-independent. While such hysteresis disappears for purely repulsive particles when mechanical properties are characterized in terms of pressure, it persists in cohesive packings, indicating that pressure is not a unique state variable for cohesive particles. Extending EMT to cohesive interactions, we show that the functional form of the shear modulus remains the same for both repulsive and cohesive particles, but that attractive interactions violate marginal stability. The resulting deviation from marginal stability generates excess rigidity, as predicted by a scaling relation. This prediction is quantitatively verified by numerical simulations and explains the persistent hysteresis in cohesive packings.

Continual learning in artificial neural networks is fundamentally limited by the stability–plasticity dilemma: systems that retain prior knowledge tend to resist acquiring new knowledge, and vice versa. Existing approaches, most notably elastic weight consolidation~(EWC), address this empirically without a physical account of why plasticity eventually collapses as tasks accumulate. Separately, the distinction between sudden insight and gradual skill acquisition through repetitive practice has lacked a unified theoretical description. Here, we show that both problems admit a common resolution within non-equilibrium statistical physics. We model the state of a learning system as a particle evolving under Langevin dynamics on a double-well energy landscape, with the noise amplitude governed by a time-dependent effective temperature $T(t)$. The probability density obeys a Fokker–Planck equation, and transitions between metastable states are governed by the Kramers escape rate $k = (\omega_0\omega_b/2\pi)\,e^{-\Delta E/T}$. We make two contributions. First, we identify the EWC penalty term as an energy barrier whose height grows linearly with the number of accumulated tasks, yielding an exponential collapse of the transition rate predicted analytically and confirmed numerically. Second, we show that insight and repetitive learning correspond to two qualitatively distinct temperature protocols within the same Fokker–Planck equation: insight events produce transient spikes in $T(t)$ that drive rapid barrier crossing, whereas repetitive practice operates at a modestly elevated but fixed temperature, achieving transitions through sustained stochastic diffusion. These results establish a physically grounded framework for understanding plasticity and its failure in continual learning systems, and suggest principled design criteria for adaptive noise schedules in artificial intelligence.

We report a comprehensive study of the temperature-dependent structural, magnetic, vibrational, and dielectric properties of Al-substituted M-type hexaferrites SrFe$_{12-x}$Al$_x$O$_{19}$. Neutron powder diffraction and Mössbauer spectrometry show that Al$^{3+}$ preferentially replaces Fe$^{3+}$ at spin-up octahedral sites (2a, 12k), disrupting the exchange coupling with the spin-down 4f tetrahedral sites and leading to a progressive reduction of site-specific magnetic moments and a systematic decrease in the Curie temperature, supported by temperature dependent susceptibility measurements. Raman spectroscopy reveals pronounced phonon anomalies near $T_C$, particularly in modes associated with bipyramidal Fe-O vibrations, reflecting the weakening of both 4e-12k and 4e-4f exchange pathways. However, the coercive field exhibits a dramatic increase, reaching $\mu_0H_C$ $\sim$ 1.2 T for SrFe$_{9.6}$Al$_{2.4}$O$_{19}$, among the largest values reported for this class. Susceptibility measurements suggest that Al substitution, while weakening the superexchange network, contributes to the stabilization of single-domain behavior.

Understanding the factors that control superconductivity is essential for discovering new superconducting materials using high-throughput elemental substitution. Focusing on the recently predicted ambient-pressure superconducting X2MH6 family, we disentangle the phononic and electronic contributions to Tc to determine how isoelectronic substitution alters superconductivity. While substitution affects both phononic and electronic properties, the electronic contribution plays the dominant role in determining Tc in the X2MH6 family. We show that the electronic contribution is affected by three key factors: the X-H bond distance, the electron localization function networking value of hydrogen, and the hydrogen-projected density of states at the Fermi level. A combined figure of merit derived from these parameters exhibits a robust correlation with Tc across the family. We further show that pressure produces competing effects on superconductivity: it enhances the electronic contribution by shortening X-H bonds, but simultaneously weaken the phononic contribution by increasing phonon frequencies. The net pressure dependence of Tc therefore results from the balance between these opposing tendencies. By disentangling and analyzing the electronic and phononic mechanisms, this work provides comprehensive insight into superconductivity in X2MH6 hydrides and offers practical guidance for designing new high-Tc hydride superconductors.

