Classical Predictions Research Articles

Separation of sticker-spacer energetics governs the coalescence of metastable condensates.

A key conundrum of biological condensates is the coexistence of multiple droplets, in direct variance with classical predictions of mean-field theories of polymer solutions. Our current study uncovers that the merging of sticker-spacer condensate is an entropy driven process, as opposed to the surface energy driven fusion that are observed for canonical liquid droplets. This entropy, stemming from the inter-condensate polymer exchange, makes the droplet merging process dependent on inter-sticker dissociation kinetics. Stronger inter-sticker interaction triggers a kinetic arrest, preventing the condensate merger even at a low density. Our prediction starkly correlates with recent experimental findings on protein-RNA condensates in vitro and in vivo, highlighting the biological relevance of the interplay of kinetics and thermodynamics.

Formation, chemical evolution and solidification of the dense liquid phase of calcium (bi)carbonate.

Metal carbonates, which are ubiquitous in the near-surface mineral record, are a major product of biomineralizing organisms and serve as important targets for capturing anthropogenic CO2 emissions. However, pathways of carbonate mineralization typically diverge from classical predictions due to the involvement of disordered precursors, such as the dense liquid phase (DLP), yet little is known about DLP formation or solidification processes. Using in situ methods we report that a highly hydrated bicarbonate DLP forms via liquid-liquid phase separation and transforms into hollow hydrated amorphous CaCO3 particles. Acidic proteins and polymers extend DLP lifetimes while leaving the pathway and chemistry unchanged. Molecular simulations suggest that the DLP forms via direct condensation of solvated Ca²+⋅(HCO3-)2 complexes that react due to proximity effects in the confined DLP droplets. Our findings provide insight into CaCO3 nucleation that is mediated by liquid-liquid phase separation, advancing the ability to direct carbonate mineralization and elucidating an often-proposed complex pathway of biomineralization.

Higgs inflation via a metastable standard model potential, generalised renormalisation frame prescriptions and predictions for primordial gravitational waves

Higgs Inflation via a metastable Standard Model Higgs Potential is possible if the effective Planck mass in the Jordan frame increases after inflation ends. Here we consider the predictions of this model independently of the dynamics responsible for the Planck mass transition. The classical predictions are the same as for conventional Higgs Inflation. The quantum corrections are dependent upon the conformal frame in which the effective potential is calculated. We generalise beyond the usual Prescription I and II renormalisation frame choices to include intermediate frames characterised by a parameter α. We find that the model predicts a well-defined correlation between the values of the scalar spectral index ns and tensor-to-scalar ratio r. For values of ns varying between the 2-σ Planck observational limits, we find that r varies between 0.002 and 0.005 as ns increases, compared to the classical prediction of 0.003. Therefore significantly larger or smaller values of r are possible, which are correlated with larger or smaller values of ns . In addition, the model can be compatible with the larger values of ns predicted by Early Dark Energy solutions to the Hubble tension, with correspondingly larger values of r. The model can be tested via the detection of primordial gravitational waves by the next generation of CMB polarisation experiments.

Particle response to oscillatory flows at finite Reynolds numbers

The response of spherical particles to oscillatory fluid flow forcing at finite Reynolds numbers exhibits significant deviations from classical analytical predictions due to nonlinear convective contributions. This study employs finite element simulations to explore the long-term (stationary) behavior of such particles across a wide range of conditions, including various external and particle Reynolds numbers, Strouhal numbers, and fluid-to-particle density ratios. Key contributions of this work include determining the range of validity of Tchen's equation of motion for infinitesimal and finite Reynolds numbers and correlating particle response for a wide range of density ratios and flow conditions at high frequency oscillations. This work introduces a modified form of the history drag term in a newly proposed Lagrangian equation of motion. The new equation incorporates a parameter-dependent fractional-order derivative tailored to accommodate nonlinearities due to convective effects. These novel correlations not only extend the operational range of existing model equations but also provide accurate estimates of particle response under a range of external flow conditions, as validated by comparison with numerical solutions of the Navier–Stokes flow around the particles.

