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At least 1,027 records · Page 57

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗

Predictive Chemical Kinetic Modeling: Where We Succeed, Where We Struggle, and What Comes Next

Chemical kinetic modeling plays a foundational role in fields ranging from energy to environmental science, pharmaceuticals, and advanced materials. The past two decades have seen remarkable progress, particularly in modeling gas-phase reactions for thermochemical processes, leading to impactful industrial applications such as steam cracking and air quality management. However, new challenges are emerging. The successful development of systematic methodologies for the description of gas-phase kinetics opens the possibility to apply the same approach to the study of more challenging systems. Here, we review recent advances, including ab initio transition state theory-based master equation estimation of elementary rates, automated mechanism generation, machine-learning-assisted kinetics, and uncertainty quantification, and discuss the advances needed to apply the same methodological approach in areas such as heterogeneous catalysis, electrochemistry, liquid-phase and solid-state reactivity, and multiscale model integration. We advocate for the development of targeted tools, especially methods that go beyond empirical tuning toward first-principles-based predictions. We highlight the need for accessible software and AIaugmented workflows to democratize modeling for industry and academia alike. In this perspective, we call attention to not only what has worked but also what remains unsolved, advocating to avoid overemphasizing successes in scientific works at the expense of realism. The next decade should focus on predictive capability, physical accuracy, and community infrastructure (e.g., databases and services) to enable innovation across diverse fields. We argue that kinetic modeling, properly equipped, can accelerate discovery far beyond its traditional domains.

ab initio calculations↗

Multi-Species Test of Ion Cyclotron Resonance Heating at High Altitudes

Observations of ion distributions and plasma waves obtained by the Dynamics Explorer 1 satellite in the high-altitude, nightside auroral zone are used to study ion energization for three ion species. A number of theoretical models have been proposed to account for the transverse heating of these ion populations. One of these, the ion cyclotron resonance heating (ICRH) mechanism, explains ion conic formation through ion cyclotron resonance with broadband electromagnetic wave turbulence in the vicinity of the characteristic ion cyclotron frequency. The cyclotron resonant heating of the ions by low- frequency electromagnetic waves is an important energy source for the transport of ions from the ionosphere to the magnetosphere. In this paper we test the applicability of the ICRH mechanism to three simultaneously heated and accelerated ion species by modelling the ion conic formation in terms of a resonant wave-particle interaction in which the ions extract energy from the portion of the broadband electromagnetic wave spectrum which includes the ion cyclotron frequency. Using a Monte Carlo technique we evaluate the ion heating produced by the electromagnetic turbulence at low frequencies and find that the wave amplitudes near the ion cyclotron frequencies are sufficient to explain the observed ion energies.

Persoon, A. M.↗

Multi-Species Test of Ion Cyclotron Resonance Heating at High Altitudes

Observations of ion distributions and plasma waves obtained by the Dynamics Explorer 1 satellite in the high-altitude, nightside auroral zone are used to study ion energization for three ion species. A number of theoretical models have been proposed to account for the transverse heating of these ion populations. One of these, the ion cyclotron resonance heating (ICRH) mechanism, explains ion conic formation through ion cyclotron resonance with broadband electromagnetic wave turbulence in the vicinity of the characteristic ion cyclotron frequency. The cyclotron resonant heating of the ions by low-frequency electromagnetic waves is an important energy source for the transport of ions from the ionosphere to the magnetosphere. In this paper we test the applicability of the ICRH mechanism to three simultaneously heated and accelerated ion species by modelling the ion conic formation in terms of a resonant wave-particle interaction in which the ions extract energy from the portion of the broadband electromagnetic wave spectrum which includes the ion cyclotron frequency. Using a Monte Carlo technique we evaluate the ion heating produced by the electromagnetic turbulence at low frequencies and find that the wave amplitudes near the ion cyclotron frequencies are sufficient to explain the observed ion energies.

