Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “atomically precise”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Grafted polythiophene pendent polymer brushes and their electronanopatterning

Here electrochemical nanolithography using grafted polymer brushes with terthiophene (3T) pendent was investigated. The film was fabricated by surface electropolymerization of a reversible addition-fragmentation chain-transfer agent macroinitiator containing a 3T pendant molecule and the subsequent polymer brush growth from a 3T functionalized methacrylate monomer (3T-Methacrylate). Electrochemical nanolithography and patterning were done using conducting atomic force microscopy (C-AFM) enabling precise nanopattern fabrication. In contrast to direct nanowriting, dip pen nanolithography, and nanolithographic additive manufacturing, the electrochemical nanolithography can be readily facilitated by applying a bias voltage between a conductive AFM tip and the grafted polymer brush film at ambient conditions and without ink transfer. The height and electrical resistance of the nanopatterns were dependent on the writing parameters (i.e. applied bias voltage and scan rate).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improved high-precision mass measurements of mid-shell neon isotopes

New mass values measured with the TITAN MR-TOF-MS are reported for the short-lived isotopes 24-26 Ne, produced at TRIUMF's ISAC facility using a uranium carbide target and cold FEBIAD ion source. A least-squares adjustment within the framework of the Atomic Mass Evaluation was performed and the improved precision of the new mass values is highlighted. The improved mass accuracy in this N = 14mid-shell region can also point to the refinement in values of the charge radii. By reducing the mass uncertainty of isotopes, their contribution of the mass shift uncertainty in laser spectroscopy can be negated. The work is part of developments for reaching the N = 20 Island of Inversion, where high molecular contamination hinders mass measurements of the neon isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light–matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Benchmarking Correlation-Consistent Basis Sets for Frequency-Dependent Polarizabilities with Multiresolution Analysis

This paper presents the first converged frequency-dependent HF polarizability results for general molecules, on a set of 89 closed-shell atoms and molecules. The solver employs multiresolution analysis (MRA) in a multiwavelet basis to compute both ground and response states to a guaranteed precision, which are validated against independent numerical grid calculations on atoms and linear molecules. The MRA ground-state energies and response properties are used to evaluate results in correlation-consistent basis sets up to 5Z augmented with either single or double diffuse functions and core-polarization functions. Systematic trends are revealed through consideration of chemical composition as well as the use of machine learning to cluster convergence trends, the latter suggesting the possibility of learning and correcting basis-set error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Revealing the Latent Atomic World Through Data-Driven Microscopy

Many emerging technologies depend on the precise design of materials structure, chemistry, and defects. As devices shrink, manufacturing tolerances tighten, and performance envelopes improve, we must increasingly measure and manipulate materials at or near the single atom level. Here we describe how transmission electron microscopy (TEM) underpins our ability to see and direct the latent atomic world. We review a selection of our recent high-resolution TEM studies of the synthesis of oxide-based nanomaterials and their evolution in extreme environments. We then discuss powerful new artificial intelligence (AI) and machine learning (ML) approaches we have developed for rich, reproducible, and scalable experimentation. Furthermore, we conclude by discussing future developments that will enable new materials for breakthrough technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Vapor–Phase Synthesis of Electrocatalytic Covalent Organic Frameworks

The inability to process many covalent organic frameworks (COFs) as thin films plagues their widespread utilization. Herein, a vapor-phase pathway for the bottom-up synthesis of a class of porphyrin-based COFs is presented. This approach allows integrating electrocatalysts made of metal-ion-containing COFs into the electrodes’ architectures in a single-step synthesis and deposition. By precisely controlling the metal sites at the atomic level, remarkable electrocatalytic performance is achieved, resulting in unprecedentedly high mass activity values. How the choice of metal atoms, i.e., cobalt and copper, can determine the catalytic activities of POR-COFs is demonstrated. The theoretical data proves that the Cu site is highly active for nitrate conversion to ammonia on the synthesized COFs.

25 ENERGY STORAGE↗
DOE OSTI2026

High sensitivity measurement of femtogram-level 238 Pu by thermal ionization mass spectrometry with correction of background 238 U

Low-concentration plutonium isotopic measurements provide a valuable fingerprint to identify possible material origins in the context of environmental contamination monitoring, environmental tracing, nuclear safeguards, nuclear forensics, and treaty monitoring. Thermal ionization mass spectrometry (TIMS) has long been recognized as one of the most sensitive techniques for plutonium isotopic measurement, but has not generally been utilized for 238 Pu determination, especially at low concentrations, due to an isobaric interference from 238 U, prevalent as background. Here, this work demonstrates a new analytical technique for correction of background 238 U from the 238 Pu counts collected during a TIMS analysis. The technique takes advantage of the higher ionization temperature of U relative to Pu and uses a 235 U tracer added after plutonium purification chemistry for 238 U semi-quantitative determination. This technique has been successfully applied to the determination of 238 Pu concentration and the 238 Pu/ 239 Pu ratio in sample types including single-isotope standards, isotopic certified reference materials, matrix-containing environmental reference materials, and simulated nuclear detonation debris. The results have been directly compared on a sample-by-sample basis to alpha spectrometry results. The detection limit by this new technique is 0.23 fg 238 Pu, which was previously unachievable by mass spectrometry and is possible in around 1 h of analysis time post-chemistry compared to weeks of required counting time by alpha spectrometry (at the same atom amount). We also present original, high precision data for Pu isotope concentrations in IAEA-384, Fangataufa Sediment, including 242 Pu results for the first time. The new technique allows measurement of a key isotope, 238 Pu, that was previously not measured in small environmental or nuclear forensics collections.