Quantum nuclear motion in silicene: Assessing structural and vibrational properties through path-integral simulations

This paper explores the interplay between quantum nuclear motion and anharmonicity, which causes nontrivial effects on the structural and dynamical characteristics of silicene, a two-dimensional (2D) allotrope of silicon with interesting electronic and mechanical properties. Employing path-integral molecular dynamics (PIMD) simulations, we investigate the quantum delocalization of nuclei, unraveling its impact on the behavior of silicene at the atomic scale. Our study reveals that this delocalization induces significant deviations in the structural parameters of silicene, influencing in-plane surface area, bond lengths, angles, compressibility, and overall lattice dynamics. Through extensive simulations, we delve into the temperature-dependent behavior between 25 and 1200 K, unveiling the role of quantum nuclear fluctuations in dictating thermal expansion and phonon spectra. The extent of nuclear quantum effects is assessed by comparing results of PIMD simulations using an efficient tight-binding Hamiltonian, with those obtained from classical molecular dynamics simulations. The observed quantum effects showcase non-negligible deviations from classical predictions, emphasizing the need for accurate quantum treatments in understanding the material’s behavior at finite temperatures. At low T, the 2D compression modulus of silicene decreases by a 14% due to quantum nuclear motion. We compare the magnitude of quantum effects in this material with those in other related 2D crystalline solids, such as graphene and SiC monolayers.

Design and characterisation of an open-jet pressure gradient test rig for an aeroacoustic wind tunnel

This paper summarises an approach to generating controllable pressure gradients within an open-jet configuration for aeroacoustics research. A novel open-jet pressure gradient test rig has been designed for the UNSW Anechoic Wind Tunnel with the help of RANS simulations. A range of pressure gradients is created by adjusting the inclination angle of the top plate to change the cross-sectional area along the streamwise direction gradually. The test model mounting point is located on the bottom plate adjacent to partially opened side walls to allow far-field noise measurements. A comprehensive characterisation of flow quality, pressure gradient parameters and acoustic data quality has been carried out using Particle Imaging Velocimetry (PIV), surface pressure taps, and a microphone array. The test rig produces near-uniform pressure gradient flows at the model mounting point, with momentum Reynolds numbers (Reθ) ranging from 3014 to 11853 and Clauser's pressure gradient parameters (β) from -0.24 to 1.66. The pressure gradients generated by this facility are approximately linear, approaching the model mounting point, and the boundary layer profiles compare favourably with those from conventional hard-walled enclosed pressure gradient wind tunnel facilities. Measurements of airfoil trailing-edge noise from this test rig compare well with classical semi-empirical model predictions. Simultaneous acoustic and flow measurements on a square finite wall-mounted cylinder showcase the capability of this facility for coupled acoustic-flow diagnosis.

Testing quantum reasoning: Developing, validating, and application of a questionnaire

Clear and rigorous quantum reasoning is needed to explain quantum physical phenomena. As pillars of true quantum physical explanations, we suggest specific quantum reasoning derived from quantum physical key ideas. An experiment is suggested to support such a quantum reasoning, in which a quantized radiation field interacts with an optical beam splitter, leading to experimental results conflicting with classical physical predictions. The results, however, can be explained consistently with a quantum reasoning based on the key ideas of probability, superposition, and interference (PSI). In this quantum optical key experiment the optical beam splitter prepares a superposition of single photon states and a Michelson interferometer is used to detect the superposition via controlled propagation phases. Although different single photon experimental setups (aimed at helping students to gain access to foundational issues in quantum physics) have been discussed in the past, the wave-particle dualism bound to classical physics maintains its predominance as an explanation pattern for the interpretation of these experiments. The study presented here investigates the effect of the quantum optical key experiment on the ability of students to use quantum reasoning based on the key ideas of PSI to overcome the naive wave-particle dualism. The current state of relevant studies that test student access to quantum physics can roughly be divided into two distinct areas: one tests how mathematical abilities help them to understand quantum physics and one tests how nonmathematical representations of a set of specific quantum theoretical traits (“Wesenszüge”) lead to a deeper understanding of quantum physics. There is a lack of questionnaires that focus on the idea of developing quantum reasoning based on superposition, probability, and interference of quantum states combined with a real experiment using true quantum light. In the first part of the article, we describe the physical modeling and present the development of the questionnaire. The set of items has been constructed from newly developed items and combined with well-tested ones. The validation of the set addresses qualitative and quantitative methods. In the second part, we give a pre- and poststudy examination of the impact of the quantum optical key experiment on students’ quantum reasoning. A significant increase in the number of students using quantum arguments is based on PSI reasoning for the explanation of an interference, such as the behavior of single photon states. Though the increase is significant, we found only minor changes in a particular issue to the students’ reasoning when approaching quantum physics as illustrated by a sample of answers given in the second part of the article. The concept of quantum states and the principle of superposition still appear particularly difficult. Published by the American Physical Society 2024

