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At least 649 records · Page 36

Component Selection, Accelerated Testing, and Improved Modeling of AMTEC Systems for Space Power

Alkali metal thermal to electric converter (AMTEC) designs for space power are numerous, but the selection of materials for construction of long-lived AMTEC devices has been limited to electrodes, current collectors, and the solid electrolyte. AMTEC devices with lifetimes greater than 5 years require careful selection and life testing of all hot-side components. The likely selection of a remote condensed design for initial flight test and probable use with a radioisotope heat source in AMTEC powered planet probes requires the device to be constructed to tolerate operating T greater than 1150K, as well as exposure to Na (g) , and Na (liq) on the high pressure side. The temperatures involved make the characterization of high strength and chemical resistance to Na containing Na 2 O critical. Selection among materials which can be worked should not be driven by ease of fabricablity, as high temperature stability is the critical issue. These concepts drive the selecton of Mo alloys for Na (liq) containment in AMTEC cells for T to 1150K operation, as they are significantly stronger than comparable Nb or Ta alloys, are less soluble in Na (liq) containing dissolved Na 2 O, are workable compared with W alloys (which might be used for certain components), and are ductile at the T greater than 500K of proposed AMTEC modules in space applications.

AMTEC↗

First demonstration of multi-MeV proton acceleration from a cryogenic hydrogen ribbon target

We show efficient laser driven proton acceleration up to 14 MeV from a 50 μm thick cryogenic hydrogen ribbon. Pulses of the short pulse laser ELFIE at LULI with a pulse length of ≈ 350 fs at an energy of 8 J per pulse are directed onto the target. The results were then compared to proton spectra from metal and plastic foils with different thicknesses and show a similar good performance both in maximum energy as well as in proton number. Thus, this target type is a promising candidate for experiments with high repetition rate laser systems.

43 PARTICLE ACCELERATORS↗

Mathematical Model of Bubble Sloshing Dynamics for Cryogenic Liquid Helium in Orbital Spacecraft Dewar Container

A generalized mathematical model is investigated of sloshing dynamics for dewar containers, partially filled with a liquid of cryogenic superfluid helium 2, driven by both gravity gradient and jitter accelerations applicable to two types of scientific spacecrafts, which are eligible to carry out spinning motion and/or slew motion to perform scientific observations during normal spacecraft operation. Two examples are given for the Gravity Probe-B (GP-B) with spinning motion, and the Advanced X-Ray Astrophysics Facility-Spectroscopy (AXAF-S) with slew motion, which are responsible for the sloshing dynamics. Explicit mathematical expressions for the modelling of sloshing dynamics to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics will be based on the noninertial frame spacecraft bound coordinate, and we will solve the time-dependent three-dimensional formulations of partial differential equations subject to initial and boundary conditions. Explicit mathematical expressions of boundary conditions lo cover capillary force effects on the liquid-vapor interface in microgravity environments are also derived. Results of the simulations of the mathematical model are illustrated.

Hung, R. J.↗

NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly.

Source record↗

Targeting tissues via dynamic human systems modeling in generative design

Drug discovery is a complex, costly process with high failure rates. A successful drug should bind to a target, be deliverable to an intended site of activity, and promote a desired pharmacological effect without causing toxicity. Typically, these factors are evaluated in series over the course of a pipeline where the number of candidates is sequentially whittled down from a very large initial pool. One promise of AI-driven discovery is the opportunity to evaluate multiple facets of drug performance in parallel. However, despite ML-driven advancements, current models for pharmacological property prediction are exclusively trained to predict molecular properties, ignoring important, dynamic biodistribution and bioactivity effects. Here, we present our progress towards incorporating quantitative systems physiology models into an AI-enabled drug design and molecular generation pipeline. Within a genetic algorithm, we include human-relevant physiologically based pharmacokinetic (PBPK) models. These PBPK models leverage properties that are predicted by a fine-tuned molecular language model. Together, these models will aid in capturing the mapping between molecules and therapeutic outcomes that is necessary to accelerate the drug discovery process.