238Pu↗
DOE OSTI2025

Electron correlation and relativistic effects in the excited states of radium monofluoride

Highly accurate and precise electronic structure calculations of heavy radioactive atoms and their molecules are important for several research areas, including chemical, nuclear, and particle physics. Ab initio quantum chemistry can elucidate structural details in these systems that emerge from the interplay of relativistic and electron correlation effects, but the large number of electrons complicates the calculations, and the scarcity of experiments prevents insightful theory-experiment comparisons. Here we report the spectroscopy of the 14 lowest excited electronic states in the radioactive molecule radium monofluoride (RaF), which is proposed as a sensitive probe for searches of new physics. The observed excitation energies are compared with state-of-the-art relativistic Fock-space coupled cluster calculations, which achieve an agreement of ≥99.64% (within ~12 meV) with experiment for all states. Guided by theory, a firm assignment of the angular momentum and term symbol is made for 10 states and a tentative assignment for 4 states. The role of high-order electron correlation and quantum electrodynamics effects in the excitation energies is studied and found to be important for all states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Electron ptychography achieves atomic-resolution limits set by lattice vibrations

Transmission electron microscopes use electrons with wavelengths of a few picometers, potentially capable of imaging individual atoms in solids at a resolution ultimately set by the intrinsic size of an atom. However, owing to lens aberrations and multiple scattering of electrons in the sample, the image resolution is reduced by a factor of 3 to 10. By inversely solving the multiple scattering problem and overcoming the electron-probe aberrations using electron ptychography, we demonstrate an instrumental blurring of less than 20 picometers and a linear phase response in thick samples. The measured widths of atomic columns are limited by thermal fluctuations of the atoms. As a result, our method is also capable of locating embedded atomic dopant atoms in all three dimensions with subnanometer precision from only a single projection measurement.

42 ENGINEERING↗
DOE OSTI2024

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Precision measurement of Compton scattering in silicon with a skipper CCD for dark matter detection

Experiments aiming to directly detect dark matter through particle recoils can achieve energy thresholds of $\mathcal{O}(1\,\mathrm{eV})$. In this regime, ionization signals from small-angle Compton scatters of environmental $\gamma$-rays constitute a significant background. Monte Carlo simulations used to build background models have not been experimentally validated at these low energies. We report a precision measurement of Compton scattering on silicon atomic shell electrons down to 23$\,$eV. A skipper charge-coupled device (CCD) with single-electron resolution, developed for the DAMIC-M experiment, was exposed to a $^{241}$Am $\gamma$-ray source over several months. Features associated with the silicon K, L$_{1}$, and L$_{2,3}$-shells are clearly identified, and scattering on valence electrons is detected for the first time below 100$\,$eV. We find that the relativistic impulse approximation for Compton scattering, which is implemented in Monte Carlo simulations commonly used by direct detection experiments, does not reproduce the measured spectrum below 0.5$\,$keV. The data are in better agreement with $ab$$initio$ calculations originally developed for X-ray absorption spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Autonomous self-repair in piezoelectric molecular crystals

Living tissue uses stress-accumulated electrical charge to close wounds. Self-repairing synthetic materials, which are typically soft and amorphous, usually require external stimuli, prolonged physical contact, and long healing times. We overcome many of these limitations in piezoelectric bipyrazole organic crystals, which recombine following mechanical fracture without any external direction, autonomously self-healing in milliseconds with crystallographic precision. Kelvin probe force microscopy, birefringence experiments, and atomic-resolution structural studies reveal that these noncentrosymmetric crystals, with a combination of hydrogen bonds and dispersive interactions, develop large stress-induced opposite electrical charges on fracture surfaces, prompting an electrostatically driven precise recombination of the pieces via diffusionless self-healing.

Bhunia, Surojit↗
DOE OSTI2026

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗
DOE OSTI2025

Single Metal Atom Catalysts Prepared by Diluted Atomic Layer Deposition

The scalable and facile preparation of single-atom catalysts remains a critical challenge. Here, in this study, we introduce diluted atomic layer deposition (DALD), a unique approach for synthesizing supported metal catalysts with precisely tunable loadings. Unlike conventional metal deposition by ALD which uses pure metal precursors, DALD employs a diluted precursor mixture, combining organometallic precursors with the corresponding free ligand in controlled ratios. The method enables precise control over metal loadings, allowing the synthesis of structures ranging from nanoparticles to isolated single atoms, as exemplified by Ir, Rh, and Pt on high-surface-area γ-Al 2 O 3 . With its inherent simplicity and exceptional efficiency in metal precursor utilization, DALD represents a highly scalable strategy, unlocking opportunities for integrating single-atom catalysts into industrial processes.

36 MATERIALS SCIENCE↗