Belief-consistent information is most shared despite being the least surprising

In the classical information theoretic framework, information “value” is proportional to how novel/surprising the information is. Recent work building on such notions claimed that false news spreads faster than truth online because false news is more novel and therefore surprising. However, another determinant of surprise, semantic meaning (e.g., information’s consistency or inconsistency with prior beliefs), should also influence value and sharing. Examining sharing behavior on Twitter, we observed separate relations of novelty and belief consistency with sharing. Though surprise could not be assessed in those studies, belief consistency should relate to less surprise, suggesting the relevance of semantic meaning beyond novelty. In two controlled experiments, belief-consistent (vs. belief-inconsistent) information was shared more despite consistent information being the least surprising. Manipulated novelty did not predict sharing or surprise. Thus, classical information theoretic predictions regarding perceived value and sharing would benefit from considering semantic meaning in contexts where people hold pre-existing beliefs.

TabEE: Tabular Embeddings Explanations

Tabular embedding methods have become increasingly popular due to their effectiveness in improving the results of various tasks, including classic databases tasks and machine learning predictions. However, most current methods treat these embedding models as "black boxes" making it difficult to understand the insights captured by the models. Our research proposes a novel approach to interpret these models, aiming to provide local and global explanations for the original data and detect potential flaws in the embedding models. The proposed solution is appropriate for every tabular embedding algorithm, as it fits the black box view of the embedding model. Furthermore, we propose methods for comparing different embedding models, which can help identify data biases that might impact the models' credibility without the user's knowledge. Our approach is evaluated on multiple datasets and multiple embeddings, demonstrating that our proposed explanations provide valuable insights into the behavior of tabular embedding methods. By making these models more transparent, we believe our research will contribute to the development of more effective and reliable embedding methods for a wide range of applications.

Angular momentum and chemical transport by azimuthal magnetorotational instability in radiative stellar interiors

Context. The transport of angular momentum and chemical elements within evolving stars remains poorly understood. Asteroseismic and spectroscopic observations of low-mass main sequence stars and red giants reveal that their radiative cores rotate orders of magnitude slower than classical predictions from stellar evolution models and that the abundances of their surface light elements are too small. Magnetohydrodynamic (MHD) turbulence is considered a primary mechanism to enhance the transport in radiative stellar interiors but its efficiency is still largely uncertain. Aims. We explore the transport of angular momentum and chemical elements due to azimuthal magnetorotational instability, one of the dominant instabilities expected in differentially rotating radiative stellar interiors. Methods. We employed 3D MHD direct numerical simulations in a spherical shell of unstratified and stably stratified flows under the Boussinesq approximation. The background differential rotation was maintained by a volumetric body force. We examined the transport of chemical elements using a passive scalar. Results. We provide evidence of magnetorotational instability for purely azimuthal magnetic fields in the parameter regime expected from local and global linear stability analyses. Without stratification and when the Reynolds number Re and the background azimuthal field strength are large enough, we observed dynamo action driven by the instability at values of the magnetic Prandtl number Pm in the range 0.6 − 1, which is the smallest ever reported in a global setup. When considering stable stratification at Pm = 1, the turbulence is transitional and becomes less homogeneous and isotropic upon increasing buoyancy effects. The transport of angular momentum occurs radially outward and is dominated by the Maxwell stresses when stratification is large enough. We find that the turbulent viscosity decreases when buoyancy effects strengthen and scales with the square root of the ratio of the reference rotation rate Ωa to the Brunt–Väisälä frequency N. The chemical turbulent diffusion coefficient scales with stratification similarly to the turbulent viscosity, but is lower in amplitude so that the transport of chemicals is slower than the one of angular momentum, in agreement with recent stellar evolution models of low-mass stars. Conclusions. We show that the transport induced by azimuthal magnetorotational instability scales somewhat slowly with stratification and may enforce rigid rotations of red giant cores on a timescale of a few thousand years. In agreement with recent stellar evolution models of low-mass stars, the instability transports chemical elements less efficiently than angular momentum.

