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Liquid-like and rigid-body motions in molecular-dynamics simulations of a crystalline protein

To gain insight into crystalline protein dynamics, we performed molecular-dynamics (MD) simulations of a periodic 2 × 2 × 2 supercell of staphylococcal nuclease. We used the resulting MD trajectories to simulate X-ray diffraction and to study collective motions. The agreement of simulated X-ray diffraction with the data is comparable to previous MD simulation studies. We studied collective motions by analyzing statistically the covariance of alpha-carbon position displacements. The covariance decreases exponentially with the distance between atoms, which is consistent with a liquidlike motions (LLM) model, in which the protein behaves like a soft material. To gain finer insight into the collective motions, we examined the covariance behavior within a protein molecule (intraprotein) and between different protein molecules (interprotein). The interprotein atom pairs, which dominate the overall statistics, exhibit LLM behavior; however, the intraprotein pairs exhibit behavior that is consistent with a superposition of LLM and rigid-body motions (RBM). Our results indicate that LLM behavior of global dynamics is present in MD simulations of a protein crystal. They also show that RBM behavior is detectable in the simulations but that it is subsumed by the LLM behavior. Finally, the results provide clues about how correlated motions of atom pairs both within and across proteins might manifest in diffraction data. Overall, our findings increase our understanding of the connection between molecular motions and diffraction data and therefore advance efforts to extract information about functionally important motions from crystallography experiments.

59 BASIC BIOLOGICAL SCIENCES↗

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum dynamics simulations of the 2D spectroscopy for exciton polaritons

We develop an accurate and numerically efficient non-adiabatic path-integral approach to simulate the non-linear spectroscopy of exciton–polariton systems. This approach is based on the partial linearized density matrix approach to model the exciton dynamics with explicit propagation of the phonon bath environment, combined with a stochastic Lindblad dynamics approach to model the cavity loss dynamics. Through simulating both linear and polariton two-dimensional electronic spectra, we systematically investigate how light–matter coupling strength and cavity loss rate influence the optical response signal. Our results confirm the polaron decoupling effect, which is the reduced exciton–phonon coupling among polariton states due to the strong light–matter interactions. We further demonstrate that the polariton coherence time can be significantly prolonged compared to the electronic coherence outside the cavity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Editorial announcements and information — ICFA Beam Dynamics Newsletter No. 81

This is a general information article of the ICFA Beam Dynamics Newsletter No. 81. Thus, it contains two forewords from the Editor-in-Chief and the issue editor, a workshop and conference report section, a recent Ph.D. thesis section, a forthcoming beam dynamics events section, and a section of announcements from the beam dynamics panel.

47 OTHER INSTRUMENTATION↗

Editorial announcements and information — ICFA Beam Dynamics Newsletter No. 82

This is a general information article of the ICFA Beam Dynamics Newsletter No. 81. It contains two forewords from the Editor-in-Chief and the issue editor, a workshop and conference report section, a recent Ph.D. thesis section, a forthcoming beam dynamics events section, and a section of announcements from the beam dynamics panel.

43 PARTICLE ACCELERATORS↗

Editorial announcements and information — ICFA Beam Dynamics Newsletter No. 85

This is a general information article of the ICFA Beam Dynamics Newsletter No. 85. It contains foreword from the Editor-in-Chief and the issue editor, a workshop and conference report section, a recent Ph.D. thesis section, a forthcoming beam dynamics events section, and a section of announcements from the beam dynamics panel.

43 PARTICLE ACCELERATORS↗

Dynamic Matrix Completion Based State Estimation in Distribution Grids

The power distribution network is undergoing tremendous transformation due to an increase in the penetration of renewable energy resources and electric vehicles. These changes have resulted in greater uncertainty and dynamics in the distribution grid states. Therefore, the ability to track and monitor system states has become a critical need for accurate and timely control actions. In this paper, we propose two dynamic sparsity-based state estimation approaches for distribution systems: (1) locally weighted matrix completion (LW-MC) and (2) Bayesian matrix completion with Kalman filter prediction (BMC-KF). The performance of the proposed dynamic state estimation strategies is compared with the classic/static matrix completion (static-MC) approach using the IEEE 37 and IEEE 123 bus test systems. Finally, results indicate that BMC-KF approach outperforms both LW-MC as well as static-MC even when 30% of the measurement data is available. Computational complexity associated with both approaches is quantified.

