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DOE OSTI2024

Unveiling the nanoscale architectures and dynamics of protein assembly with in situ atomic force microscopy

Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Plasma technology for lignocellulosic biomass conversion toward an electrified biorefinery

Lignocellulosic biomass conversion to renewable, carbon-neutral materials, fuels, and chemicals is the cornerstone of the transition to a sustainable future bioeconomy. Green energy in the form of electricity needs to be coupled with or substitute conventional thermally driven processes to realize small-scale, economically viable and environmentally friendly biorefineries. Gas discharge plasmas enable the conversion of renewable electric energy, supplied in the form of an electric field, to chemical energy through the formation of a highly reactive environment that can induce several transformations related to agricultural waste valorization processes. Herein, we review the application of plasma technology to lignocellulosic biomass upgrade, aiming to provide the scientific background and technical challenges in this rapidly emerging research field. To bridge the gap between plasma science and biomass valorization technologies, we initially present the technical aspects of plasma reactors related to biomass processing and further discuss the advances in plasma processing for each biomass conversion technology, providing insights into the related plasma chemistry and interaction mechanisms. Here, we first focus on the low and medium-temperature biomass conversion processes, including biomass pretreatment and delignification to promote enzyme or acid-catalyzed hydrolysis to sugars and biomass liquefaction using plasma electrolysis. Then we discuss the high and very high-temperature conversion processes, such as plasma-assisted pyrolysis and gasification to syngas and plasma application to tar removal, combustion, and vitrification. Overall, this review provides knowledge at the interface of plasma science and biomass conversion technology to promote the interaction between the individual communities, which is crucial for the further advancement of the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Characterizing Land-Atmosphere Interactions During the Afternoon-to-Evening Transition Using ARM SGP Observations

The land-atmosphere (LA) system consists of the soil, vegetation, and lowest layer of the atmosphere. The energy and water transport processes in this system contribute to the structure and the daily cycle of the atmospheric boundary layer (ABL), which is the layer between the land surface and the free troposphere that controls the exchange of momentum, energy, and water. The state of the ABL is the result of complex two-way interactions between local processes such as surface fluxes and entrainment at the ABL top as well as large-scale and mesoscale processes such as advection and subsidence.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Convection-Permitting Ensembles of an Isolated Mountain Thunderstorm during RELAMPAGO/CACTI

Abstract The north–south-oriented Sierras de Córdoba (SDC) ridge in central Argentina is noted for initiating thunderstorms that may grow into intense mesoscale convective systems (MCSs). It also initiates more isolated, shorter-lived cells under weaker synoptic forcing. These cells are less impactful than MCSs but may be difficult to predict in convective-scale numerical weather prediction (NWP) due to their strong sensitivities to subgrid and partially resolved processes. To study the mechanisms and predictability of such cells, convection-permitting ensemble simulations were conducted of an isolated, diurnally forced SDC thunderstorm during Cloud, Aerosol, and Complex Terrain Interactions (CACTI)/Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO). The rich observational data facilitated detailed ensemble verification, where dry biases in the surface energy balance and soil moisture were identified. These biases promoted rapid removal of convective inhibition and an early onset of precipitating cells over the SDC that were shallower and weaker than the observed cell. Correction, and then overcorrection, of the soil moisture bias in two successive ensembles was required to rectify the surface energy balance and improve the representation of the SDC cell. Nevertheless, substantial ensemble variability in convective precipitation was found, with some members producing more widespread convection than observed and others producing no deep convection at all. This variability was largely explained by a combination of thermodynamic and dynamic mechanisms, dominated by a positive sensitivity of convective precipitation to preconvective moist instability over the ridge. Secondary sensitivities were found to low-level upward mass flux and midlevel cross-barrier winds, the latter of which caused gravity waves with elevated downdrafts that tended to suppress incipient clouds.

Lopez, Andres [Department of Atmospheric and Ocean↗

DOE OSTI2022

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. Here, the predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

N -Arylimide Molecular Balances: A Comprehensive Platform for Studying Aromatic Interactions in Solution

