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At least 19 records

Fuel‐Driven π‐Conjugated Superstructures to Form Transient Conductive Hydrogels

Despite advances in creating dissipative materials with transient properties, such as hydrogels and active droplets, their application remains confined to temporal changes in structural properties. Developing out-of-equilibrium materials whose electronic functions are parameterized by a chemical reaction cycle is challenging. Yet, this class of materials is required to construct biomimetic materials. In contrast to traditional chemical reaction cycles that exploit molecularly dissolved building blocks at thermodynamic equilibrium, we show that fiber structures derived from reactive naphthalene diimide (NDI) building blocks can be used as resting states to form far-from-equilibrium conductive hydrogels after the addition of chemical fuels. Upon fueling the NDI-derived fibers, a dual-component activation and deactivation pathway is deduced by kinetic analysis and is absent when using a molecularly dissolved resting state. Investigating the solid-state morphologies of the structures formed throughout the fuel-driven reaction cycle using cryo-EM reveals that the resting thermodynamic fibers evolve to transient thicker fibrils and layered superstructures. We show that the transient redox-active hydrogels exhibit a nearly threefold increase in electrical conductivity upon fuel consumption before reverting to their original value over hours. In conclusion, these far-from-equilibrium materials are potential candidates in applications such as programmable biorobotics and chemical computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic Surface Incorporation of Pb 2+ Ions at the Actively Dissolving Calcite (104) Surface

The reaction of dissolved Pb 2+ with calcite surfaces at near-equilibrium conditions involves adsorption of Pb 2+ and precipitation of secondary heteroepitaxial Pb-carbonate minerals. A more complex behavior is observed under far-from-equilibrium conditions, including strong inhibition of calcite dissolution, development of microtopography, and near-surface incorporation of multiple monolayers (ML) of Pb 2+ without precipitation of secondary phases [where 1 ML ≡ 1 Ca/20.2 Å 2 , the crystallographic site density of the calcite (104) lattice plane]. However, the mechanistic controls governing far-from-equilibrium reactivity are not well understood. Here, in this study, we observe the interfacial incorporation of dissolved Pb 2+ during the dissolution of calcite (104) surfaces at pH ~3.7 in a flow-through reaction cell, revealing the formation of a ~1 nm thick Pb-rich calcite layer with a total Pb coverage of ~1.4 ML. These observations of the sorbed Pb distribution used resonant anomalous X-ray reflectivity, X-ray fluorescence, and nanoinfrared atomic force microscopy. We propose that this altered surface layer represents a novel sorption mode that is stabilized by conditions of sustained disequilibrium. This behavior may significantly impact the transport of dissolved metals during disequilibrium processes occurring in acid mine drainage and subsurface CO 2 injection and, if appropriately accounted for, could improve the predictive capability of geochemical reactive-transport models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled feldspar dissolution and secondary mineral precipitation in batch systems: 6. Labradorite dissolution, calcite growth, and clay precipitation at 60 °C and pH 8.2–8.4

Here, we conducted experiments on concurrent labradorite dissolution, calcite precipitation, and clay precipitation in batch reactor systems and tracked reaction processes using multiple isotope tracers. Labradorite was chosen for its role as a major and reactive component in basalt; the experiments thus directly impact our understanding of CO 2 storage in basalt aquifers and enhanced rock weathering. We doped initial solutions with 29 Si, 43 Ca, and Ca 13 CO 3 (s). Experiments were conducted at 60 °C and pH ~ 8.3 for up to 840 h, with isotope ratios in the experimental aqueous solutions measured using MC-ICP-MS. Unidirectional rates of labradorite dissolution near equilibrium were approximately two orders of magnitude slower than far-from-equilibrium rates reported in the literature. Calcite growth occurred near equilibrium and the rates were limited by the labradorite dissolution rates. In the steady state phase, the interplay of these three heterogeneous reactions—labradorite dissolution, calcite growth, and clay precipitation—results in a coupled system that approaches a near-equilibrium state. The system does not reach true equilibrium because labradorite continues to dissolve, albeit at a much slower rate near equilibrium. The overall reaction can be approximated as, Na 0.4 Ca 0.6 Al 1.6 Si 2.4 O 8 + 0.6HCO 3 - + 1·.7H 2 O + 0.4H + → 0.4Na + + 0.6CaCO 3(s) + 0.5Al 2 Si 2 O 5 (OH) 4(s) + 0.6Al(OH) 4 - + 1.4SiO 2 o (aq). The experimental results show that using short-term far-from-equilibrium rate constants would lead to an overestimation of feldspar weathering rates at the Earth’s surface (e.g., basalt weathering and enhanced rock weathering) and CO 2 mineralization in basalt aquifers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning enabled discovery of superhard and ultrahard carbon polymorphs