42 ENGINEERING↗

Exciton Dynamics in Layered Halide Perovskite Light‐Emitting Diodes

Abstract Layered halide perovskites have garnered significant interest due to their exceptional optoelectronic properties and great promises in light‐emitting applications. Achieving high‐performance perovskite light‐emitting diodes (PeLEDs) requires a deep understanding of exciton dynamics in these materials. This review begins with a fundamental overview of the structural and photophysical properties of layered halide perovskites, then delves into the importance of dimensionality control and cascade energy transfer in quasi‐2D PeLEDs. In the second half of the review, more complex exciton dynamics, such as multiexciton processes and triplet exciton dynamics, from the perspective of LEDs are explored. Through this comprehensive review, an in‐depth understanding of the critical aspects of exciton dynamics in layered halide perovskites and their impacts on future research and technological advancements for layered halide PeLEDs is provided.

Baek, Sung‐Doo↗

Control of the Folding Dynamics of Self-Reconfiguring Magnetic Microbots Using Liquid Crystallinity

Reconfigurable microdevices are being explored in a range of contexts where their life-like abilities to move and change shape are important. While much work has been done to control the motion of these microdevices by engineering their geometry and composition, little is known about their dynamics in complex fluid environments with non-Newtonian rheology. Here in this paper, it is shown how the actuation dynamics of reconfigurable microdevices made by assembly of patchy magnetic microcubes, which are referred to as “microbots,” can be modulated by their interactions with the anisotropic viscoelastic environment of a liquid crystal (LC). The free energy arising from the elastic strain of LC and formation of topological defects around the microbots influences their folding dynamics, which can be tuned by tailoring both the far-field orientation of the LC and the local ordering of the LC at the microbot surfaces. These findings represent a first step toward establishing a general set of design rules to control the dynamics of microbots using complex anisotropic fluids.

36 MATERIALS SCIENCE↗

Static and Dynamic Gradient Based Directional Transportation of Neutral Molecules in Swollen Polymer Films

Abstract Materials which selectively transport molecules offer powerful opportunities for concentrating and separating chemical agents. Here, utilizing static and dynamic chemical gradients, transport of molecules within swollen crosslinked polymers is demonstrated. Using an ≈200 μm static hydroxyl to hexyl gradient, the neutral ambipolar nerve agent surrogate diethyl (cyanomethyl)phosphonate (DECP) is directionally transported and concentrated 60‐fold within 4 hours. To accelerate transport kinetics, a dynamic gradient (a “travelling wave”) is utilized. Here, the non‐polar dye pyrene was transported. The dynamic gradient is generated by an ion exchange process triggered by the localized introduction of an aqueous NaCl solution, which converts the gel from hydrophobic to hydrophilic. As the hydrophilic region expands, associated water enters the gel, and pyrene is pushed ahead of the expansion front. The dynamic gradient provides about 10‐fold faster transport kinetics than the static gradient.

Ali, Mohammad A.↗

Ion‐Specific Interactions Engender Dynamic and Tailorable Properties in Biomimetic Cationic Polyelectrolytes

Abstract Biomaterials such as spider silk and mussel byssi are fabricated by the dynamic manipulation of intra‐ and intermolecular biopolymer interactions. Organisms modulate solution parameters, such as pH and ion co‐solute concentration, to effect these processes. These biofabrication schemes provide a conceptual framework to develop new dynamic and responsive abiotic soft material systems. Towards these ends, the chemical diversity of readily available ionic compounds offers a broad palette to manipulate the physicochemical properties of polyelectrolytes via ion‐specific interactions. In this study, we show for the first time that the ion‐specific interactions of biomimetic polyelectrolytes engenders a variety of phase separation behaviors, creating dynamic thermal‐ and ion‐responsive soft matter that exhibits a spectrum of physical properties, spanning viscous fluids to viscoelastic and viscoplastic solids. These ion‐dependent characteristics are further rendered general by the merger of lysine and phenylalanine into a single, amphiphilic vinyl monomer. The unprecedented breadth, precision, and dynamicity in the reported ion‐dependent phase behaviors thus introduce a broad array of opportunities for the future development of responsive soft matter; properties that are poised to drive developments in critical areas such as chemical sensing, soft robotics, and additive manufacturing.

