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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Automated Construction of Artificial Lattice Structures with Designer Electronic States

Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.

Algorithms↗
NASA NTRSDate not supplied

SOLL-E: A Module Transport and Placement Robot for Autonomous Assembly of Discrete Lattice Structures

This paper presents the design and development of a transport and placement robot that demonstrates autonomous assembly of structural building blocks. The robots are intended to serve as a critical component of automated structural assembly and maintenance systems. The Scaling Omni-directional Lattice Locomoting Explorer (SOLL-E) uses a 5-DoF bipedal inchworm locomotion architecture with locking foot and cargo grippers. The locomotion system employs large magnet gap diameter BLDC motors with moderate timing belt gearing for primary joints, and DC planetary gearmotors for turning. Foot and cargo grippers are identical, with servo-actuated locking mechanisms. Three modular controller boards are used to control these actuators in real-time, with command and telemetry data transferred between the server and each controller board via WiFi. Functionality and performance were evaluated in a ground demonstration.

robotics↗
DOE OSTI2023

Prediction and Validation of Flow Properties in Porous Lattice Structures

High-porosity metal foams have been extensively studied as an attractive candidate for efficient and compact heat exchanger design. With the advancements in additive manufacturing, such foams can be manufactured with controlled topology to yield highly tailorable mechanical and transport properties. In this study, a lattice Boltzmann method (LBM)-based pore-scale model is implemented to simulate the fluid flow in additively manufactured (AM) metal foams with unit cell topologies of Cube, Face Diagonal (FD)-Cube, Tetrakaidecahedron (TKD), and Octet lattices. The pressure gradient versus average velocity profiles predicted by the LBM model were validated against in-house measurements on the AM lattice samples with the same unit cell topologies. Based on the simulation results, a novel hybrid model is proposed to accurately predict the volume averaged flow properties (permeability and inertial coefficients) of the four structures. Specifically, the linear LBM (neglecting inertial forces) is first implemented to obtain the intrinsic permeability, and then the standard LBM is applied to obtain the inertial coefficient. Convenient correlations for those flow properties as a function of porosity and fiber diameter are constructed. The effects of the AM print qualities on the flow properties are also discussed. The advantages of the hybrid model compared to the polynomial fitting approach for determining flow properties are discussed and compared quantitatively. The hybrid model and presented results are valuable for flow and thermal transport evaluation when designing new metal foams for specific applications and with different materials and topologies. Finally, the presented correlations based on pore-scale simulations can also be conveniently used in volume-averaged models to predict the macroscale flow behavior in such complex structures.

42 ENGINEERING↗
DOE OSTI2020

Synchrotron CT imaging of lattice structures with engineered defects

Understanding mechanical failure, crack propagation, and compressive behavior at the micrometer scale is essential for tailoring material properties for structural performance in cellular materials. Typically, modeling of traditional polymer foam materials is clouded by the lack of control in material morphology and its inherent stochastic structure. Additive manufacturing with sub-micrometer resolution provides a direct path for experimenters to specifically tailor structures needed by modelers to explicitly probe mechanical performance. Using laboratory-based 3D X-ray computed tomographic imaging (CT), the examination of deformation and damage provides a critical path to understand how these soft materials behave. Additionally, synchrotron CT yields realistic information at higher strain rates to directly validate the robustness of our finite element modeling. For this study, nanolithographic printing was employed to generate a series of engineered lattices with increasing levels of defects through the random removal of ligaments. These structures were mechanically tested and imaged with laboratory-based microCT. Additionally, synchrotron experiments were conducted in which the structures were imaged in 3D at 14 Hz during compression at a 0.4 s –1 strain rate. These 3D images show the changes in the structure as the ligaments bend, buckle and fracture in real time. This technique provides a robust framework for developing our methodologies and future exploration of engineered structures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Embedded 3D printing of isotropically enhanced lattice structure with programmable elasticity via three-dimensional fiber alignment

Engineered composites with fiber orientation in a complete three-dimensional (3D) context are highly desired for maximizing structural performance as they mimic the well-organized fiber arrangement in natural composites. However, most fabrication techniques lack the capability for through-plane (z-axis) alignment, limiting the possibility for structural design and performance optimization. In this study, we present an embedded 3D printing approach that enables complete 3D fiber alignment, including region-specific alignment control along the through-plane direction. Our method utilizes the extrusion and suspension of composite inks within a supporting matrix. By regionally adjusting the ink extrusion rate and nozzle translation rate, we locally manipulated the fiber arrangement within the composite 3D architecture. Here, we demonstrate that the 3D alignment of carbon fibers in a structural composite significantly enhances both mechanical properties and thermal conductivity in the in-plane and through-plane directions. Furthermore, by strategically arranging regional fiber orientations within micro-architected materials, we fabricated metamaterial engineered composites with programmable anisotropy ratio and directional moduli.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures

Significance The efficient utilization of electrical energy is an increasingly important challenge, especially as renewable energy sources become cheaper and demand increases. Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy. Their commercial viability and ultimate adoption hinge on attaining high current densities to drive cost competitiveness. There are limited opportunities for engineering FTE materials, as these are often random, disordered media. Alternatively, three-dimensional (3D)–printed FTEs provide the opportunity to quickly explore the impact of engineered electrode architectures on device performance. We demonstrate that 3D-printed FTEs have the potential to exceed the performance of conventional materials by using the expanded design freedom to engineer the internal flow.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Lattice structure and dynamics of sparse molecular crystals: OsO4 and RuO4

This dataset contains input and output files from DFT simulations used to reproduce the electronic and phonon calculations of bulk and molecular OsO₄ and RuO₄. The files include data from initial electronic structure and phonon calculations performed using different functionals: PBE, PBEsol, and vdW-DF-optB86b. The computed phonon frequencies are compared with Raman crystal and gas-phase frequencies from existing literature, while the calculated phonon density of states (PhDOS) is compared with experimental PhDOS data.

36 MATERIALS SCIENCE↗