Fox, Zach↗

Human Stability While Exercising on a VIS Device in Zero Gravity

BACKGROUND: A Vibration Isolation and Stabilization (VIS) system is being designed for use with the European Enhanced Exploration Exercise Device (E4D) [1]. The exercise bar is attached to cables that extend and retract through openings in the E4D platform, which the subject stands on while exercising. Since the E4D is mounted on a moving VIS device, the whole system moves under the subject’s feet. While tension in the cables does help stabilize a crew member in 0g by bracing him or her against the moving platform, flexible cables do not offer full support against falling. This raises the question of whether various exercises that are successfully performed in 1g on a stationary device can be performed without losing balance in 0g on a moving device. Quantifying stability conditions and establishing stability requirements for exercise countermeasure systems is a long-standing challenge and this work helped to inform this specific need for integrated E4D/VIS flight project development. METHODS AND RESULTS: A simplified stability analysis can be attempted based on platform accelerations generated by the VIS device simulation. In this type of analysis, the subject is conceived as standing on the platform in 0g while being held down to it by the tension in the cables. If the sideways acceleration of the platform is such that the cables cannot generate a sufficient moment relative to, e.g., the heels or the toes of the subject to overcome the tipping moment from the inertial forces on the accelerated subject’s body, the subject becomes unstable. This approach, which we refer to as the ‘static’ approximation, indicated failure of all the exercises that were considered in the comprehensive VIS analysis of the E4D. It was realized, however, that platform accelerations are not externally imposed but are themselves induced by the motion of the subject’s body during exercise, and a model calculation confirmed that this drastically altered the tipping moment on the subject, with the potential to even switch the direction in which the body would tip over. This made it imperative to consider in a coupled manner both the motion of the exercising subject’s body and the induced VIS platform motion while considering stability. The coupled dynamics requirement was met by the VIS simulation incorporating time-dependent human mass properties atop the platform and driven by the inertial forces from the prescribed subject motion relative to the platform based on motion-capture recorded human trajectories in 1g on a stationary E4D [2]. To analyze simulation results, a stability criterion was also needed. We do not know how to account for the human ‘control system’ that would take visual and vestibular cues as inputs as the platform moves in 0g. We thus chose to follow an approach we had previously used to analyze the dynamic feasibility of performing a task in lunar gravity along the human body trajectory recorded in 1g [3]. In this approach, one analyzes the center of pressure (COP) between the shoes and the ground (or platform) and checks if the COP remains within the convex hull of the footprints on the ground (or platform), commonly referred to as base of support (BOS). Since pressure is vertical and, in the absence of foot restraints, positive, the COP going outside the BOS indicates that the trajectory recorded in 1g is not dynamically feasible in microgravity and/or on the moving platform of the device. The outcome of the COP-based analysis was that some of the key exercises, especially the deadlift and the back squat exercises, were found to be dynamically feasible for at least some number of the exercise cycles, this number increasing with the cable tension. While this type of stability analysis does not account for the likely alteration of the exercise trajectory from its 1g form in space, it does show that there exist at least some realistic trajectories that pass the dynamic feasibility criterion. This adds confidence that, with further adjustment by the subject of the exercise form in 0g on a moving device, a number of exercises can be performed without losing balance.

D Frenkel↗

Different and Often Opposing Forces Drive the Encapsulation and Multiple Exterior Binding of Charged Guests to a M 4 L 6 Supramolecular Vessel in Water

Abstract The supramolecular assembly [Ga 4 L 6 ] 12− acts as a nanoscale flask to mediate the reactivity of encapsulated reactive guests and also functions as a catalyst to carry out enzyme‐like chemical transformations. The guest binding to the interior cavity and exterior of this host is difficult to untangle because multiple equilibria occur in solution, and only when refining simultaneously data obtained from different techniques, such as NMR, UV/Vis, and calorimetry, can the accurate solution thermodynamics of these host–guest systems be determined. This study reports the driving forces for the inclusion and stepwise exterior guest binding of different aliphatic quaternary ammonium guests to the [Ga 4 L 6 ] 12− assembly. Encapsulation into the host cavity was found to be an entropy‐driven process, whereas exterior ion association is driven either by enthalpically favorable attractive forces or by the entropy gain due to desolvation, depending on guest size and character. The analysis of the energetics of reaction may help predicting and understanding the intimate role and contribution of the transition state in those rate‐accelerated reactions involving this supramolecular assembly as an enzyme‐like molecular flask.