Noncovalent interactions of aromatic surfaces play a key role in many biological processes and in determining the properties and utility of synthetic materials, sensors, and catalysts. However, the study of aromatic interactions has been challenging because these interactions are usually very weak and their trends are modulated by many factors such as structural, electronic, steric, and solvent effects. Recently, N-arylimide molecular balances have emerged as highly versatile and effective platforms for studying aromatic interactions in solution. These molecular balances can accurately measure weak noncovalent interactions in solution via their influence on the folded–unfolded conformational equilibrium. The structure (i.e., size, shape, π-conjugation, and substitution) and nature (i.e., element, charge, and polarity) of the π-surfaces and interacting groups can be readily varied, enabling the study of a wide range of aromatic interactions. These include aromatic stacking, heterocyclic aromatic stacking, and alkyl–π, chalcogen–π, silver–π, halogen–π, substituent–π, and solvent–π interactions. The ability to measure a diverse array of aromatic interactions within a single model system provides a unique perspective and insights as the interaction energies, stability trends, and solvent effects for different types of interactions can be directly compared. Some broad conclusions that have emerged from this comprehensive analysis include: (1) The strongest aromatic interactions involve groups with positive charges such as pyridinium and metal ions which interact with the electrostatically negative π-face of the aromatic surface via cation–π or metal–π interactions. Attractive electrostatic interactions can also form between aromatic surfaces and groups with partial positive charges. (2) Electrostatic interactions involving aromatic surfaces can be switched from repulsive to attractive using electron-withdrawing substituents or heterocycles. These electrostatic trends appear to span many types of aromatic interactions involving a polar group interacting with a π-surface such as halogen–π, chalcogen–π, and carbonyl–π. (3) Nonpolar groups form weak but measurable stabilizing interactions with aromatic surfaces in organic solvents due to favorable dispersion and/or solvophobic effects. Furthermore, a good predictor of the interaction strength is provided by the change in solvent-accessible surface area. (4) Solvent effects modulate the aromatic interactions in the forms of solvophobic effects and competitive solvation, which can be modeled using solvent cohesion density and specific solvent–solute interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Ansatz-Free Hamiltonian Learning with Heisenberg-Limited Scaling

Learning the unknown interactions that govern a quantum system is crucial for quantum information processing, device benchmarking, and quantum sensing. The problem, known as Hamiltonian learning, is well understood under the assumption that interactions are local, but this assumption may not hold for arbitrary Hamiltonians. Previous methods all require high-order inverse polynomial dependency with precision, unable to surpass the standard quantum limit and reach the gold-standard Heisenberg-limited scaling. Whether Heisenberg-limited Hamiltonian learning is possible without prior assumptions about the interaction structures, a challenge we term ansatz-free Hamiltonian learning , remains an open question. In this work, we present a quantum algorithm to learn arbitrary sparse Hamiltonians without any structure constraints using only black-box queries of the system’s real-time evolution and minimal digital controls to attain Heisenberg-limited scaling in estimation error. Our method is also resilient to state-preparation-and-measurement errors, enhancing its practical feasibility. We numerically demonstrate our ansatz-free protocol for learning physical Hamiltonians and validating analog quantum simulations, benchmarking our performance against the state-of-the-art Heisenberg-limited learning approach. Moreover, we establish a fundamental trade-off between total evolution time and quantum control on learning arbitrary interactions, revealing the intrinsic interplay between controllability and total evolution-time complexity for any learning algorithm. These results pave the way for further exploration into Heisenberg-limited Hamiltonian learning in complex quantum systems under minimal assumptions, potentially enabling new benchmarking and verification protocols.

machine learning↗

DOE OSTI2024

The Role of Cloud Radiative Effects in the Propagating Southern Annular Mode

Abstract The Southern Annular Mode (SAM) is the most dominant natural mode of variability in the mid‐latitudes of the Southern Hemisphere (SH). However, both the sign and magnitude of the feedbacks from the diabatic processes, especially those associated with clouds, onto the SAM remain elusive. By applying the cloud locking technique to the Energy Exascale Earth System Model (E3SM) atmosphere model, this study isolates the positive feedback from the cloud radiative effect (CRE) to the SAM. Feedback analysis based on a wave activity‐zonal momentum interaction framework corroborates this weak but positive feedback. While the magnitude of the CRE feedback appears to be secondary compared to the feedbacks from the dry and other diabatic processes, the indirect CRE effects through the interaction with other dynamical and thermodynamical processes appear to play as important a role as the direct CRE in the life cycle of the SAM. The cross‐EOF analysis further reveals the obstructive effect of the interactive CRE on the propagation mode of the SH zonal wind directly through the CRE wave source and/or indirectly through modulating other diabatic processes. As a result, the propagation mode becomes more persistent and the SAM it represents becomes more predictable when the interactive CRE is disabled by cloud locking. Future efforts on inter‐model comparisons of CRE‐denial experiments are important to build consensus on the dynamical feedback of CRE.