The Grover lower bound for the unstructured search problem can be surpassed when some information about the data structure is available. Here, we numerically observe that reinforcement can exponentially reduce the number of required evolution layers from $\sqrt{D}$ to $\ln D$ in a $D$-dimensional system, by exploiting the information provided by the quantum state. Therefore, a reinforced quantum search is expected to exhibit a larger noise threshold compared to a standard search algorithm in a noisy environment. We use numerical simulations to characterize the level of noise tolerance via reinforcement in the presence of both coherent and incoherent noise, considering a system of $N$ qubits and a single $D$-level (qudit) system. Our results show that reinforcement significantly enhances the algorithm's success probability and improves the scaling of the number of reinforced evolution layers with system size. These findings indicate that reinforcement offers a promising strategy for error mitigation, especially when a precise noise model is unavailable.

We study the triangular lattice optical Su-Schrieffer-Heeger (SSH) model using determinant quantum Monte Carlo. By varying the model's carrier concentration, electron-phonon coupling strength, and phonon energy $\Omega$, we identify two doping regimes of interest. At one-quarter filling ($\langle n\rangle = 0.5$), corresponding to the case of a circular noninteracting Fermi surface, we find evidence for a metal to insulating bond-order-wave (BOW) phase transition that breaks a local $C_6$ rotational symmetry. Conversely, at three-quarters filling ($\langle n\rangle = 1.5$), corresponding to a hexagonal Fermi surface, we find evidence for transitions to another BOW phase for small $\Omega$ and an $s$-wave superconducting phase for sufficiently large $\Omega$. This tendency toward pairing appears to be associated with the possibility of a sign change in the effective intersite hopping, which can occur for sufficiently large lattice displacements. We also find no evidence for enhanced magnetic correlations in the model, contrary to what has been reported for square lattice SSH models.

We discuss the finite-temperature properties of low-dimensional bosons with three-body interactions described by a Feshbach-resonance-like two-channel model. In particular, by using the approximate consideration that collects ring-like Feynman diagrams for the grand potential and resembles the three-body $t$-matrix approximation, we have computed the third virial coefficient, an equation of state, and the temperature depletion of the average number of closed-channel trimers. The calculated heat capacity demonstrates a non-monotonic temperature behavior, which is unusual for a low-dimensional Bose gas.

A two dimensional classical ferromagnetic XY model with its bound vortex-antivortex dominated quasi long range ordered phase at low temperatures is a long standing as well as well studied problem of interest in the field of condensed matter. We conduct a detailed Monte Carlo study of such model in a square lattice with rather unexplored extensions where additional anisotropic exchange coupling and Dzyaloshinskii-Moriya interactions (DMI) together affect the Kosterlitz-Thouless (KT) transition in presence/ absence of symmetry breaking fields. Without DMI, the exchange term promotes collinear (ferromagnetic) order, whereas the DMI term induces spin cantings. By tuning anisotropy upto Ising limit, we document energy, specific-heat, magnetizations as well as helicity modulus and vortex densities for different temperatures and DMI strength. We also compute the 2nd moment of correlation lengths in order to probe the spatial correlation of the spins. Furthermore, the effect of U(1) symmetry breaking 4-fold and 8-fold symmetric h4 and h8 fields are explored which shows how the double-peaked specific heat profiles changes in presence of DMI. Overall, our findings append many important updates in the low temperature phases of a topological XY ferromagnet when additional DMI and isotropy-breaking exchange and/or field terms are considered thereby providing a few practical blueprints for suitably engineering topological spin systems.

UMG-Si has the potential to reduce the cost of PV technology and to improve its environmental profile. In this contribution, we summarize the extensive work made in the research and development of UMG technology for PV, which has led to the demonstration of UMG-Si as a competitive alternative to polysilicon for the production of high-efficiency multicrystalline solar cells and modules. The tailoring of the processing steps along the complete Ferrosolar's UMG-Si manufacturing value chain has been addressed, commencing with the purification stage that results in a moderately compensated material due to the presence of phosphorous and boron. Gallium is added as a dopant at the crystallization stage to obtain a uniform resistivity profile 1 Ohm*cm along the ingot height. Defect engineering techniques based on phosphorus diffusion gettering have been optimized to improve the bulk electronic quality of UMG-Si wafers. Black silicon texturing, compatible with subsequent gettering and surface passivation, has been successfully implemented. Industrial-type BSF and PERC solar cells have been fabricated, achieving cell efficiencies in the range of those obtained with conventional polysilicon substrates. TOPCon solar cell processing key steps have also been tested to further evaluate the potential of the material in advanced device architectures beyond PERC. Degradation mechanisms related to light exposure and operation temperature have been shown not to be significant in UMG PERC solar cells when a regeneration step is implemented, and PV modules with several years of outdoor operation have demonstrated similar performance to reference ones based on poly-Si. LCA has been carried out to evaluate the environmental impact of UMG-based PV technology when compared to the poly-Si-based one, considering different scenarios both for the manufacturing sites and the PV installations.

