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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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Pulsed Laser Additive Manufacturing for 316L Stainless Steel: A New Approach to Control Subgrain Cellular Structure
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In vitro study of enhanced photodynamic cancer cell killing effect by nanometer-thick gold nanosheets
Abstract not provided
3D RNA nanocage for encapsulation and shielding of hydrophobic biomolecules to improve the in vivo biodistribution
Ribonucleic acid (RNA) nanotechnology platforms have the potential of harboring therapeutics for in vivo delivery in disease treatment. However, the nonspecific interaction between the harbored hydrophobic drugs and cells or other components before reaching the diseased site has been an obstacle in drug delivery. In this work, we report an encapsulation strategy to prevent such nonspecific hydrophobic interactions in vitro and in vivo based on a self-assembled three-dimensional (3D) RNA nanocage. By placing an RNA three-way junction (3WJ) in the cavity of the nanocage, the conjugated hydrophobic molecules were specifically positioned within the nanocage, preventing their exposure to the biological environment. The assembly of the nanocages was characterized by native polyacrylamide gel electrophoresis (PAGE), atomic force microscopy (AFM), and cryogenic electron microscopy (cryo-EM) imaging. The stealth effect of the nanocage for hydrophobic molecules in vitro was evaluated by gel electrophoresis, flow cytometry, and confocal microscopy. The in vivo sheathing effect of the nanocage for hydrophobic molecules was assessed by biodistribution profiling in mice. The RNA nanocages with hydrophobic biomolecules underwent faster clearance in liver and spleen in comparison to their counterparts. Therefore, this encapsulation strategy holds promise for in vivo delivery of hydrophobic drugs for disease treatment.
Modulating precursor nanosheets for stabilized Ni-rich cathode material for Li-ion batteries
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Operando Converting BiOCl into Bi[subscript 2]O[subscript 2](CO[subscript 3])[subscript x]Cly for Ef
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Regulating the properties of activated carbon for supercapacitors: impact of particle size and degree of aromatization of hydrochar
Hydrochar (HC), obtained by the hydrothermal carbonization (HTC) of biomass, is an excellent precursor for preparing activated carbon (AC). However, the effects of the intrinsic properties of HC on the microstructure and electrochemical properties of AC are largely unknown. Here, this study investigates the impact of particle size and the degree of aromatization of in-situ HC on the microstructure and electrochemical properties of AC. Our results show that a large particle size and a high degree of aromatization help protect the HC from overactivation by ZnCl 2 , resulting in an large specific surface area (SSA > 2000 m 2 /g) and high mesopore to micropore volume ratio value ( V mes /V mic > 0.3) of the AC. Electrochemical performance measurements show a maximum specific capacitance of 218 F/g at 0.5 A/g was achieved in all samples where the AC (AC180-10 h) was prepared by activating HC180-10 h with a large size, a high degree of aromatization, and abundant surface oxygen-containing functional groups. After AC180-10 h was assembled into a supercapacitor, the specific capacitance of AC180-10 h still reached 158 F/g at 0.5 A/g, and it showed excellent cycling stability. This study advances the understanding of the impact of HC particle size and degree of aromatization on AC properties, providing new insights into tailoring HC qualities so that improving improve the properties of AC.