58 GEOSCIENCES↗

DOE OSTI2025

Light in the shadows: primordial black holes making dark matter shine

We consider the possibility of indirect detection of dark sector processes by investigating a novel form of interaction between ambient dark matter (DM) and primordial black holes (PBHs). The basic scenario we envisage is that the ambient DM is “dormant”, i.e., it has interactions with the SM, but its potential for an associated SM signal is not realized for various reasons. We argue that the presence of PBHs with active Hawking radiation (independent of any DM considerations) can act as a catalyst in this regard by overcoming the aforementioned bottlenecks. The central point is that PBHs radiate all types of particles, whether in the standard model (SM) or beyond (BSM), which have a mass at or below their Hawking temperature. The emission of such radiation is “democratic” (up to the particle spin), since it is based on a coupling of sorts of gravitational origin. In particular, such shining of (possibly dark sector) particles onto ambient DM can then activate the latter into giving potentially observable SM signals. We illustrate this general mechanism with two specific models. First, we consider asymmetric DM, which is characterized by an absence of ambient anti-DM, and consequently the absence of DM indirect detection signals. In this case, PBHs can “resurrect” such a signal by radiating anti-DM, which then annihilates with ambient DM in order to give SM particles such as photons. In our second example, we consider the PBH emission of dark gauge bosons which can excite ambient DM into a heavier state (which is, again, not ambient otherwise), this heavier state later decays back into DM and photons. Finally, we demonstrate that we can obtain observable signals of these BSM models from asteroid-mass PBHs (Hawking radiating currently with ~ $ \mathcal{O}\left(\textrm{MeV}\right) $ temperatures) at gamma-ray experiments such as AMEGO-X.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Exclusive dielectron production in ultraperipheral Pb+Pb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV with ATLAS

Exclusive production of dielectron pairs, γγ → e + e – , is studied using $\mathcal{L}_{int}$ = 1.72 nb –1 of data from ultraperipheral collisions of lead nuclei at $\sqrt{s_{NN}}$ = 5.02 TeV recorded by the ATLAS detector at the LHC. The process of interest proceeds via photon–photon interactions in the strong electromagnetic fields of relativistic lead nuclei. Dielectron production is measured in the fiducial region defined by following requirements: electron transverse momentum $p^{e}_{T}$ > 2.5 GeV, absolute electron pseudorapidity |η e | < 2.5, dielectron invariant mass m ee > 5 GeV, and dielectron transverse momentum $p^{ee}_{T}$ < 2 GeV. Differential cross-sections are measured as a function of m ee , average $p^{e}_{T}$, absolute dielectron rapidity |y ee |, and scattering angle in the dielectron rest frame, |cos θ*|, in the inclusive sample, and also with a requirement of no activity in the forward direction. The total integrated fiducial cross-section is measured to be 215 ± 1 (stat) $^{+23}_{-20}$ (syst.) ± 4 (lumi.) μ b. Within experimental uncertainties the measured integrated cross-section is in good agreement with the QED predictions from the Monte Carlo programs STARLIGHT and SUPERCHIC, confirming the broad features of the initial photon fluxes. The differential cross-sections show systematic differences from these predictions which are more pronounced at high |y ee | and |cos θ*| values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

New Opportunities for Neutrons in Environmental and Biological Sciences

The use of neutron methods in environmental and biological sciences is rapidly emerging and accelerating with the development of new instruments at neutron user facilities. This article, based on a workshop held at Oak Ridge National Laboratory (ORNL), offers insights into the application of neutron techniques in environmental and biological sciences. Here we highlight recent advances and identify key challenges and potential future research areas. These include soil and rhizosphere processes, root water dynamics, plant-microbe interactions, structure and dynamics of biological systems, applications in synthetic biology and enzyme engineering, next-generation bioproducts, biomaterials and bioenergy, nanoscale structure, and fluid dynamics of porous materials in geochemistry. We provide an outlook on emerging opportunities with an emphasis on new capabilities that will be enabled at the Spallation Neutron Source Second Target Station currently under design at ORNL. The mission of scientific neutron user facilities worldwide is to enable science using state-of-the-art neutron capabilities. We aim to encourage researchers in the environmental and biological research community to explore the unique capability afforded by neutrons at these facilities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Deformation and Fracture Behavior of Additively Manufactured 316L Stainless Steel