Turning scientific papers into reliable code requires making implicit computational knowledge explicit. We introduce and evaluate a human-supervised workflow in which large language models develop and review technical specifications before implementing quantum many-body algorithms. The specifications encode conventions, procedures, scaling requirements, and validation gates for mathematical consistency, physical accuracy, and production-scale performance. For the density-matrix renormalization group, all 16 tested specification–implementation model pairings succeed, compared with 6 of 13 direct attempts; two further attempts succeed with a prose specification. For Pfaffian conversion of Hartree–Fock–Bogoliubov states to matrix product states, on eleven matched model–harness configurations, four self-paired workflow attempts pass and no direct attempts do; across all phases, 11 of 26 workflow attempts pass the audit and validation criteria. Cross-model transfer is asymmetric: one implementation model succeeds with all four specifications written by other models, whereas all four reverse-direction attempts fail. A consolidated specification informed by these experiments supports successful implementations in three previously unsuccessful model–harness configurations. Technical specifications therefore guide scalable implementation and help distinguish paper-to-code ambiguity from limitations in implementation capability. We synthesize these findings into the Paper-to-Program Many-Body protocol, which turns implementation experience into reusable review criteria, validation gates, and reporting practices. Publicly archived prompts, transcripts, specifications, code, and validation records support independent verification and extension to other many-body algorithms.

Twistronics is a powerful strategy to engineer novel quantum states by controlling the relative orientation between layered materials. Here, we demonstrate that an orthogonally twisted bilayer CrPS$_4$ shows $d$-wave altermagnetism driven purely by structural rotation. Symmetry analysis reveals that the twisted stacking breaks partial translational combined with time-reversal symmetry, leading to a fourfold rotation relation between opposite spin sublattices, enabling altermagnetism. First-principles calculations demonstrate a sizable non-relativistic spin splitting of up to 68 meV around the Fermi level. We further show that the altermagnetic state can be further stabilized through interlayer compression and modulation of the on-site Coulomb interaction. The resulting band structure exhibits pronounced spin-dependent anisotropy, enabling efficient spin to charge conversion reaching $\sim$50% near the Fermi level and sizable giant magnetoresistance. These results establish twisted CrPS$_4$ as a realistic platform for altermagnetism and highlights twistronics as a versatile route for advanced spintronics applications.

Integrability in one dimension prevents quantum thermalization and gives rise to rich many-body phenomena described by generalized hydrodynamics, which have been extensively studied over the past two decades using cold atoms in optically confined tubes. However, experimental work to date has focused primarily on low-energy states. Here, we report the experimental observation and theoretical understanding of near-integrable effects on thermalization in highly excited states. We design a protocol to prepare atoms within a high-energy window by combining a harmonic trap and a weak optical lattice: a Bose-Einstein condensate is initially prepared away from the trap center via Wannier-Stark localization and subsequently emits atoms into a selected energy window of highly excited states via Landau-Zener tunneling. By reconstructing the Wigner functions from the density distribution using a machine learning algorithm, we find that it takes an exceptionally long time, up to several seconds, for these atoms to gradually thermalize from an approximately microcanonical ensemble toward a canonical ensemble. We develop a modified Boltzmann equation that captures weak integrability breaking, yielding good agreement between theory and experiment. Our results extend the understanding of integrability and thermalization in low-dimensional quantum systems.