Modeling the competition between phase separation and polymerization under explicit polydispersity.

The dynamics of phase separation for polymer blends is important in determining the final morphology and properties of polymer materials; in practical applications, this phase separation can be controlled by coupling to polymerization reaction kinetics via a process called 'polymerization-induced phase separation'. We develop a phase-field model for a polymer melt blend using a polymerizing Cahn-Hilliard (pCH) formalism to understand the fundamental processes underlying phase separation behavior of a mixture of two species independently undergoing linear step-growth polymerization. In our method, we explicitly model polydispersity in these systems to consider different molecular-weight components that will diffuse at different rates. We first show that this pCH model predicts results consistent with the Carothers predictions for step-growth polymerization kinetics, the Flory-Huggins theory of polymer mixing, and the classical predictions of spinodal decomposition in symmetric polymer blends. The model is then used to characterize (i) the competition between phase separation dynamics and polymerization kinetics, and (ii) the effect of unequal reaction rates between species. For large incompatibility between the species (i.e. high χ), our pCH model demonstrates that the strength for phase separation directly corresponds to the kinetics of phase separation. We find that increasing the reaction rate k̃, first induces faster phase separation but this trend reverses as we further increase k̃ due to the competition between molecular diffusion and polymerization. In this case, phase separation is delayed for faster polymerization rates due to the rapid accumulation of slow-moving, high molecular weight components.

Revised Passing-Bablok Regression Method for Model Comparison

Type-II regression models are used to compare more than one method that makes the same measurement. The Passing-Bablok regression method, which is one of them, is non-parametric and can yield more successful results than other comparison methods, particularly when there are outliers. In this study, innovations in the calculation of the slope and intercept parameters used in the traditional Passing-Bablok method are proposed. Instead of the median parameter used in the classical model, the use of the trimean parameter is suggested, and the model parameter estimates are adjusted accordingly. The proposed model and classical model predictions were compared on 15 different datasets, eight of which were simulations. It was determined that the proposed model calculations contained fewer errors than the results of the classical method.

Range expansion can promote the evolution of plastic generalism in coarse-grained landscapes.

Phenotypic plasticity is one way for organisms to deal with variable environments through generalism. However, plasticity is not found universally and its evolution may be constrained by costs and other limitations such as complexity: the need for multiple mutational steps before the adaptation is realized. Theory predicts that greater experienced heterogeneity, such as organisms may encounter when spatial heterogeneity is fine-grained relative to dispersal, should favor the evolution of a broader niche. Here we tested this prediction via simulation. We found that, contrary to classical predictions, coarse-grained landscapes can be the most favorable for the evolution of plasticity, but only when populations encounter those landscapes through range expansion. During these range expansions, coarse-grained landscapes select for each step in the complex mutational pathway to plastic generalism by blocking the dispersal of specialists. These circumstances provide ecological opportunities for innovative mutations that change the niche. Our results indicate a new mechanism by which range expansion and spatially structured landscapes interact to shape evolution and reveal that the environments in which a complex adaptation has the highest fitness may not be the most favorable for its evolution.