Tensile deformation and fracture behavior of an additively manufactured (AM) 316L stainless steel (SS) in the as-built, stress-relieved, and solution-annealed conditions was investigated using in situ tensile testing in a scanning electron microscope with an electron back scattering diffraction (SEM–EBSD) detector. Analyses were performed to discuss the characteristic deformation and fracture process of the fine-grained AM 316L SS with and without relaxation heat treatment. The as-built 316L showed the highest strength, and both post-build heat treatments lowered the strength of the alloy. Regardless of the post-build processing, the AM 316L SS showed overall higher strength but slightly lower ductility when compared to the wrought (WT) 316L SS. Analysis of EBSD data indicated that the characteristic microstructural features from AM, such as the complex and fine grain morphology, dislocation network, pores, and silicon-rich oxides, evolved and exerted various roles during the tensile deformation and fracture processes. Further, it was obvious that the interaction of dislocation slips with oxide particles and cavities (or pores) resulted in an accelerated cracking in AM 316L SS. Overall, however, their influence on mechanical behavior was limited, as the genuinely high ductility of 316L SS could help avoid any premature or brittle fracture.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Fundamental Phenomena and Applications of Swift Heavy Ion Irradiations

This review concentrates on the specific properties and characteristics of damage structures generated with high-energy ions in the electronic energy loss regime. Irradiation experiments with so-called swift heavy ions (SHIs) find applications in many different fields, with examples presented in ion-track nanotechnology, radiation hardness analysis of functional materials, and laboratory tests of cosmic radiation. The basics of the SHI-solid interaction are described with special attention to processes in the electronic subsystem. The broad spectrum of damage phenomena is exemplified for various materials and material classes, along with a description of typical characterization techniques. This review also presents state-of-the-art modeling efforts that try to account for the complexity of the coupled processes of the electronic and atomic subsystems. Lastly, a brief discussion at the end of this review on SHI phenomena induced by fission fragments in nuclear materials will highlight the relevance of energetic ion irradiation in nuclear technology applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Object manipulation in immersive virtual environments: Hand Motion tracking technology and snap-to-fit function

There have been recent efforts to use virtual reality and manipulation to train construction workers and inspection. However, there is a lack of research efforts comparing and evaluating virtual manipulation hardware for construction tasks. Moreover, the current practice of virtual manipulation has limited functionality to guide users with the placement of objects in virtual environments. To address these issues, this paper presents 1) a detailed case study that compares three types of manipulation hardware (image-based, infrared-based, and magnetic-based) for construction applications and 2) a snap-to-fit method that improves the VM through solving limitations of the advanced virtual reality interaction metaphors. The latter enhances the placement process for manipulation by comparing two models (e.g., scan and BIM models) for proper placement in assembly scenarios. Finally, the case study results show that magnetic-based systems outperform others in construction scenarios. Lastly, the snap-to-fit function was validated in terms of accuracy and time performance.

42 ENGINEERING↗

DOE OSTI2021

Initial Fermi orbital descriptors for FLOSIC calculations: The quick-FOD method

Fermi orbital descriptors (FODs) play a key role in Fermi-Löwdin orbital self-interaction correction (FLOSIC) calculations used to remove self-interaction from approximate density functionals. Optimal FODs are obtained by minimizing the self-interaction-corrected total energy, and, in this process, identifying initial sets of FODs becomes crucial. Here we propose, implement and test a novel method for automatically initializing FODs, quick-FOD, based on the minimization of an empirical energy expression that involves a Coulomb-like FOD-electron density attraction, an FOD-FOD short-range repulsion, and an exchange-like FOD-density repulsion. Quick-FOD successfully reproduces FOD arrangements in qualitatively good agreement with Lewis theory and with full-fledged FLOSIC calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Dynamics of collision-induced energy transfer

Collisions are of fundamental importance in many relevant physico-chemical phenomena in the gas phase and at the gas-surface interface. Collision-induced energy transfer not only offers a sensitive probe of interatomic interactions, but also impacts an array of processes ranging from transport to reactivity. This perspective highlights some recent advances on collision-induced energy transfer dynamics. In the gas phase, cold collisions revealed remarkable quantum effects and stereodynamics of bimolecular inelastic scattering, which motivated development of new state-to-state quantum scattering methods. For surface processes, experiments of hydrogen atom scattering from various surfaces combined with first-principles molecular dynamics simulations shed valuable light on the relative importance of adiabatic energy transfer to surface phonons and nonadiabatic energy transfer to surface electrons. We outline further challenges in these fields and expect more fruitful interplay between experiment and theory.

Cold collision↗