We introduce the notion of dismagicker: non-Clifford unitary gate designed to reduce the non-stabilizerness (also called magic) of quantum many-body states. Although both entanglement and non-stabilizerness are fundamental quantum resources, they require distinct control strategies. While disentanglers (unitary operations that lower entanglement) are well-established in tensor network methods, analogous concept for non-stabilizerness suppression has been largely missing. In this work, we define dismagicker as non-Clifford unitary operation that actively suppresses non-stabilizerness, steering states toward classically simulatable stabilizer states. We develop optimization method for constructing dismagickers within the Matrix Product States framework. Our numerical results show that the non-stabilizerness reduction procedure, when combined with entanglement reduction steps with Clifford circuits, significantly improves the accuracy for both classical simulation of many-body systems and quantum state preparation on quantum devices. Dismagicker enriches our toolkit for the manipulation of many-body states by unifying non-stabilizerness and entanglement reduction.

A modified set of Mosseri-Sadoc (MS) tiles tessellating 3D Euclidean space with icosahedral symmetry is introduced. The new set of tiles are embedded in dodecahedron with a threefold symmetric order. The modified Mosseri-Sadoc (MMS) tiles can be inflated by a new inflation matrix with positive eigenvalues $\tau^3$ and $\tau$ with the corresponding eigenvectors representing the volumes and the Dehn invariants of the tiles, respectively, where $\tau=\frac{1+\sqrt5}{2}$ is the golden ratio. The MMS tiles are obtained by projection of the 4D and 5D facets of the Delone cells tiling the $D_6$ root lattice in an alternating order. It is also proved that a subset of the lattice $D_6$ projects into the dodecahedron inflated by $\tau^n$ with an arbitrary integer $n$ and tiled by the MMS tiles.

We theoretically investigate circular dichroism (CD) in second- and third-harmonic generation (SHG and THG) in the chiral topological semimetal CoSi. We demonstrate that both SHG and THG exhibit dichroic responses of order unity, while their robustness against spectral broadening is strikingly different. Specifically, while SHG-CD is strongly suppressed by dissipation, THG-CD remains robust over a wide frequency range. We show that this qualitative difference originates from the phase structure of the nonlinear current, where SHG-CD arises from subleading interference processes that are sensitive to dephasing, whereas THG-CD emerges already at the leading nonlinear order and is therefore protected against spectral broadening. As a result, THG-CD provides a robust probe of chirality encoded in nonequilibrium electronic dynamics. We further reveal non-monotonic frequency dependences and pronounced sensitivity of harmonic emission to the polarization state and crystallographic orientation of the driving field. Our results provide a representative example of robust nonlinear chiroptical responses in chiral topological semimetals and highlight the potential of high-harmonic spectroscopy as a probe of phase-resolved electronic dynamics.

Recently, studies have explored the statistics of matrix elements of local operators in the Lieb-Liniger model. It was found that the probability distribution function for off-diagonal matrix elements $\langle \boldsymbol{\mu}|\mathcal{O}|\boldsymbol{\lambda} \rangle$ within the same macro-state is well described by the Fréchet distributions. This represents a significant development for the Eigenstate Thermalization Hypothesis (ETH). In this paper, we investigate a similar phenomenon in another solvable model: the disorder-free Sachdev-Ye-Kitaev (SYK) model. The Hamiltonian of this model consists of 4-body interactions of Majorana fermions. Unlike the conventional SYK model, the coupling strengths in this model are fixed to a constant, earning it the name “disorder-free.” We evaluate the matrix elements of operators constructed from products of $n$ Majorana fermions: $\mathcal{O} = \chi_{a_1}\chi_{a_2}\ldots \chi_{a_n}$. For a general choice of indices and $n \geq 4$, we find that the statistics of the off-diagonal matrix elements are well-fitted by a generalized inverse Gaussian distribution rather than Fréchet distributions.

Magneto-thermoelectric (MTE) effect has demonstrated significant ad-vantages in achieving optimal thermoelectric (TE) properties compared to conventional methods. Topological materials pro-vide a unique platform for investigating the MTE effect, leveraging their exotic electronic structure topology. In this study, we report that the topological material GdTe3 exhibits an unsaturated power factor of up to 18846 {\mu}W m-1 K-1 under a magnetic field of 13.5 T at 20 K, which represents the highest value observed in metallic systems and surpasses most state-of-the-art TE materials. The relative enhancement under magnetic field in thermopower and power factor reaches 873% and 1075%, respectively, attributed to the Weyl points contribution resulting from the field-induced topological transition, as confirmed by our theoretical calculations. Our findings demonstrate a promising candidate for solid-state cooling and reveal the substantial contribution of Weyl points to TE enhancement, thereby offering a novel approach to optimizing TE properties in topological materials.