The demand for multifunctional materials has motivated the move from near-equilibrium materials to metastable i.e. out-of-equilibrium phases that can meet several desired target properties. The search for such metastable phases with exotic properties is non-trivial and often serendipitous. Inverse design approaches based on evolutionary search have been powerful tools, but such traditional searches have focused on identifying primarily stable and metastable materials with the lowest enthalpy. The inverse design of materials, with a focus on a desired property such as, for example, hardness is a challenging task because of the expensive computational cost involved in sampling multiple structures. The recent advances in machine learning have brought new powerful AI techniques to the forefront which can potentially revolutionize the inverse design and discovery of materials, especially metastable phases capable of meeting multifunctionality. Here, in this work, we develop and apply an automated reinforcement learning workflow for inverse design that integrates first principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the superhard and ultrahard metastable phases of Carbon. We demonstrate an automatic machine learning based inverse design workflow to map new undiscovered metastable states ranging from near equilibrium to those far-from-equilibrium that satisfy multiple property objectives, specifically bulk moduli, shear moduli and hardness. We create a comprehensive library of carbon stable and metastable phases with varying hardness and subsequently shortlist 10 top performing candidate carbon structures, including two newly reported phases, based on their hardness and characterize their temperature dependent mechanical properties. A neural network model is built using featurization of allotropes of carbon to predict the quasi-harmonic Gibbs free energies. The Gibbs free energies of the top performing phases are analyzed to get an estimate of the experimental synthesizability of these superhard and ultrahard carbon phases. In general, we show using machine learning based inverse design approaches how hitherto inaccessible metastable states can be identified and potentially synthesized to meet the demand for multifunctional materials.

Balasubramanian, Karthik [Univ. of Illinois, Chica↗

Grain boundary metastability controls irradiation resistance in nanocrystalline metals

Grain boundaries (GBs) in polycrystalline materials are powerful sinks for irradiation defects. While standard theories assume that a GB’s efficiency as a sink is defined solely by its character before irradiation, recent evidence conclusively shows that the irradiation sink efficiency is a highly dynamic property controlled by the intrinsic metastability of GBs under far-from-equilibrium irradiation conditions. In this paper, we reveal that the denuded (i.e., defect-free) zone, typically the signature of a strong sink, can collapse as irradiation damage accumulates. We propose a radiation damage evolution model that captures this behavior based on the emergence of a series of irradiation defect-enabled metastable GB microstate changes that dynamically alter the ability of the GB to absorb further damage. We show that these microstate changes control further defect absorption and give rise to the formation of a defect network that manifests itself as a net Nye-tensor signal detectable via lattice curvature experiments.

36 MATERIALS SCIENCE↗

MP-ALOE: an r2SCAN dataset for universal machine learning interatomic potentials

We present MP-ALOE, a dataset of nearly 1 million DFT calculations using the accurate r2SCAN meta-generalized gradient approximation. Covering 89 elements, MP-ALOE was created using active learning and primarily consists of off-equilibrium structures. We benchmark a machine learning interatomic potential trained on MP-ALOE, and evaluate its performance on a series of benchmarks, including predicting the thermochemical properties of equilibrium structures; predicting forces of far-from-equilibrium structures; maintaining physical soundness under static extreme deformations; and molecular dynamic stability under extreme temperatures and pressures. MP-ALOE shows strong performance on all of these benchmarks and is made public for the broader community to utilize.

Kuner, Matthew C↗

Extended X-ray absorption spectroscopy using an ultrashort pulse laboratory-scale laser-plasma accelerator

Laser-driven compact particle accelerators can provide ultrashort pulses of broadband X-rays, well suited for undertaking X-ray absorption spectroscopy measurements on a femtosecond timescale. Here the Extended X-ray Absorption Fine Structure (EXAFS) features of the K-edge of a copper sample have been observed over a 250 eV window in a single shot using a laser wakefield accelerator, providing information on both the electronic and ionic structure simultaneously. This capability will allow the investigation of ultrafast processes, and in particular, probing high-energy-density matter and physics far-from-equilibrium where the sample refresh rate is slow and shot number is limited. For example, states that replicate the tremendous pressures and temperatures of planetary bodies or the conditions inside nuclear fusion reactions. Using high-power lasers to pump these samples also has the advantage of being inherently synchronised to the laser-driven X-ray probe. A perspective on the additional strengths of a laboratory-based ultrafast X-ray absorption source is presented.