Sgarlata, Carmelo↗

Long duration X-ray drive hydrodynamics experiments relevant for laboratory astrophysics

The advent of high-power lasers facilities such as the National Ignition Facility (NIF), and the Laser Megajoule (LMJ) in the near future, opens a new era in the field of High Energy Density Laboratory Astrophysics. These versatile laser facilities will provide unique platforms to study the rich physics of nonlinear and turbulent mixing flows. The extended laser pulse duration could be harnessed to accelerate targets over much larger distances and longer time periods than previously achieved. Here, we report on the first results acquired on NIF with the ablative Rayleigh–Taylor Instability (RTI) platform. A 20-ns X-ray drive is tailored to accelerate planar modulated samples into the highly-nonlinear bubble merger regime. Based on the analogy between flames front and ablation front, highly nonlinear RTI measurements at ablation front can provide important insights into the initial deflagration stage of thermonuclear supernova of Type Ia. We also report on an innovative concept used to create even longer drive on multi-beam laser facilities. The multi-barrel hohlraum (Gattling Gun) approach consists, here, of three adjacent cavities, driven in succession in time. This novel concept has been validated on the Omega EP laser system. The three cavities were irradiated with three 6–10 ns pulse UV beams and a 30 ns, 90 eV X-ray radiation drive was measured with the time-resolved X-ray spectrometer μDMX. This concept is promising to investigate the pillar structures in the Eagle Nebula or for photoionization studies which require a steady light source of sufficient duration to recreate relevant physics.

Molecular clouds↗

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗

NEUTRON-STAR MERGER EJECTA AS OBSTACLES TO NEUTRINO-POWERED JETS OF GAMMA-RAY BURSTS

We present the first special relativistic, axisymmetric hydrodynamic simulations of black hole-torus systems (approximating general relativistic gravity) as remnants of binary-neutron star (NS–NS) and neutron star–black hole (NS–BH) mergers, in which the viscously driven evolution of the accretion torus is followed with self-consistent energy-dependent neutrino transport and the interaction with the cloud of dynamical ejecta expelled during the NS–NS merging is taken into account. The modeled torus masses, BH masses and spins, and the ejecta masses, velocities, and spatial distributions are adopted from relativistic merger simulations. We find that energy deposition by neutrino annihilation can accelerate outflows with initially high Lorentz factors along polar low-density funnels, but only in mergers with extremely low baryon pollution in the polar regions. NS–BH mergers, where polar mass ejection during the merging phase is absent, provide sufficiently baryon-poor environments to enable neutrino-powered, ultrarelativistic jets with terminal Lorentz factors above 100 and considerable dynamical collimation, favoring short gamma-ray bursts (sGRBs), although their typical energies and durations might be too small to explain the majority of events. In the case of NS–NS mergers, however, neutrino emission of the accreting and viscously spreading torus is too short and too weak to yield enough energy for the outflows to break out from the surrounding ejecta shell as highly relativistic jets. We conclude that neutrino annihilation alone cannot power sGRBs from NS–NS mergers.

79 ASTRONOMY AND ASTROPHYSICS↗

Superfluid helium sloshing dynamics induced oscillations and fluctuations of angular momentum, force and moment actuated on spacecraft driven by gravity gradient or jitter acceleration associated with slew motion

The generalized mathematical formulation of sloshing dynamics for partially filled liquid of cryogenic superfluid helium II in dewar containers driven by the gravity gradient and jitter accelerations associated with slew motion for the purpose to perform scientific observation during the normal spacecraft operation are investigated. An example is given with the Advanced X-Ray Astrophysics Facility-Spectroscopy (AXAF-S) for slew motion which is responsible for the sloshing dynamics. The jitter accelerations include slew motion, spinning motion, atmospheric drag on the spacecraft, spacecraft attitude motions arising from machinery vibrations, thruster firing, pointing control of spacecraft, crew motion, etc. Explicit mathematical expressions to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics is based on the non-inertia frame spacecraft bound coordinate, and solve time-dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. The explicit mathematical expressions of boundary conditions to cover capillary force effect on the liquid-vapor interface in microgravity environments are also derived. The formulations of fluid moment and angular moment fluctuations in fluid profiles induced by the sloshing dynamics, together with fluid stress and moment fluctuations exerted on the spacecraft dewar containers have also been derived. Examples are also given for cases applicable to the AXAF-S spacecraft sloshing dynamics associated with slew motion.

