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At least 235 records · Page 13

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗

Effects of local compositional and structural disorder on vacancy formation in entropy-stabilized oxides from first-principles

Entropic stabilization has evolved into a strategy to create new oxide materials and realize novel functional properties engineered through the alloy composition. Achieving an atomistic understanding of these properties to enable their design, however, has been challenging due to the local compositional and structural disorder that underlies their fundamental structure-property relationships. Here, we combine high-throughput atomistic calculations and linear regression algorithms to investigate the role of local configurational and structural disorder on the thermodynamics of vacancy formation in (MgCoNiCuZn)O-based entropy-stabilized oxides (ESOs) and their influence on the electrical properties. We find that the cation-vacancy formation energies decrease with increasing local tensile strain caused by the deviation of the bond lengths in ESOs from the equilibrium bond length in the binary oxides. The oxygen-vacancy formation strongly depends on structural distortions associated with the local configuration of chemical species. Vacancies in ESOs exhibit deep thermodynamic transition levels that inhibit electrical conduction. By applying the charge-neutrality condition, we determine that the equilibrium concentrations of both oxygen and cation vacancies increase with increasing Cu mole fraction. Our results demonstrate that tuning the local chemistry and associated structural distortions by varying alloy composition acts an engineering principle that enables controlled defect formation in multi-component alloys.

36 MATERIALS SCIENCE↗

Performance of wave function and Green's function methods for non-equilibrium many-body dynamics

Theoretical descriptions of the non-equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on the truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In this work, we select representative cases of each of the methods and address how these complementary approaches capture the dynamics driven by intense field perturbations to non-equilibrium states. Under strong driving, the systems are characterized by strong entanglement of the single-particle density matrix and natural populations approaching those of a strongly interacting equilibrium system. We generate a representative set of results that are numerically exact and form a basis for a critical comparison of the distinct families of methods. We demonstrate that the compressed formulation based on similarity-transformed Hamiltonians (coupled-cluster approach) is practically exact in weak fields and, hence, weakly or moderately correlated systems. Coupled cluster, however, struggles for strong driving fields, under which the system exhibits strongly correlated behavior, as measured by the von Neumann entropy of the single-particle density matrix. The dynamics predicted by Green's functions in the (widely popular) G W approximation are less accurate, but improve significantly upon the mean-field results in the strongly driven regime. Published by the American Physical Society 2025

Reeves, Cian C. (ORCID:0009000642581845)↗

Enhanced resistance to decay of imprinted nanopatterns in thin films by bare nanoparticles compared to polymer-grafted nanoparticles

We extend a previous study on the influence of nanoparticles on the decay of nanoimprinted polymer film patterns to compare the effects of “bare” silica (SiO 2 ) nanoparticles and SiO 2 nanoparticles with grafted polymer layers having the same chemical composition as the polymer matrix. This method involves nanoimprinting substrate-supported polymer films using a pattern replicated from a digital versatile disc (DVD), and then annealing the patterned polymer nanocomposite films at elevated temperatures to follow the decay of the topographic surface pattern with time by atomic force microscopy imaging after quenching. We quantified the relaxation of the pattern height (“slumping”) and determined the relaxation time τ for this pattern decay process as a function of nanoparticle filler type and concentration to determine how nanoparticle additives influence relative film stability. Attractive interactions between the bare nanoparticles and the polymer matrix significantly enhance the thermal resilience of the nanopatterns to decay, compared to those of the particle brushes, wherein the particle core interactions are screened from the matrix via the brush layer. A novel aspect of this method is that it readily lends itself to in situ film relaxation measurements in a manufacturing context. We observe that the relaxation time of the pattern relaxation exhibits entropy–enthalpy compensation in the free energy parameters governing the pattern relaxation process as a function of temperature, irrespective of the NP system used, consistent with our previous experimental and computational studies.

36 MATERIALS SCIENCE↗

Orientation dependence of the effect of short-range ordering on the plastic deformation of a medium entropy alloy

Multi-principal-element alloys (also known as medium and high entropy alloys) offer a much larger and richer design space than conventional alloys, providing opportunities for discovering new functionalities and their governing physics. Some of these alloys exhibit an outstanding combination of high strength and ductility, linked to the activation of various deformation modes triggered by low-energy stacking faults. However, a pressing question remains: Is the plasticity of medium- and high-entropy alloys governed only by stacking fault energy, or does atomic short-range order (SRO) play a role? Here, to answer this, we investigated how SRO affects the deformation in single-crystalline NiCoCr, with previous contradictory findings. First, we established unique experimental evidence for SRO formation in bulk single crystals using high-energy synchrotron transmission X-Ray Diffraction. By tuning the degree of SRO by aging at high temperatures, twinning density and strain-induced martensitic phase transformation can be significantly increased in the [110] and [111] orientations under tension, increasing the tensile ductility; yet, no increase was observed along the [001] orientation due to lack of TWinning-Induced Plasticity (TWIP) or TRansformation-Induced Plasticity (TRIP), indicating a strong crystallographic orientation dependence. Our first-principles thermodynamic calculations unequivocally show SRO exists and governs the observed microstructural evolution and deformation hardening behavior. Here we find direct proof that SRO triggers a simultaneous TWIP and TRIP in NiCoCr, a rare microstructural evolution path. Our findings establish that the interplay of SRO and plasticity could be exploited to alter deformation modes and yield unprecedented mechanical response in medium- and high-entropy alloys.