Spatially Fractionated Radiation Therapy (SFRT) or GRID therapy has been in existence for more than a century. GRID therapy was invented as an approach to address the challenges posed by bulky tumors. To treat patients with GRID therapy, the protocol needs to be implemented within the Treatment Planning System (TPS) software. Also, the dose needed for treatment must be validated. A few TPS software vendors such as Elekta and Varian have protocols for treating patients with GRID therapy. However, we are the first to implement the protocols within RayStation TPS. To achieve these, we used the .decimal GRID block applicator to create conformal treatment plans. For the beam modeling, several dosimetry data, and measurements such as percentage depth dose (PDD), beam profile, output, and GRID factors, were obtained for different field sizes and energies. The dose distribution from the GRID openings covered the Planning Target Volume (PTV), with the QA plan having a 98% agreement with the planned dose. Also, we used the Mapcheck2 results to verify the adjustments made to the script variables such as aperture size (hole and spacing). We developed a robust way to validate the dose needed for patient treatment using the GRID block applicator. Also, we have proposed a novel approach to standardize the clinical implementation of the GRID block in RayStation TPS.

Tensor network methods, particularly those based on Matrix Product States (MPS), provide a powerful framework for simulating quantum many-body systems. A persistent computational challenge in these methods is the selection of the bond dimension chi, which controls the trade-off between accuracy and computational cost. Fixed bond dimension strategies either waste resources in low-entanglement regions or lose fidelity in high-entanglement regions. This work introduces an adaptive bond dimension management framework that uses von Neumann entropy feedback coupled with a Proportional-Integral-Derivative (PID) controller to dynamically adjust chi at each bond during simulation. An Exponential Moving Average (EMA) filter stabilizes entropy measurements against transient fluctuations, and a predictive scheduling module anticipates future bond dimension requirements from entropy trends. The per-bond granularity of the allocation ensures that computational resources concentrate where entanglement is largest. The framework integrates GPU-accelerated Singular Value Decomposition (SVD) via CuPy and the cuSOLVER backend, achieving individual SVD speedups of 4.1x at chi=256 and 7.1x at chi=2048 relative to CPU-based NumPy for isolated matrix factorisations (measured on an NVIDIA A100-SXM4-40GB GPU with CuPy 13.4.1 and CUDA 12.8). At the system level, benchmarks on the spin-1/2 antiferromagnetic Heisenberg chain demonstrate a 2.7x reduction in total DMRG wall time compared to fixed-chi simulations, with energy accuracy within 0.1% of the Bethe ansatz solution. Integration with the Density Matrix Renormalization Group (DMRG) algorithm yields ground-state energies per site converging to E/N = -0.4432 for the isotropic Heisenberg model at chi = 128. Validation against Amazon Web Services (AWS) Braket SV1 statevector simulator confirms agreement within 2-5% for small systems.

In superconducting quantum circuits, decoherence improvements are frequently obtained through process interventions that simultaneously modify surface chemistry, microstructural topology, and device geometry, leaving mechanistic attribution structurally underdetermined. Predictive materials engineering requires measurable structural statistics to be separated from geometry-dependent coupling coefficients into independently testable factors. We introduce the concept of classical and quantum microstructure. In that context, we formulate a channel-wise separable framework for decoherence in superconducting transmon qubits in which each loss channel is described by a reduced prescriptor. Here, a channel-specific microstructural state variable is determined independently of device geometry, and a geometry-dependent coupling functional is computable from field solutions without reference to surface chemistry. We derive this product form from a spatially resolved kernel representation and establish a perturbative separability criterion that defines the regime where independent variation of the variables is valid. The framework specifies five prescriptor classes for dominant loss pathways in transmon-class devices. Falsifiability is operationalized through a pre-committed 2x2 experimental protocol in which the variables must satisfy independent ratio checks within propagated uncertainty. A Minimum-Dataset Specification standardizes reporting for cross-laboratory inference. Part I establishes the conceptual and mathematical architecture; coordinated experimental validation is reserved for Part II.