Hung, R. J.↗

Accelerating Nuclear-Integrated Data Centers in the USA: SWOT Analysis, Power-Thermal Management Strategies, and Industrial-Scale Demonstration and Potential Deployment

Driven by the growth in digital services, cloud computing, AI, and manufacturing, data centers face rising energy demands that challenge traditional power sources and cooling efficiency. This study explores using nuclear power to meet these demands, focusing on accelerated reactor technology deployment and highlighting needs such as N+1/N+2 power supplies and integrated power-thermal management. A SWOT analysis addresses grid connectivity, reactors, and site selection, particularly DOE sites. Reactor technology demonstration and deployment could be accelerated by leveraging test facilities such as MARVEL, MAGNET, TED, FAS, DOME, LOTUS, ATR, Energy System Proving Grounds, and upcoming Energy Launch Pads, along with modeling and simulation tools such as RELAP5, MOOSE, VERA, RAVEN, and FORCE. The potential power and thermal management options, including various cooling technologies, waste-heat utilization, and an industrial-scale demonstration plan, aim to accelerate the integration of nuclear power and data centers in the USA, while emphasizing community and stakeholder engagement and synergistic efforts.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Convergence of Vehicle and Infrastructure Data for Traffic and Demand Management

The increasing availability of highly granular, vehicle trajectory data combined with ever increasing stores of roadway sensor data has provided unparalleled observability into the operation of our urban roadway networks. These data sources are quickly moving from research and prototype environments into full-scale commercial deployment and data offerings. The observability gained allows for increased control opportunities to enhance transportation mobility, safety and energy efficiency. The National Renewable Energy Laboratory (NREL) is involved in three initiatives to leverage these data for positive outcomes: 1) In 2015 NREL, in cooperation with industry and university partners, was awarded an ARPA-E research grant to research a control architecture to incentivize individual travelers toward more sustainable travel behavior. Based on real-time data on the traveler's destination and state of the system, the traveler is presented with route and/or mode choices and offered incentives to accept sustainable alternatives over less-sustainable ones. The project tests the extent to which small incentives can influence, or tip the balance toward more sustainable travel behavior. 2) Although commercial sources of travel time and speed have emerged in recent years based on vehicle probe data, volume estimates continue to rely primarily on historical count data factored for the time of day, day of week, and season of year. Real-time volume flows would enable better tools, simulation in the loop, and ultimately more effective control outcomes. NREL in cooperation with the University of Maryland and industry traffic data providers (INRIX, HERE and TomTom), are attempting to accelerate the timeframe to a viable real-time vehicle volume data feed based on probe data. 3) Signal control on urban arterials for years has had to rely on models rather than measured data to assess performance. High-resolution controller data and low-cost re-identification data now allows for direct measurement of the quality of progression along a corridor. Though still requiring an investment in equipment and communications, these data sources are transforming traffic signal management to a data driven, performance management basis. Ever increasing availability of granular GPS trace data from automobiles may allow for assessment of traffic signal performance, allowing for signal optimization while minimizing the investment in additional sensors and communication infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗

Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic

Automated Vehicles (AV) can potentially improve the performance of transportation system by reducing human errors and enhancing mobility and safety. In lower levels of automation, humans are still controlling the vehicle and receiving some advisory information regarding their surrounding environment. This paper investigates the safety impact of low and high levels of AVs, and their interaction with conventional human-driven vehicles at intersections. In order to enhance our understanding of the future interactions between conventional vehicles with AVs, we developed a framework to simulate the mixed traffic environment. Different market penetration scenarios are simulated using VENTOS (VEhicular NeTwork Open Simulator) software. A modified Wiedemann car-following model was calibrated to represent the behavior of human drivers of both conventional and low-level AVs, while an Adaptive Cruise Control model was used to represent high-level AVs. Notably, this study investigates purely the automation improvement in the system. We modified the acceleration and deceleration regimes of the Wiedemann model and tuned it by harnessing real-world connected vehicle data. Next, the simulation was calibrated utilizing two measures of driving volatility to ensure it closely represents the volatility measures of the real-world data. To evaluate the safety performance of a representative intersection under different scenarios, the number of longitudinal conflicts and driving volatility are used as surrogate safety indicators. The results reveal that increase in market penetration rate of LAVs and HAVs substantially improves intersection safety performance by reducing the number of conflicts and driving volatility.