43 PARTICLE ACCELERATORS↗

Crack mitigation in additively manufactured AlCrFe 2 Ni 2 high-entropy alloys through engineering phase transformation pathway

The far-from-equilibrium solidification during additive manufacturing often creates large residual stresses that induce solid-state cracking. Here we present a strategy to suppress solid-state cracking in an additively manufactured AlCrFe 2 Ni 2 high-entropy alloy via engineering phase transformation pathway. We investigate the solidification microstructures formed during laser powder-bed fusion and directed energy deposition, encompassing a broad range of cooling rates. At high cooling rates (10 4 –10 6 K/s), we observe a single-phase BCC/B2 microstructure that is susceptible to solid-state cracking. At low cooling rates (10 2 –10 4 K/s), FCC phase precipitates out from the BCC/B2 matrix, resulting in enhanced ductility (~10 %) and resistance to solid-state cracking. Site-specific residual stress/strain analysis reveals that the ductile FCC phase can largely accommodate residual stresses, a feature which helps relieve residual strains within the BCC/B2 phase to prevent cracking. Our work underscores the value of exploiting the toolbox of phase transformation pathway engineering for material design during additive manufacturing.

36 MATERIALS SCIENCE↗

Ultrafast nano-imaging and nano-spectroscopy

Ultrafast pump–probe nano-imaging combines scanning probe-based optical near-field microscopy with ultrafast spectroscopy to enable imaging with deep sub-wavelength spatial resolution, femtosecond temporal resolution and simultaneous spectral resolution. Ultrafast nano-imaging has gained increased attention for its ability to provide far-from-equilibrium excitation and excited-state contrast. With coherent and nonlinear probing, coupled electron, spin and lattice dynamics on elementary timescale and length scale can be resolved. Through nano-movies, ultrafast nano-imaging visualizes correlated quantum dynamics underlying the properties of solid-state materials, semiconductors, molecular electronic, photonic, photovoltaic and other functional materials. With nanometre spatial resolution, this method probes elementary dynamic processes across multiple length scales that are otherwise obscured in conventional ultrafast spectroscopy in which heterogeneities are spatially averaged. Furthermore, this Primer describes the theoretical background and experimental implementation of ultrafast nano-imaging; signal interpretation and modelling; representative examples and a perspective for the future development of the field.

Microscopy↗

Modeling active nematics via the nematic locking principle

Active nematic systems consist of rod-like internally driven subunits that interact with one another to form large-scale coherent flows. They are important examples of far-from-equilibrium fluids, which exhibit a wealth of nonlinear behavior. This includes active turbulence, in which topological defects in the nematic order braid around one another in a chaotic fashion. One of the most studied examples of active nematics consists of a dense two-dimensional layer of microtubules, crosslinked by kinesin molecular motors that inject extensile deformations into the fluid. Though numerous theoretical studies have modeled microtubule-based active nematics, no consensus has emerged on how to fully and quantitatively capture the features of the experimental system. Here, to better understand the theoretical foundations for modeling this system, we propose a fundamental principle we call the nematic locking principle—individual microtubules cannot rotate without all neighboring microtubules also rotating. Physically, this is justified by the high density of the microtubules, their elongated nature, and their corresponding steric interactions. We assert that the nematic locking principle holds throughout the majority of the material, but breaks down in the neighborhood of topological defects and other regions of low density. We derive the most general nematic transport equation consistent with this principle and also derive the most general term that violates it, introducing fracturing into the material. We then examine the standard Beris–Edwards approach, commonly used to model this system, and show that it violates the nematic locking principle throughout the majority of the material due to fracturing. We then propose a modification to the Beris–Edwards model that enforces nematic locking nearly everywhere. This modification shuts off fracturing except in regions where the order parameter (a proxy for density) is reduced. In these regions fracturing is turned on. The resulting simulations in turn show strong nematic locking throughout the bulk of the material, with narrow bands of fracturing, consistent with experimental observation. One additional advantage of enforcing nematic locking is that nontrivial stationary state solutions, common in Beris–Edwards simulations but not seen in experiments, are eliminated.