36 MATERIALS SCIENCE↗

Holographic Weyl anomalies for 4d defects in 6d SCFTs

In this note, we study 1/4- and 1/2-BPS co-dimension two superconformal defects in the 6d N = (2, 0) A N–1 SCFT at large N using their holographic descriptions as solutions of 11d supergravity. In this regime, we are able to compute the defect contribution to the sphere entanglement entropy and the change in the stress-energy tensor one-point function due to the presence of the defect using holography. From these quantities, we are then able to unambiguously compute the values for two of the twenty-nine total Weyl anomaly coefficients that characterize 4d conformal defects in six and higher dimensions. We are able to demonstrate the consistency of the supergravity description of the defect theories with the average null energy condition on the field theory side. For each class of defects that we consider, we also show that the A-type Weyl anomaly coefficient is non-negative. Lastly, we uncover and resolve a discrepancy between the on-shell action of the 7d 1/4-BPS domain wall solutions and that of their 11d uplift.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Page curve for reflected entropy

We study the reflected entropy $S_{R}$ in the West Coast Model, a toy model of black hole evaporation consisting of JT gravity coupled to end-of-the-world branes. We demonstrate the validity of the holographic duality relating it to the entanglement wedge cross section away from phase transitions. Further, we analyze the important non-perturbative effects that smooth out the discontinuity in the phase transition. By performing the gravitational path integral, we obtain the reflected entanglement spectrum analytically. The spectrum takes a simple form consisting of superselection sectors, which we interpret as a direct sum of geometries, a disconnected one and a connected one involving a closed universe. We find that area fluctuations of $\textit{O}$$\sqrt{G_N}$ spread out the $S_{R}$ phase transition in the canonical ensemble, analogous to the entanglement entropy phase transition. We also consider a Renyi generalization of the reflected entropy and show that the location of the phase transition varies as a function of the Renyi parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

c -functions in higher-derivative flows across dimensions

In the context of gravitational theories describing renormalization group flows across dimensions via AdS/CFT, we study the role of higher-derivative corrections to Einstein gravity. We use the Null Energy Condition to derive monotonicity properties of candidate holographic central charges formed by combinations of metric functions. We also implement an entropic approach to the characterization of the four-derivative flows using the Jacobson-Myers functional and demonstrate, under reasonable conditions, monotonicity of certain terms in the entanglement entropy via the appropriate generalization of the Ryu-Takayanagi prescription. In particular, we show that any flow from a higher dimensional theory to a holographic CFT 2 satisfies a type of monotonicity. We also uncover direct relations between NEC-motivated and entropic central charges.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Data-driven analysis and prediction of stable phases for high-entropy alloy design

High-entropy alloys (HEAs) represent a promising class of materials with exceptional structural and functional properties. However, their design and optimization pose challenges due to the large composition-phase space coupled with the complex and diverse nature of the phase formation dynamics. In this study, a data-driven approach that utilizes machine learning (ML) techniques to predict HEA phases and their composition-dependent phases is proposed. By employing a comprehensive dataset comprising 5692 experimental records encompassing 50 elements and 11 phase categories, we compare the performance of various ML models. Our analysis identifies the most influential features for accurate phase prediction. Furthermore, the class imbalance is addressed by employing data augmentation methods, raising the number of records to 1500 in each category, and ensuring a balanced representation of phase categories. The results show that XGBoost and Random Forest consistently outperform the other models, achieving 86% accuracy in predicting all phases. Additionally, this work provides an extensive analysis of HEA phase formers, showing the contributions of elements and features to the presence of specific phases. We also examine the impact of including different phases on ML model accuracy and feature significance. Notably, the findings underscore the need for ML model selection based on specific applications and desired predictions, as feature importance varies across models and phases. This study significantly advances the understanding of HEA phase formation, enabling targeted alloy design and fostering progress in the field of materials science.