Persoon, A. M.↗

Microbial contribution to post-fire tundra ecosystem recovery over the 21st century

Abstract Tundra ecosystems have experienced an increased frequency of fire, and this trend is predicted to continue throughout the 21 st Century. Post-fire recovery is underpinned by complex interactions between microbial functional groups that drive nutrient cycling. Here we use a mechanistic model to demonstrate an acceleration of the nitrogen cycle post-fire driven by changes in niche space and microbial competitive dynamics. We show that over the first 5-years post-fire, fast-growing bacterial heterotrophs colonize regions of the soil previously occupied by slower-growing saprotrophic fungi. The bacterial heterotrophs mineralize organic matter, releasing nutrients into the soil. This pathway outweighs new sources of nitrogen and facilitates the recovery of plant productivity. We broadly show here that while consideration of distinct microbial metabolisms related to carbon and nutrient cycling remains rare in terrestrial ecosystem models, they are important when considering the rate of ecosystem recovery post-disturbance and the feedback to soil nutrient cycles on centennial timescales.

54 ENVIRONMENTAL SCIENCES↗

Shock acceleration of electrons and ions in solar flares

The simultaneous first-order Fermi shock acceleration of electrons, protons, and alpha particles are compared to observations of solar energetic particle events. For each event, a unique shock compression ratio in the range approx. 1.6 to 3 produces spectra in good agreement with observation. The range in compression ratios predicts that the more than 5 orders of magnitude spread in electron to proton intensity ratios observed at MeV energies is compressed to about 3 orders of magnitude at an assumed injection energy of 100 keV. The remaining spread can be accounted for with a modest range of injection conditions. The model predicts that the acceleration time to a given energy will be approximately equal for electrons and protons and, for reasonable solar parameters, can be on the order of 1 second to approx. 100 MeV.

Ellison, Donald C.↗

Shock acceleration of electrons and ions in solar flares

The simultaneous first-order Fermi shock acceleration of electrons, protons, and alpha particles are compared to observations of solar energetic particle events. For each event, a unique shock compression ratio in the range of approximately 1.6-3 produces spectra in good agreement with observation. The range in compression ratios predicts that the more than five orders of magnitude spread in electron-to-proton intensity ratios observed at MeV energies is compressed to about three orders of magnitude at an assumed injection energy of 100 keV. The remaining spread can be accounted for with a modest range of injection conditions. The model predicts that the acceleration time to a given energy will be approximately equal for electrons and protons, and for reasonable solar parameters, can be on the order of 1 s to approximately 100 MeV.

Ellison, D. C.↗

Preliminary study of auto-differentiation algorithm in beam dynamics with stochastic process

Modern particle accelerator optimization requires sophisticated computational methods to address the inherently stochastic nature of beam dynamics. This research develops a framework applying AD to SDEs that specifically addresses beam dynamics challenges in particle accelerators, focusing on accurately modeling and optimizing beam behavior in regimes dominated by stochastic processes. By incorporating key physical phenomena such as synchrotron radiation, wakefield effects, and quantum excitation, the framework aims to provide auto differentiation on the figure of merit of the phase space evolution and beam dynamics. The methodology will enable effective optimization method in a dynamic system with stochastic process.

Accelerator Physics↗

Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements

Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.

Li, Jinxing↗

Modeling a Miniature Voitenko-Like Explosively-Driven Shock Tube Using FLAG

Using the FLAG hydrocode, hypervelocity plasma jets observed in miniature explosively–driven shock tube experiments have been modeled with a relative error in velocity of less than 5% (a reduction from previous attempts which yielded errors of 37%). This suggests that FLAG may be well-suited to model HE systems involving the acceleration of gases through complex crack systems in HE devices: A phenomenon not accurately captured using current modeling capabilities. The Eulerian hydrocode model presented here leverages AMR to reduce computational cost and, importantly, it was found that mesh resolution and model geometry each significantly affected the average jet velocity. The model and the results are detailed here together with comments on challenges during its development and avenues for future work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle Engulfment and Pushing By Solidifying Interfaces