Mitchell, Kevin A. [Univ. of California, Merced, C↗

Neuromorphic heat transport effects in a molecular junction

Understanding energy transport at the nanoscale is an open and fundamental challenge in the molecular sciences with direct implications for the design of new electronics, computing devices, and materials. While nanoscale energy transport under steady-state conditions has been studied extensively, there is much less known about energy transport under time-dependent driving forces, particularly in the far-from-equilibrium regime. In this work, we use nonequilibrium molecular dynamics simulations and stochastic thermodynamics to investigate energy transport in a well-studied nanoscale system—a molecular junction—subjected to a time-periodic temperature gradient. The primary observation is that molecular junctions can exhibit heat transport hysteresis, a phenomenon in which the heat flux through a system depends not only on the instantaneous value of a time-dependent temperature bias but also on the temporal history of that bias. The presented findings illustrate that molecular junctions can exhibit the specific memory effect—heat transport hysteresis—that is essential for the design of thermal neuromorphic computers. This work elucidates a potential pathway toward the realization of such devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Equilibrium-gated pattern formation: How molecular dissociation thermodynamics drive emergent behavior in dissipative polymeric systems

Emergent patterns in biological systems arise through dissipative processes that balance reaction and transport phenomena, producing highly functional properties from self-regulating mechanisms. Synthetic fabrication, by contrast, often relies on user-controlled, multistep methods that lack the self-organizing capabilities of natural systems. Inspired by nature, we sought chemical systems that integrate strongly coupled reaction and transport phenomena, identifying frontal ring-opening metathesis polymerization (FROMP) as a method capable of creating diverse forms and functions through reactive processing. By employing discrete molecular initiators, FROMP allows precise control of key reaction steps—inhibition, initiation, and propagation. Using an integrated computational and experimental framework, we uncover how near-equilibrium inhibition dynamics, coupled with far-from-equilibrium reaction kinetics, drive pattern formation in frontally polymerized synthetic materials. We propose the concept of equilibrium-gated pattern formation, demonstrating how initiator chemistry can be tuned to achieve programmable macroscale properties. Our study reveals a surprising insight: Emergent behavior in FROMP systems arises from the inhibition-dominated regime of resin composition, expanding prior observations that such behavior is confined to a narrow compositional space near the boundary between front quenching and uniform front propagation. We identify a broader compositional window, far from the quenching regime, where emergent behavior reliably manifests. This expanded design space significantly enhances the operational flexibility of reactive systems and their capacity for self-organization. Furthermore, these insights provide a roadmap for designing bioinspired materials with self-organizing capabilities, unlocking possibilities in synthetic manufacturing.

Architected Polymers↗

Phase-field model of alloy solidification far from chemical equilibrium at the solid-liquid interface

We further develop a recently introduced phase-field model of far-from-equilibrium alloy solidification under additive manufacturing conditions [K. Ji et al., Phys. Rev. Lett. 130, 026203 (2023)]. This model utilizes enhanced solute diffusivity within the spatially diffuse interface region to quantitatively capture solute trapping with a larger interface width, thereby making simulations on experimentally relevant length and timescales computationally feasible. The main developments presented here include testing the robustness of different variational formulations, extending the model to concentrated alloys by incorporating solid and liquid free energies from thermodynamic databases, as illustrated for hypoeutectic Al-Ag alloys with CALPHAD, extending convergence tests as a function of interface width to 3D, and carrying out simulations in both 2D and 3D to examine existing theories of microstructure development. Our results indicate that the simplest variational formulation that interpolates the bulk free-energy density between its solid and liquid forms is the most robust. Remarkably, for hypoeutectic Al-Ag alloys, this formulation yields a high-velocity nonequilibrium phase diagram that is independent of interface width, thereby demonstrating that the framework of enhanced solute diffusivity can be nontrivially extended to concentrated alloys. Other variational formulations have restricted ranges of materials or processing parameters that can be reliably modeled. We use 2D simulations to construct high-velocity microstructure selection maps for dilute Al-Cu alloys. The results validate the important role of latent heat rejection at the interface and extend the limited predictions of linear stability analysis [A. Karma and A. Sarkissian, Phys. Rev. E 47, 513 (1993)] and sharp-interface 1D simulations to fully nonlinear regimes. Furthermore, 3D simulations, carried out using a computationally tractable axisymmetric cellular/dendritic interface shape, demonstrate a good convergence similar to that observed in 2D as a function of interface width. Full 3D simulations, in turn, reveal that the standard theory of absolute stability is a good predictor of the upper critical velocity beyond which steady-state growth becomes unstable, despite the different morphological manifestations of this instability in 2D and 3D.