36 MATERIALS SCIENCE↗

Fast and converged classical simulations of evidence for the utility of quantum computing before fault tolerance

A recent quantum simulation of observables of the kicked Ising model on 127 qubits implemented circuits that exceed the capabilities of exact classical simulation. We show that several approximate classical methods, based on sparse Pauli dynamics and tensor network algorithms, can simulate these observables orders of magnitude faster than the quantum experiment and can also be systematically converged beyond the experimental accuracy. Our most accurate technique combines a mixed Schrödinger and Heisenberg tensor network representation with the Bethe free entropy relation of belief propagation to compute expectation values with an effective wave function–operator sandwich bond dimension >16,000,000, achieving an absolute accuracy, without extrapolation, in the observables of <0.01, which is converged for many practical purposes. We thereby identify inaccuracies in the experimental extrapolations and suggest how future experiments can be implemented to increase the classical hardness.

Science & Technology - Other Topics↗

Thermodynamic Modeling of Point Defects in Triple Conducting Perovskite Ba 0.95 La 0.05 FeO 3- $_δ$ with Incorporation of the Hydride Defect Formation Reaction for Solid Oxide Cells

Distinct from the proton defect, the hydride defect species may be present in certain perovskite materials in reducing environments such as in fuel electrodes of solid oxide cells (SOCs) or on the reducing side of ceramic membranes. A generalized defect thermodynamic model was developed for the triple-conducting perovskites (La,Ba)Fe 1-x M x O 3-δ (M = Y and Zr) to allow inclusion of the hydride defect formation reaction in addition to the other three main defect reactions, namely, the oxygen vacancy formation, hydration, and charge disproportionation reactions. This comprehensive defect model also allows the incorporation of polynomial functional forms of oxygen nonstoichiometry δ to describe the defect reaction energies and entropies and to enable refinements of the defect reaction equilibrium constants in the defect thermodynamic analysis. As a first step, the developed model is applied to the Ba 0.95 La 0.05 FeO 3-δ material as an illustrative system to obtain its Brouwer diagrams with both the proton and hydride defects in relevant SOC conditions, particularly for more reducing environments. In conclusion, the results provide direct guidance on the influence of electronic and ionic defect concentrations upon thermodynamic properties and ultimately on the performance of Ba 0.95 La 0.05 FeO 3-δ and potentially other (La,Ba)Fe 1-x M x O 3-δ perovskite materials involved in SOC applications.

25 ENERGY STORAGE↗

A High‐Rate Li–CO 2 Battery Enabled by 2D Medium‐Entropy Catalyst

Abstract Lithium‐air batteries based on CO 2 reactant (Li–CO 2 ) have recently been of interest because it has been found that reversible Li/CO 2 electrochemistry is feasible. In this study, a new medium‐entropy cathode catalyst, (NbTa) 0.5 BiS 3 , that enables the reversible electrochemistry to operate at high rates is presented. This medium entropy cathode catalyst is combined with an ionic liquid‐based electrolyte blend to give a Li–CO 2 battery that operates at high current density of 5000 mA g −1 and capacity of 5000 mAh g −1 for up to 125 cycles, far exceeding reported values in the literature for this type of battery. The higher rate performance is believed to be due to the greater stability of the multi‐element (NbTa) 0.5 BiS 3 catalyst because of its higher entropy compared to previously used catalysts with a smaller number of elements with lower entropies. Evidence for this comes from computational studies giving very low surface energies (high surface stability) for (NbTa) 0.5 BiS 3 and transmission electron microscopystudies showing the structure being retained after cycling. In addition, the calculations indicate that Nb‐terminated surface promotes Li–CO 2 electrochemistry resulting in Li 2 CO 3 and carbon formation, consistent with the products found in the cell. These results open new direction to design and develop high‐performance Li–CO 2 batteries.

25 ENERGY STORAGE↗

In situ study on the compression deformation of MoNbTaVW high-entropy alloy

The excellent mechanical properties of high-entropy alloys (HEAs) make them promising materials for advances in science and technology. However, the underlying mechanism of plastic deformation is not well understood. In situ experiments are urgently required to provide a fundamental understanding of the plastic deformation under high pressure. We performed in situ synchrotron X-ray diffraction (XRD) experiments to study compression deformation behavior of the HEA MoNbTaVW in a radial diamond anvil cell (rDAC). Our results show that the strength and ratio of the stress-to-shear modulus values are ~1.5 and 3 times that of pure tungsten (W), respectively. MoNbTaVW showed plastic deformation above 5 GPa and displayed a much stronger texture. In this work, we found that the active dislocation behavior is mainly responsible for the high strength in MoNbTaVW under compression. This unique technique opens a new avenue to investigate the in situ mechanical properties and their mechanism in other types of HEAs.