A photodetector that can directly distinguish the orbital angular momentum (OAM) of light is highly desirable for integrated on-chip OAM detection and focal plane array devices. The recent development of OAM detectors based on the intrinsic orbital photo galvanic effects (OPGE) of materials provide a new route for direct OAM detection that is on-chip scalable with high resolution and speed. In this paper, we summarize the current progress in direct photodetection of OAM via OPGE. We begin with a short review of the basic operation scheme of the OAM detector and provide a comprehensive symmetry analysis to sort out the favorable characteristics of the materials, incorporating considerations from device schemes based on various device performance characteristics and specific application circumstances. From that, we review the current experimental progress and technical challenges, then oversee the possible solutions to these challenges and provide a perspective on the future opportunities of this OAM detection route.

Understanding the realization of thermal equilibrium through the thermalization process in a many-body system is a fundamental and complex scientific question, bridging thermodynamics and classical dynamics and connecting to a host of physical phenomena, such as mechanical instabilities in a thermal environment. In this work, based on the harmonic lattice model, we investigate the thermalization process in both velocity and coordinate spaces, by examining microscopic dynamics on the atomic level. We show the distinct relaxation rates of the transverse and longitudinal components of the velocity, reveal the power law governing the nonlinear proliferation of dominant frequencies, and observe the concurrent rapid proliferations of frequencies and topological defects. We also show that the lattice system's persistent out-of-plane deformations exhibit two-stage fluctuation behaviors, characterized by distinct power laws of fractional exponents and associated with the broken up-down symmetry. This work demonstrates the rich dynamics underlying the thermalization process, and advances our understanding on the dynamical adaptations of many-body systems to external disturbances.

Classical thermal transport theories that preserve rotational symmetry, predict strong anharmonic scattering of out-of-plane lattice vibrational modes called flexural phonons in flat suspended graphene sheets. Such strong scattering processes cause a breakdown of the phonon quasiparticle picture, which remains valid only when several cycles of lattice vibrations occur before the mode decays. Here we show that the renormalization of elastic bending rigidity ($D$), caused by the coupling between the in-plane and the out-of-plane thermal lattice fluctuations, restores phonon quasiparticles in suspended graphene. Importantly, this $D$-renormalization weakens the momentum-dissipating Umklapp phonon scattering processes, resulting in improved thermal conductivity and amplified phonon hydrodynamics in suspended graphene. Our results unveil a previously-unrecognized connection between the macroscopic elasticity and the microscopic flexural phonon scattering in two-dimensional (2D) materials that does not occur in three-dimensional bulk crystals, thereby motivating a re-examination of the classical theories and opening up new avenues to engineer the thermal as well as the phonon-limited electronic transport and relaxation in two- and lower-dimensional materials.

This study presents a computational investigation of self-assembly and rheological behaviour of multichain amphiphilic block copolymers under varying chain length, architecture, composition, and shear rate. Using Brownian dynamics (BD) simulations, we systematically examined bead-spring model multi-chain diblock and triblock copolymers with chain lengths of 12-48 beads, hydrophobic fractions (f) ranging from 0 to 1.0, and shear rates spanning 0-0.1 1/ns. In the dilute regime, results demonstrate that triblock copolymers form extensive 3D networks with bridging architectures through hydrophobic end blocks, achieving solution viscosities up to half an order of magnitude higher than diblock systems, with superior structural integrity under weak shear. At shear rate=0.003-0.01 1/ns, both chain architectures show increased gyration radius of individual chains within each micelle and decreased cluster counts, indicating aggregation of clusters prior to breakdown at higher shear rates. Shape anisotropy analysis reveals that triblocks develop highly elongated prolate structures (L1/L3 = 11) at high shear rates, while diblocks form more discrete micellar assemblies (L1/L3 = 7.5). Chain length analysis shows systematic increases in radius of gyration, with triblocks exhibiting an increase in cluster count, indicative of network percolation. Rheologically, triblock systems maintain lower crossover frequencies with increasing hydrophobic fraction, reflecting slower network relaxation versus diblocks. The terminal relaxation time of triblock copolymer systems increases with hydrophobic fraction due to double-ended hydrophobic bridging, while diblocks maintain stable values. These findings provide fundamental insights for the rational design of polymer-based drug carriers through architectural selection and flow conditions.