The study of particle behavior at solid/liquid interfaces (SLI s) is at the center of the Particle Engulfment and Pushing (PEP) research program. Interactions of particles with SLI s have been of interest since the 1960 s, starting with geological observations, i.e., frost heaving. Ever since, this field of research has become significant to such diverse areas as metal matrix composite materials, fabrication of superconductors, and inclusion control in steels. The PEP research effort is geared towards understanding the fundamental physics of the interaction between particles and a planar SLI. Experimental work including 1-g and mu-g experiments accompany the development of analytical and numerical models. The experimental work comprised of substantial groundwork with aluminum (Al) and zinc (Zn) matrices containing spherical zirconia particles, mu-g experiments with metallic Al matrices and the use of transparent organic metal-analogue materials. The modeling efforts have grown from the initial steady-state analytical model to dynamic models, accounting for the initial acceleration of a particle at rest by an advancing SLI. To gain a more comprehensive understanding, numerical models were developed to account for the influence of the thermal and solutal field. Current efforts are geared towards coupling the diffusive 2-D front tracking model with a fluid flow model to account for differences in the physics of interaction between 1-g and -g environments. A significant amount of this theoretical investigation has been and is being performed by co-investigators at NASA MSFC.

Source record↗

Foundational Open Source Solar System Modeling Through Improvement and Validation of the System Advisor Model and PVWatts (FY19-FY21 Final Technical Report)

Accelerating intelligent deployment of solar energy technologies demands accurate system modeling every step of the way. From project development to policy research, grid integration studies to development of novel technologies, industry and researchers alike need validated, transparent, easy-to-use, extensible, cutting-edge, and accurate models of both the performance and financing of solar systems. The System Advisor Model (SAM) and PVWatts tools provide a platform to fill that need. The overarching goal of this set of software tools is to enable accurate PV system modeling across the industry, and our usage metrics indicate that we continue to succeed in that endeavor, with a user starting SAM every 2 minutes globally, and over 17 million PVWatts hits per month. This project leveraged DOEs past investment in the SAM and PVWatts platforms to continue to provide valuable and extensible PV, battery, and financial modeling resources to the larger solar community. We pursued multiple avenues in parallel: software maintenance and technical support that are foundational to the continued usability of the SAM and PVWatts platforms; platform and PV model improvements and stakeholder engagement activities that are core to the continued relevance of the platforms; and open source activities to foster the continued creation of a vibrant open-source community around the SAM and PVWatts tools, which opens up exciting new opportunities for industry interaction.

14 SOLAR ENERGY↗

Accelerated cometary ions observed downstream of the Comet Halley bow shock

Results are presented of fluxes of energetic ions with energies exceeding 100 keV that were detected upstream of the bow shock of Comet Halley by the Tuende instrument on board the VEGA 1 spacecraft. Downstream of the shock, ion fluxes in the energy range 100 to 180 keV were observed. The measured ion fluxes were transformed into distribution functions in the solar wind frame using a variety of assumptions concerning the energy dependence of the distribution function and the identity of the ion species. The derived distribution function upstream of the shock falls off steeply with energy between 100 and 150 keV, with an effective temperature of about 7 keV or spectral index of about -15. The distribution function increases with decreasing cometocentric distance, on average, reaching a maximum at the bow shock. The measured distribution functions are compared with those obtained by similar instruments on Giotto and ICE as well as with the predictions of several theoretical models that employ different acceleration mechanisms.

Kecskemety, K.↗

MMS Observation of Inverse Energy Dispersion in Shock Drift Accelerated Ions

The four Magnetospheric Multiscale (MMS) spacecraft observed a ∼1 min burst of energetic ions (50–1000 keV) in the region upstream from the subsolar quasi-perpendicular bow shock on 6 December 2015. The composition, flux levels, and spectral indices of these energetic protons, helium, and oxygen ions greatly resemble those seen in the outer magnetosphere earlier while MMS crossed the magnetopause and differ significantly from those simultaneously observed far upstream by Advanced Composition Explorer (ACE). However, the event cannot be explained solely in terms of leakage from the magnetosphere. The strongly southward orientation of the interplanetary magnetic field (IMF) lines at the time of the event precludes any connection to the magnetosphere. This point is confirmed by the presence of energetic electrons, known to occur on magnetic field lines that graze the bow shock rather than connect to the magnetosphere. We suggest that the ions gradient drifted out of the nearby quasi-parallel foreshock and into the quasi-perpendicular bow shock. Each of the ion species exhibited an inverse energy dispersion. As predicted by models for shock drift acceleration, the energies of the ions increased as 𝜃(sub Bn), the angle between the IMF and the shock normal, increased. Finally, we note that a similar event was observed a few minutes later in the subsolar magnetosheath, indicating that such events can be swept downstream of the bow shock.

