Engineering topics

Li, Dongsheng

Publications and source records attributed to Li, Dongsheng.

9 records

DOE OSTI2024

Defect Self-Elimination in Nanocube Superlattices Through the Interplay of Brownian, van der Waals, and Ligand-Based Forces and Torques

Understanding defect healing is necessary for realizing devices based on nanoparticle-superlattices with controlled electronic and optoelectronic performance. However, key questions remain regarding nanoparticle interactions and resulting assembly dynamics and defect self-elimination. In particular, for anisotropic particles, additional degrees of freedom beyond those of spherical particles, such as rotational dynamics and toques, significantly impact phenomena. Here, in this work, we investigate nanocube (NC) superlattices by employing liquid phase transmission electron microscopy, continuum theories and molecular dynamics simulations. Analyzing interparticle forces and torques due to van der Waals, Brownian, and ligand interactions, we find that the latter dominates and that the anisotropic NC morphology introduces significant torques. In imperfect regions, unbalanced forces and torques induce NC translations and rotations that are transmitted to neighboring NCs, prompting “chain interactions” in a 2D network, which lead to defect self-elimination. This fundamental understanding will further enable design and fabrication of defect-free superlattices, as well as those with tailored defects, via assembly of anisotropic particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

The transformation of lepidocrocite (γ-FeOOH) with Fe($\tiny{II}$) (aq) in slightly acidic media: intermediate pathways and biomimetic behavior

Lepidocrocite (LP) is commonly found in natural or anthropogenic environments and oxidized alloy steel waste storage containers. Despite its importance, the end products formed and its mineral transformation pathways, including intermediate steps and underlying mechanisms under Fe(II) (aq) catalysis still need to be clarified due to decades of dispersed research. Here, in this work, we investigated LP's catalytic transformation with 10 mM and 0.2 mM Fe(II) (aq) at their natural solution pH's via bulk (X-ray Diffraction/XRD, Raman and Attenuated Total Reflectance Fourier Transform Infrared/ATR-FTIR) and micro/nano-scale (semi in situ Transmission Electron Microscopy/TEM) analysis. In general, we observed that goethite (GT) and LP were the main end products. However, a series of two major distinct intermediate events that were initiated by a dissolution type of reaction along with an “induction period” (lack of dissolution) on LP occurred. Fascinatingly, two of the intermediate steps along its mineral transformation presented novel types of non-classical mechanisms of crystallization via some type of guided oriented particle attachment. Furthermore, one of these intermediate steps is biomimetic in appearance, similar to what is observed during bacterial particle attachment. However, it uses inorganic nano-wire antennas that have a sensory-like function as observed with bacterial fimbriae and/or flagellum through an electron transparent film (similar to a bio-film matrix). Finally, this work leads us to comprehend the evolution of some well documented crystal morphologies for GT commonly observed in natural and anthropogenic settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Achieving high-ZT in Te/Se-based thermoelectric materials via volume-constrained shear-induced plastic deformation

This study investigated the correlation between severe plastic deformation and microstructural evolution, along with the corresponding response in the thermoelectric performance. Specifically, severe plastic deformation introduced into intrinsically brittle thermoelectric materials like Bi 2 Te 3 - x Se x leads to microstructural changes ranging from nano- to micro- scales, including phase transformation, phase segregation, and stacking faults. The resultant residual strain and lattice defects in the Bi 2 Te 3-x Se x materials led to engineering of electronic bands, which increases the effective mass of electrons while controlling their concentration, thereby enhancing the power factor.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Effect of Solvent Composition on Non-DLVO Forces and Oriented Attachment of Zinc Oxide Nanoparticles

Oriented attachment (OA) occurs when nanoparticles in solution align their crystallographic axes prior to colliding and subsequently fuse into single crystals. Traditional colloidal theories such as DLVO provide a framework for evaluating OA but fail to capture key particle interactions due to the atomistic details of both the crystal structure and the interfacial solution structure. Using zinc oxide as a model system, we investigated the effect of the solvent on short-ranged and long-ranged particle interactions and the resulting OA mechanism. In situ TEM imaging showed that ZnO nanocrystals in toluene undergo long-range attraction comparable to 1kT at separations of 10 nm and 3kT near particle contact. These observations were rationalized by considering non-DLVO interactions, namely dipole-dipole forces and torques between the polar ZnO nanocrystals. Langevin dynamics simulations showed stronger interactions in toluene compared to methanol solvents, consistent with the experimental results. Concurrently, we performed atomic force microscopy measurements using ZnO-coated probes for the short-ranged interaction. Our data provided valuable insights into another type of non-DLVO interaction, namely the repulsive solvation force. Specifically, the solvation force was stronger in water compared to ethanol and methanol, due to the stronger hydrogen bonding and denser packing of water molecules at the interface. In conclusion, our results highlight the importance of non-DLVO forces in a general framework for understanding and predicting particle aggregation and attachment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