Arvin, Ramin↗

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets

Packed columns are commonly used in post-combustion processes to capture CO 2 emissions by providing enhanced contact area between a CO 2 -laden gas and CO 2 -absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs), computational fluid dynamics (CFD) can be used to model the liquid–gas countercurrent flow hydrodynamics in these columns and derive key determinants of CO 2 -capture efficiency. However, the large design space of these systems hinders the application of CFD for design optimization due to its high computational cost. In contrast, data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. We build our surrogates using MeshGraphNets (MGN), a graph neural network framework that efficiently learns and produces mesh-based simulations. We apply MGN to a random packed column modeled with over 160K graph nodes and a design space consisting of three key input parameters: solvent surface tension, inlet velocity, and contact angle. Our models can adapt to a wide range of these parameters and accurately predict the complex interactions within the system at rates over 1700 times faster than CFD, affirming its practicality in downstream design optimization tasks. This underscores the robustness and versatility of MGN in modeling complex fluid dynamics for large-scale CCS analyses.

97 MATHEMATICS AND COMPUTING↗

MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank

Purpose: To develop a method to exploit real-time dynamic machine and couch parameter control during linear accelerator (LINAC) beam delivery to facilitate efficient performance of TG-142 suggested, Annual LINAC QA tests. Methods: Varian’s TrueBeam Developer Mode (Varian Medical Systems, Palo Alto, CA) facilitates control of Varian’s TrueBeam LINAC via instructions provided in Extensible Markup Language (XML) files. This allows machine and couch parameters to be varied dynamically, in real-time, during beam delivery. Custom XML files were created to allow for the collection of (1) continuous Tissue Maximum Ratios (TMRs), (2) beam profiles, and (3) continuous output factors using a 1D-scanning tank. TMRs were acquired by orienting an ionization chamber (IC) at isocenter (depth=25cm) and synchronizing a depth scan towards the water surface while lowering the couch at 1mm/s. For beam profiles, the couch was driven laterally and longitudinally while logging IC electrometer readings. Output factors (OFs) where collected by continually varying field sizes (4×4 to 30×30-cm{sup 2}) at a constant speed of 6.66 mm/s. To validate measurements, comparisons were made to data collected using traditional methods (e.g. 1D or 3D tank). Results: All data collecting using the proposed methods agreed with traditionally collected data (TMRs within 1%, OFs within 0.5% and beam profile agreement within 1% / 1mm) while taking less time to collect (factor of approximately 1/10) and with a finer sample resolution. Conclusion: TrueBeam developer mode facilitates collection of continuous data with the same accuracy as traditionally collected data with a finer resolution in less time. Results demonstrate an order of magnitude increase in sampled resolution and an order of magnitude reduction in collection time compared to traditional acquisition methods (e.g. 3D scanning tank). We are currently extending this approach to perform other TG-142 tasks.

61 RADIATION PROTECTION AND DOSIMETRY↗

Novel Hybrid Monte Carlo/Deterministic Technique for Shutdown Dose Rate Analyses of Fusion Energy Systems

The rigorous 2-step (R2S) method uses three-dimensional Monte Carlo transport simulations to calculate the shutdown dose rate (SDDR) in fusion reactors. Accurate full-scale R2S calculations are impractical in fusion reactors because they require calculating space- and energy-dependent neutron fluxes everywhere inside the reactor. The use of global Monte Carlo variance reduction techniques was suggested for accelerating the neutron transport calculation of the R2S method. The prohibitive computational costs of these approaches, which increase with the problem size and amount of shielding materials, inhibit their use in the accurate full-scale neutronics analyses of fusion reactors. This paper describes a novel hybrid Monte Carlo/deterministic technique that uses the Consistent Adjoint Driven Importance Sampling (CADIS) methodology but focuses on multi-step shielding calculations. The Multi-Step CADIS (MS-CADIS) method speeds up the Monte Carlo neutron calculation of the R2S method using an importance function that represents the importance of the neutrons to the final SDDR. Using a simplified example, preliminarily results showed that the use of MS-CADIS enhanced the efficiency of the neutron Monte Carlo simulation of an SDDR calculation by a factor of 550 compared to standard global variance reduction techniques, and that the increase over analog Monte Carlo is higher than 10,000.

hybrid Monte Carlo/deterministic↗

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