Lee, S. H.↗

APOLLO: a facility-scale differentiable virtual accelerator at Fermilab FAST/IOTA

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or yield additional insights like gradients. The FAST/IOTA facility has been working on implementing and experimentally validating an end-to-end digital twin that is both fast and gradient-aware, allowing for rapid prototyping of new software and experiments with minimal beam time costs. Our framework integrates physics and ML codes for linac and ring simulation through a set of generic interfaces between surrogate and physics-based sections. To reproduce device inputs and outputs, system state is exposed as a deterministic event loop in a specialized discrete event simulator architecture. Because Fermilab is undergoing control system transition, several APIs were implemented as final user interfaces - a fully asynchronous EPICS soft IOC, a gRPC-based Data Pool Manager (DPM), and legacy ACNET protocols. We discuss implementation details as well as challenges handling live data assimilation and future plans to extend modelling to main complex proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗

Deep learning-assisted modeling for χ (2) nonlinear optics

Modeling second-order (χ(2)) nonlinear optical processes remains computationally expensive due to the need to resolve fast field oscillations and simulate wave propagation using methods such as the split-step Fourier method (SSFM). This can become a bottleneck in real-time applications, such as high-repetition-rate laser systems requiring rapid feedback and control. We present a long short-term memory-based surrogate model trained on SSFM simulations generated from a start-to-end model of the photocathode drive laser at SLAC National Accelerator Laboratory’s Linac Coherent Light Source II. The model achieves over 250× speedup while maintaining high fidelity, enabling future real-time optimization and laying the foundation for data-integrated modeling frameworks and digital twins of laser systems.

Accelerator Physics (physics.acc-ph)↗

Horizontal vestibuloocular reflex evoked by high-acceleration rotations in the squirrel monkey. I. Normal responses

The horizontal angular vestibuloocular reflex (VOR) evoked by high-frequency, high-acceleration rotations was studied in five squirrel monkeys with intact vestibular function. The VOR evoked by steps of acceleration in darkness (3,000 degrees /s(2) reaching a velocity of 150 degrees /s) began after a latency of 7.3 +/- 1.5 ms (mean +/- SD). Gain of the reflex during the acceleration was 14.2 +/- 5.2% greater than that measured once the plateau head velocity had been reached. A polynomial regression was used to analyze the trajectory of the responses to steps of acceleration. A better representation of the data was obtained from a polynomial that included a cubic term in contrast to an exclusively linear fit. For sinusoidal rotations of 0.5-15 Hz with a peak velocity of 20 degrees /s, the VOR gain measured 0.83 +/- 0.06 and did not vary across frequencies or animals. The phase of these responses was close to compensatory except at 15 Hz where a lag of 5.0 +/- 0.9 degrees was noted. The VOR gain did not vary with head velocity at 0.5 Hz but increased with velocity for rotations at frequencies of >/=4 Hz (0. 85 +/- 0.04 at 4 Hz, 20 degrees /s; 1.01 +/- 0.05 at 100 degrees /s, P < 0.0001). No responses to these rotations were noted in two animals that had undergone bilateral labyrinthectomy indicating that inertia of the eye had a negligible effect for these stimuli. We developed a mathematical model of VOR dynamics to account for these findings. The inputs to the reflex come from linear and nonlinear pathways. The linear pathway is responsible for the constant gain across frequencies at peak head velocity of 20 degrees /s and also for the phase lag at higher frequencies being less than that expected based on the reflex delay. The frequency- and velocity-dependent nonlinearity in VOR gain is accounted for by the dynamics of the nonlinear pathway. A transfer function that increases the gain of this pathway with frequency and a term related to the third power of head velocity are used to represent the dynamics of this pathway. This model accounts for the experimental findings and provides a method for interpreting responses to these stimuli after vestibular lesions.

NASA Program Biomedical Research and Countermeasur↗