36 MATERIALS SCIENCE↗

Generalizing multiple memories from a single drive: The hysteron latch

Far-from-equilibrium systems can form memories of previous deformations or driving. In systems from sheared glassy materials to buckling beams to crumpled sheets, this behavior is dominated by return-point memory, in which revisiting a past extremum of driving restores the system to a previous state. Cyclic driving with both positive and negative strains forms multiple nested memories, as in a single-dial combination lock, while asymmetric driving (only positive strain) cannot. We study this case in a general model of hysteresis that considers discrete elements called hysterons. We show how two hysterons with a frustrated interaction can violate return-point memory, realizing multiple memories of asymmetric driving. This reveals a general principle for designing systems that store sequences of cyclic driving, whether symmetric or asymmetric. In disordered systems, asymmetric driving is a sensitive tool for the direct measurement of frustration.

Science & Technology - Other Topics↗

Comparing matching prescriptions between pre-equilibrium and hydrodynamic models in high-energy nuclear collisions

Abstract State-of-the-art simulations of high-energy nuclear collisions rely on hybrid setups, involving in particular a pre-equilibrium stage to let the system evolve from a far-from-equilibrium initial condition towards a near-equilibrated state after which fluid dynamics can be applied meaningfully. A known issue is the mismatch between the equation of state in the fluid-dynamical evolution and the effective one in the previous stage, which leads to discontinuities at the interface between the two models. Here we introduce a new matching prescription at this interface, based on the entropy, and we compare it with the standard one relying on local energy conservation. We study the behavior of various quantities at the switching time between the models and investigate a number of final-state hadronic observables. For the latter, we show that they are not modified significantly by the choice of matching prescription, provided an appropriate normalization is chosen for the initial state. In turn, our approach reduces sizeably the ratio of bulk over thermodynamic pressure at the beginning of the fluid-dynamical stage.

Borghini, Nicolas (ORCID:0000000239063258)↗

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗

Non-equilibrium Dynamics of the Quark Gluon Plasma (Final Report)

During this funding period I continued my work on far-from-equilibrium formulations of hydrodynamics and bottomonium suppression in the quark-gluon plasma. I published 23 peer-reviewed articles and 9 proceedings contributions. The publications produced during this period have thus far received 705 citations. I delivered 22 talks, seminars, and colloquia about my work, most of which were invited. In addition to the work on hydrodynamics and heavy quarkonia, I also worked on high-order perturbative calculations of N=4 supersymmetric Yang-Mills thermodynamics and contributed to the efforts of the MUSES collaboration whose focus is developing a modular equation-of-state framework for use in modeling neutron stars and neutron star mergers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Establishing defect-property relationships for 2D-nanomaterials (Final technical report)

Studies of new families of two-dimensional nanomaterials (2DNMs) have established that they possess unique properties that diverge from those of their bulk counterparts. This project aimed to determine how tolerant 2DNMs are to extreme photon and particle fluxes and to identify the mechanisms governing their radiation response. Early work indicated that graphene is not as representative of other 2DNMs as previously assumed; however, the origin of this difference remained unclear. To address these knowledge gaps, this project investigated the physical processes occurring at multiple length scales in transition metal dichalcogenides (TMDs) and quantified their structural stability and property evolution under far-from-equilibrium conditions. In-situ and ex-situ ion and electron irradiations were performed to directly control and monitor defect formation in TMDs. Complementary density functional theory (DFT) and molecular dynamics (MD) simulations were employed to elucidate the mechanisms of defect generation and evolution. The outcomes of this work established mechanistic understanding of irradiation-induced defect formation in 2DNMs, quantified the radiation tolerance of TMDs, and built a fundamental knowledge base for correlating defect structures with material properties. Collectively, these results provide new insights into the stability of low-dimensional materials in extreme environments and enable the predictive design of radiation-tolerant 2DNMs.

2D materials↗