GVFs in the real world: making predictions online for water treatment

In this paper we investigate the use of reinforcement-learning based prediction approaches for a real drinking-water treatment plant. Developing such a prediction system is a critical step on the path to optimizing and automating water treatment. Before that, there are many questions to answer about the predictability of the data, suitable neural network architectures, how to overcome partial observability and more. We first describe this dataset, and highlight challenges with seasonality, nonstationarity, partial observability, and heterogeneity across sensors and operation modes of the plant. We then describe General Value Function (GVF) predictions—discounted cumulative sums of observations–and highlight why they might be preferable to classical n-step predictions common in time series prediction. We discuss how to use offline data to appropriately pre-train our temporal difference learning (TD) agents that learn these GVF predictions, including how to select hyperparameters for online fine-tuning in deployment. We find that the TD-prediction agent obtains an overall lower normalized mean-squared error than the n-step prediction agent. Finally, we show the importance of learning in deployment, by comparing a TD agent trained purely offline with no online updating to a TD agent that learns online. This final result is one of the first to motivate the importance of adapting predictions in real-time, for non-stationary high-volume systems in the real world.

Laboratory demonstration of the impact of weak interfaces and layered rock properties on hydraulic fracture containment and height growth

Hydraulic fracturing and waterflooding are both widely applied methods for improving the recovery of oil and gas resources. These methods have increasing commonality because many waterfloods are being carried out at high enough pressure to generate hydraulic fractures. Even so, it is challenging for engineers to make an optimal wellbore pressure design for layered and otherwise complex underground formations. An overly aggressive injection pressure may lead to uncontrollable fracture height growth into non-producing layers adjacent to the reservoir. In contrast, when using classical but highly simplified height growth models, the pressure limits can be far too conservative which may lead to lower recovery rates and inefficient use of resources invested in developing producing reservoirs. Therefore, it is necessary to investigate the mechanism of fracture height growth while considering the coupling effect from multiple dominated factors. This research contributes an experimental approach to evaluating the role of stresses, weak interfaces, and mechanical properties of a three-layer system in promoting or containing hydraulic fracture height growth from a central reservoir into neighboring barrier layers. In all cases, the experiments agree that the pressure required to induce substantial height growth exceeds the stress applied to the barrier layers and is far above classical predictions. Additionally, when the reservoir layer is softer than the barriers, the containment is sustained to even higher pressures than for layers with similar material properties. Finally, the experiments show that permeability of the barrier layer can induce a more sudden transition to uncontrolled height growth when fracture reaches the bedding interfaces. Hydraulic fracture height growth is mitigated by weak interfaces between layers. Unstable height growth typically requires fluid pressure to exceed the in-situ stress in the bounding layer(s). Contrasting layer stiffness and permeability often leads to further mitigation of height growth.

Partial protection from fluctuating selection leads to evolution towards wider population size fluctuation and a novel mechanism of balancing selection.

When a population is partially protected from fluctuating selection, as when a seed bank is present, variance in fitness will be reduced and reproductive success of the population will be promoted. This study further investigates the effect of such a 'refuge' from fluctuating selection using a mathematical model that couples demographic and evolutionary dynamics. While alleles that cause smaller fluctuations in population density should be positively selected according to classical theoretic predictions, this study finds the opposite: alleles that increase the amplitude of population size fluctuation are positively selected if population density is weakly regulated. Under strong density regulation with a constant carrying capacity, long-term maintenance of polymorphism caused by the storage effect emerges. However, if the carrying capacity of the population is oscillating, mutant alleles whose fitness fluctuates in the same direction as population size are positively selected, eventually reaching fixation or intermediate frequencies that oscillate over time. This oscillatory polymorphism, which requires fitness fluctuations that can arise with simple trade-offs in life-history traits, is a novel form of balancing selection. These results highlight the importance of allowing joint demographic and population genetic changes in models, the failure of which prevents the discovery of novel eco-evolutionary dynamics.