High-throughput, Ultra-fast Laser Sintering of Ceramics and AI Based Prediction on Processing-Microstructure-Property Relationships

We report high-throughput, ultra-fast laser sintering of alumina sample array and characterization of sample units’ microstructure and hardness, as a fast exploration of laser processing parameters, microstructure, and property. These experimental data were used to train machine-learning (ML) models. Accurate ML predictions were demonstrated for the processing-microstructure-property relationship, specifically in (1) prediction of the microstructure of alumina under arbitrary laser power and (2) prediction of the expected microstructure from the desired hardness. An independent neural network was developed and showed that ML-predicted microstructure had less than 10% error from real ones, in terms of projected hardness. To monitor the microstructure during laser sintering, we demonstrated an ML model that can instantaneously predict ceramic’s microstructure at the laser spot, based on the laser spot brightness. The ML model can generate more than 10 predictions per second, and the error in average grain size was less than 5% from the experimental observations.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Uneven Strain Distribution Induces Consecutive Dislocation Slipping, Plane Gliding, and Subsequent Detwinning of Penta-Twinned Nanoparticles

Twin structures possess distinct physical and chemical properties by virtue of their specific twin configuration. However, twinning and detwinning processes are not fully understood on the atomic scale. Integrating in situ high resolution transmission electron microscopy and molecular dynamic simulations, here, we find tensile strain in the asymmetrical 5-fold twins of Au nanoparticles leads to twin boundary migration through dislocation sliding (slipping of an atomic layer) along twin boundaries and dislocation reactions at the 5-fold axis under an electron beam. Migration of one or two layers of twin planes is governed by energy barriers, but overall, the total energy, including surface, lattice strain, and twin boundary energy, is relaxed after consecutive twin boundary migration, leading to a detwinning process. In addition, surface rearrangement of 5-fold twinned nanoparticles can aid in the detwinning process.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High‐Throughput Computational Guided Development of Refractory Complex Concentrated Alloys‐based Composite

ULTIMATE is a leading-edge DOE program to develop ultrahigh temperature materials for gas turbine use in the aviation and power generation industries. This team, headquartered at West Virginia University and including collaborators from the National Energy Technology Laboratory and Advanced Manufacturing LLC, has developed a new class of ultra-high temperature Refractory Complex Concentrated Alloys-based Composites (RCCC) for high temperature applications such as combustion turbines used in the aerospace and energy industries. The RCCC consist of Refractory Complex Concentrated Alloys (RCCA) mixed with particles of Refractory High Entropy Carbides, to increase RCCA strength to withstand extreme conditions. These new materials optimize the balance among strength, creep (deformation), density, and stability at 1300 °C (2372 °F), while maintaining ductility once the alloy cools to room temperature. The research team has developed advanced manufacturing processes using the pulsed electric current and laser 3D printing to produce test coupons of these materials.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Ultrasmall Pd Clusters in FER Zeolite Alleviate CO Poisoning for Effective Low-Temperature Carbon Monoxide Oxidation

Ultra small Pd 4 clusters form in the micropores of FER zeolite during low temperature treatment (100 °C) in the presence of humid CO gas. They effectively catalyze CO oxidation below 100°C, whereas Pd nanoparticles are not active as they are poisoned by CO. Using catalytic measurements, infrared (IR) spectroscopy, X-ray absorption spectroscopy (EXAFS), microscopy, and density functional theory calculations we provide the molecular level insight into this previously unreported phenomenon. Pd nanoparticles get covered with CO at low temperatures which effectively blocks O 2 activation until CO desorption occurs. Small Pd clusters in zeolites, in contrast, demonstrate fluxional behavior in the presence of CO, which significantly increases their affinity for binding O 2 . In conclusion, our study shows a pathway for achieving low temperature CO oxidation activity on the basis of well-defined Pd/zeolite system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