Aubrecht, Filip J.↗

Static and Dynamic Gradient Based Directional Transportation of Neutral Molecules in Swollen Polymer Films

Abstract Materials which selectively transport molecules offer powerful opportunities for concentrating and separating chemical agents. Here, utilizing static and dynamic chemical gradients, transport of molecules within swollen crosslinked polymers is demonstrated. Using an ≈200 μm static hydroxyl to hexyl gradient, the neutral ambipolar nerve agent surrogate diethyl (cyanomethyl)phosphonate (DECP) is directionally transported and concentrated 60‐fold within 4 hours. To accelerate transport kinetics, a dynamic gradient (a “travelling wave”) is utilized. Here, the non‐polar dye pyrene was transported. The dynamic gradient is generated by an ion exchange process triggered by the localized introduction of an aqueous NaCl solution, which converts the gel from hydrophobic to hydrophilic. As the hydrophilic region expands, associated water enters the gel, and pyrene is pushed ahead of the expansion front. The dynamic gradient provides about 10‐fold faster transport kinetics than the static gradient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding curing dynamics of arylacetylene and phthalonitrile thermoset blends

Tetrakis(phenylethynyl)benzene (TPEB), a high char yield arylacetylene resin, was blended with a resorcinol-based PEEK™-like oligomeric phthalonitrile resin (Res). Here, we observed the influence of each polymer precursor on the structural changes and material dynamics of different mixtures of these resins during thermal curing to produce thermosets with high char retention. We provide insight to help understand fundamental processes that control and tune this complex thermally driven curing mechanism, which, to date, has not been well understood. We show that an equivalent blend of Res and TPEB mitigates the exothermic curing process and exhibits a low viscosity, which may facilitate processing of these thermosetting blends for composite manufacturing. To obtain a more comprehensive overview of the different dynamics of these polymers during curing, we correlated thermodynamic changes with rheology, materials characterization, and molecular dynamics derived from neutron scattering. Our efforts shed more light on the thermally driven chemical changes, physical transformation, and gelation dynamics that drive or accompany softening and curing of these two distinct crosslinking resin groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗

Temperature Dependent Early-Stage Oxidation Dynamics of Cu(100) Film with Faceted Holes

Fundamental understanding of surface oxidation dynamics is critical for rational corrosion protection and advanced manufacturing of nanostructured oxides. In situ environmental TEM (ETEM) provides high spatial (nano- to atomic- scale) and temporal (< 0.1 s) resolution to investigate the early-stage oxidation/corrosion dynamics of metals and alloys. Thin samples with facets are widely used to enable cross-sectional observation of the oxidation dynamics in ETEM. However, how different facet orientations oxidize under the same conditions, and how these facets change the oxidation process, has not been investigated before. Here, using in situ ETEM, we systematically compare the oxidation dynamics of Cu(001) thin films, with faceted holes exposing {100} and {110} facets at temperatures ranging from 250–600 °C under 0.03 Pa O 2 . Oxidation preference is observed to change, from Cu(110) facets at lower temperatures to Cu(100) facets at ~ 500 °C. Oxide growth mechanisms change from outward growth on Cu 2 O surfaces at low temperatures, to inward growth on Cu-Cu 2 O interfaces at high temperatures. At high temperatures (500–600 °C), a rod-like Cu 2 O morphology is observed, with side facets of ~ {024} and top facets of {100} on Cu(100). This differs from the square-shaped Cu 2 O exposing {110} facets formed on Cu(001) surfaces. Rod-like oxides exhibit directional growth along their lengths with linear growth rates, regardless of rod length and width. This suggests that O from Cu(001) surfaces, rather than Cu(100) facets, serves as an O source for oxide growth. These results show a direct comparison of oxidation at different orientations with temperature, underscoring the temperature dependence of oxidation preference. Our results also suggest future in situ ETEM experiments viewing oxidation corrosion cross-sectionally should be cautious when oxide size is comparable with sample thickness, as the oxidizing mechanism may change due to sample thickness.

36 MATERIALS SCIENCE↗

Dynamic Tensile Response of a Fe–49Co–2V Alloy at Various Strain Rates and Temperatures

Soft ferromagnetic alloys are often utilized in electromagnetic applications due to their desirable magnetic properties. In support of these applications, the ferromagnetic alloys are also required to bear mechanical load under various loading and environmental conditions. In this study, a Fe–49Co–2V alloy was dynamically characterized in tension with a Kolsky tension bar and a Drop–Hopkinson bar at various strain rates and temperatures. Dynamic tensile stress–strain curves of the Fe–49Co–2V alloy were obtained at strain rates ranging from 40 to 230 s -1 and temperatures from - 100 to 100 °C. All dynamic tensile stress–strain curves exhibited an initial linear elastic response to an upper yield followed by Lüders band response and then a nearly linear work-hardening behavior. The yield strength of this material was found to be sensitive to both strain rate and temperature, whereas the hardening rate was independent of strain rate or temperature. The Fe–49Co–2V alloy exhibited a feature of brittle fracture in tension under dynamic loading with no necking being observed.

36 MATERIALS SCIENCE↗

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