Dissipative effects in nonideal supercapacitors and batteries

The literature is full of reports containing very high specific energy (E/W h g−1) and power (P/W g−1) values for different classes of electrochemical energy storage devices (EESD) based on distinct types of microstructured and nanosized advanced electrode materials (AEM), such as supercapacitors and batteries. In most cases, the evaluation of energy and power characteristics for EESD is carried out based on classic theory for electrical systems (Esc = CU2/2 or Ebat = CU), where the charge carriers are assumed as massless point entities, i.e., electrons and holes. However, EESDs operate simultaneously with the transport of electronic and ionic charges involving massive/finite-sized charge carriers (e.g., anions and cations) with pronounced steric effects that control the overall charge transport in migration and/or diffusion phenomena in viscous media. To overcome the inherent theoretical difficulty in studying porous and redox-active electrode materials used in AEMs, and considering the typical case where a robust theoretical model is absent to represent the different classes of EEDs, we propose a phenomenological analysis where the use of an empirical correction parameter denoted as the deviation coefficient (γ) representing the discrepancies from the classic electric predictions results in more reliable specific energy and power values. From the analysis of different experimental data obtained for laboratory-made devices, we verified that using Esc = CU2/2 and Ebat = CU equations can result in important discrepancies characterized by γ ≠ 1. Finally, we discussed the distinction between well-behaved supercapacitors and ill-defined EESD systems in light of γ-values.

Observing single particles beyond the Rindler horizon

We show that Minkowski single-particle states localized beyond the horizon modify the Unruh thermal distribution in an accelerated frame. This means that, contrary to classical predictions, accelerated observers can reveal particles emitted beyond the horizon. The method we adopt is based on deriving the explicit Wigner characteristic function for the complete description of the quantum field in the noninertial frame and can be generalized to general states.Received 1 December 2021Revised 9 March 2022Accepted 21 March 2023DOI:https://doi.org/10.1103/PhysRevA.107.L030203©2023 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasUnruh effectAtomic, Molecular & Optical

An Innovative Method to Analyze the Hydraulic Fracture Reopening Pressure of Hot Dry Rock.

This paper focuses on a new test method and theoretical model for measuring and evaluating the reopening pressure during hot dry rock hydraulic fracturing. Firstly, rock blocks of four lithologies were collected from the hot dry rock strata. Hydraulic fracturing tests at high temperatures in real-time were conducted using drilled cubic specimens and drilled cubic specimens with a pre-crack. Breakdown pressure, reopening pressure, and fracture toughness were measured, respectively. In addition, Brazilian splitting tests at high temperatures in real-time were performed using Brazilian disc specimens to measure tensile strength. Secondly, an empirical equation for evaluating the reopening pressure during hot dry rock secondary fracturing was developed based on fracture mechanics and hydraulic fracturing theory. Third, the values calculated by the new equation, considering breakdown pressure, fracture toughness, and tensile strength, were compared to the values determined by the classical equation and to measurement results. It was found that the new equation predicted closer reopening pressure to the measurement results, regardless of the lithology of the hot dry rock. Moreover, with increasing temperature in the specimens, the error between the value calculated by the new equation and the measurement value remained low. In contrast, the difference between the classical equation predictions and the measurement results was widened. In addition, the reopening pressure was positively correlated with tensile strength and fracture toughness. Variations in lithology and temperature affected tensile strength and fracture toughness, which then changed the hot dry rock reopening pressure.

Compression buckling of elastically supported cylindrical shells with Bend/Twist coupling

Composite cylindrical shells are widely used in space launch systems due to their high load-carrying capability and for being lightweight. However, these structures are prone to buckling phenomena at much lower loads than classical predictions for perfect cylinders. This work aims to develop data-driven empirical expressions to calculate the upper and lower bound values of cylindrical shells under linear compression loads with various boundary conditions together with various levels of bend/twist anisotropy. The inclusion of bend/twist coupling effects is a major development. To do so, the critical buckling load for laminated thin-walled cylindrical shells on elastic foundations with low, medium and high levels of bend/twist anisotropy were investigated. Then, an analysis-driven design approach is proposed to estimate the upper and lower bounds of buckling loads for axial, radial and tangential elastic foundations. Subsequently, parametric studies were performed with various combinations of bend/twist anisotropy and laminate thicknesses using Abaqus finite element models, and a comparison was made with the proposed data-driven empirical buckling load expressions. Finally, results show that the detrimental effect of boundary conditions and inherent bend/twist anisotropy could lead to a 61% reduction in buckling load, providing a need for detailed studies in this area.