36 MATERIALS SCIENCE↗

Low-energy enhancement in the magnetic dipole γ-ray strength functions of heavy nuclei

A low-energy enhancement (LEE), which was observed experimentally in the gamma-ray strength function (γSF) describing the decay of compound nuclei, would have profound effects on r-process nucleosynthesis if it persists in heavy neutron-rich nuclei. The LEE was shown to be a feature of the magnetic dipole (M1) strength function in configuration-interaction shell-model calculations in medium-mass nuclei. However, its existence in heavy open-shell nuclei remains an open question. Here, using a combination of many-body methods, we identify a LEE in the M1 γSFs of heavy samarium nuclei. In particular, we use the static-path plus random-phase approximation (SPA+RPA), which includes static and small-amplitude quantal fluctuations beyond the mean field. Using the SPA+RPA strength as a prior, we apply the maximum-entropy method (MEM) to obtain finite-temperature M1 γSFs from exact imaginary-time response functions calculated with the shell model Monte Carlo (SMMC) method. We find that the slope of the LEE in samarium isotopes is roughly independent of the average initial energy over a wide range below the neutron separation energy. As the neutron number increases, strength transfers to a low-energy excitation, which we interpret as the scissors mode built on top of excited states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The expressivity of classical and quantum neural networks on entanglement entropy

Abstract Analytically continuing the von Neumann entropy from Rényi entropies is a challenging task in quantum field theory. While then-th Rényi entropy can be computed using the replica method in the path integral representation of quantum field theory, the analytic continuation can only be achieved for some simple systems on a case-by-case basis. In this work, we propose a general framework to tackle this problem using classical and quantum neural networks with supervised learning. We begin by studying several examples with known von Neumann entropy, where the input data is generated by representing$${\text {Tr}}\rho _A^n$$ Tr ρ A n with a generating function. We adopt KerasTuner to determine the optimal network architecture and hyperparameters with limited data. In addition, we frame a similar problem in terms of quantum machine learning models, where the expressivity of the quantum models for the entanglement entropy as a partial Fourier series is established. Our proposed methods can accurately predict the von Neumann and Rényi entropies numerically, highlighting the potential of deep learning techniques for solving problems in quantum information theory.

Physics↗

Inclusive curvaturelike framework for describing dissipation: Metriplectic 4-bracket dynamics

An inclusive framework for joined Hamiltonian and dissipative dynamical systems that are thermodynamically consistent, i.e., preserve energy and produce entropy, is given. The dissipative dynamics of the framework is based on the metriplectic 4-bracket , a quantity like the Poisson bracket defined on phase space functions, but unlike the Poisson bracket has four slots with symmetries and properties motivated by Riemannian curvature. Metriplectic 4-bracket dynamics is generated using two generators, the Hamiltonian and the entropy, with the entropy being a Casimir of the Hamiltonian part of the system. The formalism includes known previous binary bracket theories for dissipation or relaxation as special cases. Rich geometrical significance of the formalism and methods for constructing metriplectic 4-brackets are explored. Many examples of both finite and infinite dimensions are given.

Physics↗

An Entropy-Maximization Approach to Automated Training Set Generation for Interatomic Potentials

Machine learning-based interatomic potentials are currently garnering a lot of attention as they strive to achieve the accuracy of electronic structure methods at the computational cost of empirical potentials. Given their generic functional forms, the transferability of these potentials is highly dependent on the quality of the training set, the generation of which can be highly labor-intensive. Good training sets should at once contain a very diverse set of configurations while avoiding redundancies that incur cost without providing benefits. We formalize these requirements in a local entropy-maximization framework and propose an automated sampling scheme to sample from this objective function. We show that this approach generates much more diverse training sets than unbiased sampling and is competitive with hand-crafted training sets.

74 ATOMIC AND MOLECULAR PHYSICS↗

Transferable predictions of energetic and structural properties for refractory solid solution alloys across chemical compositions

We present a data-efficient approach to train graph neural networks (GNNs) on density functional theory (DFT) data for accurate and transferable predictions of energetic and structural properties of refractory solid solution alloys in the niobium-tantalum-vanadium (Nb-Ta-V) chemical space. We start by training the GNN model only on DFT data that describes refractory binary alloys niobium-tantalum (Nb-Ta), niobium-vanadium (Nb-V), and tantalum-vanadium (Ta-V) to predict formation enthalpy and root mean squared displacement. Once trained, the GNN predictions are tested on DFT data describing refractory ternary alloys Nb-Ta-V. While, unsurprisingly, direct transferability from binary to ternary is not sufficiently accurate, augmenting the training with only 1% of the available ternary data (uniformly distributed across the entire range of chemical compositions) improves significantly the quality of the GNN predictions. For comparison, we assess the transferability in the opposite direction by training GNN models on ternary Nb-Ta-V data and making predictions on binaries Nb-Ta, Nb-V, and Ta-V, which exhibits notably higher predictive errors. The proposed methodology, which favors transferability from lower-component to higher-component alloys, offers an efficient path towards avoiding the curse of dimensionality incurred when collecting DFT data for discovery and design of multi-component disordered alloys.

Density functional theory calculations↗