Atomic-resolution imaging on molten metal/solid interfaces at temperatures above 200 {\deg}C was achieved using a high-temperature, high-speed atomic force microscope (AFM) equipped with a qPlus sensor. A tip-scanning high-speed Quadpod scanner for a large mass load of qPlus sensor (2.3 g) was developed to enhance thermal drift tolerance by high-speed scanning and thermal insulation from the heated specimen. This scanner has dominant resonant frequencies of 7.05 kHz (lateral) / 29.7 kHz (vertical) without a load. In addition, the Hybrid-loop frequency demodulation technique for low-resonant-frequency ($f_0$) sensors with a wider bandwidth than conventional phase-locked loop was also established, providing a demodulation bandwidth of $B_{\Delta f_\mathrm{inst}}\sim 0.26 f_0$ without exceeding the theoretical noise of the input deflection signal. Combining these techniques enabled atomic-resolution imaging on the molten $\mathrm{Ga/PtGa_x}$ interface at $\sim$210 {\deg}C. The topographic images obtained at $\sim$210 {\deg}C showed a relatively low-symmetry surface with an oblique lattice with a superstructure, which differed from the primitive rectangular lattice observed in the non-heated sample left at room temperature for 96 h. This demonstrates that the developed high-temperature, high-speed AFM techniques for qPlus sensors enable visualization of non-aqueous liquid/solid interfaces above 200 {\deg}C at atomic resolution, which has various potential applications, such as injection modeling, soldering, and the fabrication of liquid-metal-based catalysts.

Ising symmetry typically emerges in the critical domain between liquid-gas phases. Universality of this property imposes strong constraints on the behavior of thermodynamic crossovers for supercritical fluids. In this work, we develop a novel approach to investigate the crossover lines for supercritical AdS black holes using Lee-Yang phase transition theory. We analytically continue Lee-Yang zeros into the complex plane within the supercritical region by keeping a modular pressure real. Consequently, we obtain a pair of complex crossover lines, which exhibit universal scalings and manifest the emergent Ising symmetry in the complex phase space. The real crossover lines are defined by projecting the complex crossovers onto the real phase space. As a result, the phase diagram above the critical point is divided into three distinct regimes: liquid-like, indistinguishable and gas-like states, in sharp contrast to scenarios featuring only a single crossover line.

We report the design and implementation of a point-contact spectroscopy (PCS) system integrated with a dilution refrigerator, enabling measurements down to 30 mK. The setup employs a needle-anvil geometry with a cryogenic piezo-driven nanopositioner for in-situ formation of mesoscopic point contacts. We discuss the thermal anchoring strategies that enable efficient cooling of the probe to ultra-low temperatures and reliable measurements. We also address positioner-related challenges and the solutions implemented to ensure stable operation at millikelvin temperatures. The performance of the probe is demonstrated through point contact spectroscopy on Ta-doped TiSe$_2$ (Ta$_x$Ti$_{1-x}$Se$_2$, $x = 0.2$), a superconductor with $T_c \approx 2.3$ K. The spectra exhibit well-defined superconducting features that systematically diminish with increasing temperature and magnetic field. The platform provides a robust and versatile tool for spectroscopic investigations of superconductors and other quantum materials at millikelvin temperatures and high magnetic fields.

Rutile germanium oxide (r-GeO2) has shown potential for ultrawide bandgap semiconductor applications such as power conversion and UV optoelectronics. Homoepitaxial substrates will be key for achieving phase pure and doped r-GeO2 thin films as synthesis is inhibited by strain associated with substrate lattice mismatch. Initial reports of single crystal r-GeO2 synthesis from a MoO3-Li2CO3 flux have shown mm scale crystals with dominantly (110) faceting. However, fundamental understanding of the synthesis parameters and the ability to tune size and facet are needed. Here, we report on both seeded and unseeded growth of single crystal r-GeO2 across a range of MoO3-Li2CO3 flux compositions. Small variations in Mo concentration can be used to control crystal habit, faceting, and growth rate through variation in precursor complexion, solution viscosity, and GeO2 solubility. While seed size and seeded growth rates are optimized in 40% Mo solutions, aspect ratios and seeded growth volumes are maximized in 41.5% Mo solutions without sacrificing faceting. Increased Mo concentration leads to polycrystallinity and isotropic growth. These results enable faster and tailored growth of r-GeO2 crystals using the flux growth method.