Synthesis of Mg–K-biochar bimetallic catalyst and its evaluation of glucose isomerization
Highly efficient isomerization of glucose to fructose is essential for valorizing cellulose fraction of biomass to value-added chemicals. This work provided an innovative method for preparing Mg-biochar and Mg–K-biochar catalysts by impregnating either MgCl 2 alone or in combination with different K compounds (Ding et al. in Bioresour Technol 341:125835, 2021, https://doi.org/10.1016/j.biortech.2021.125835 and KHCO 3 ) on cellulose-derived biochar, followed by hydrothermal carbonization and pyrolysis. Single active substance MgO existing in the 10 Mg–C could give better catalytic effect on glucose isomerization than the synergy of MgO and KCl crystalline material present in 10 Mg–KCl–C. But the catalytic effect of 10 Mg–C was decreased when the basic site of MgO was overloaded. Compared to other carbon-based metal catalysts, 10 Mg–KHCO3–C with 10 wt% MgCl 2 loading had excellent catalytic performance, which gave a higher fructose yield (36.7%) and selectivity (74.54%), and catalyzed excellent glucose conversion (53.99%) at 100 °C in 30 min. Scanning electron microscope–energy dispersive spectrometer and X-Ray diffraction revealed that the distribution of Mg 2+ and K+ in 10 Mg–KHCO 3 –C was uniform and the catalytic active substances (MgO, KCl and K2CO 3 ) were more than 10 Mg–C (only MgO). The synergy effects of MgO and K 2 CO 3 active sites enhanced the pH of reaction system and induced H 2 O ionization to form considerable OH– ions, thus easily realizing a deprotonation of glucose and effectively catalyzing the isomerization of glucose. In this study, we developed a highly efficient Mg–K-biochar bimetallic catalyst for glucose isomerization and provided an efficient method for cellulose valorization.
Understanding and quantifying electron beam effects during in situ TEM nanomechanical tensile testing on metal thin films
Transmission electron microscopy (TEM) imaging relies on high energy electrons for atomic scale resolution, however, the electrons themselves interact with and may alter the material being imaged. Using an in situ TEM MEMS-based nanomechanical testing technique, the effect of the electron beam (e-beam) on the deformation behavior of nanocrystalline Al and ultrafine-grained Au is investigated and quantified. We show that the e-beam enhances plastic deformation, leading to an increase in plastic strain rate and a decrease in true activation volume V* in Al (28 to 21b 3 , with b being the Burgers vector length). The e-beam has a much weaker effect on Au. The e-beam effect is not caused by knock-on damage, but rather an effective temperature increase due to additional atomic fluctuations provided by the e-beam. The effective temperature increase is larger for Al than Au. This e-beam effect does not change the deformation mechanisms, but instead accelerates the stress-driven, thermally activated plastic deformation. These experiments provide insight into the effects of the e-beam on plastic deformation in different metals and underscore the importance of understanding and quantifying these effects for proper interpretation of measured mechanical properties during in situ TEM experiments.
Atomistic modeling of surface and grain boundary dislocation nucleation in FCC metals
Dislocation nucleation plays a critical role in the plastic deformation of crystalline materials. However, it is challenging to predict the active mode and associated rate of dislocation nucleation under typical experimental loading conditions through molecular dynamics simulation due to timescale limitations. In this report we use the free-end nudged elastic band method to determine the activation energies and activation volumes of dislocation nucleation in four typical face-centered cubic metals of Au, Al, Cu and Ni. We focus on the representative processes of surface and grain boundary dislocation nucleation. The atomistically determined activation volumes of these dislocation nucleation processes are larger than 10b3 (with b being the Burgers vector length) under typical experimental loading conditions. These results are compared with experimentally measured activation volumes in ultrafine-grained and nanocrystalline metals, thereby providing mechanistic insight into their rate-controlling deformation mechanisms.
Robust deep learning framework for constitutive relations modeling
Modeling the full-range deformation behaviors of materials under complex loading and materials conditions is a significant challenge for constitutive relations (CRs) modeling. Here, we propose a general encoder-decoder deep learning framework that can model high-dimensional stress-strain data and complex loading histories with robustness and universal capability. The framework employs an encoder to project high-dimensional input information (e.g., loading history, loading conditions, and materials information) to a lower-dimensional hidden space and a decoder to map the hidden representation to the stress of interest. We evaluated various encoder architectures, including gated recurrent unit (GRU), GRU with attention, temporal convolutional network (TCN), and the Transformer encoder, on two complex stress-strain datasets that were designed to include a wide range of complex loading histories and loading conditions. All architectures achieved excellent test results with an root-mean-square error (RMSE) below 1 MPa. Additionally, we analyzed the capability of the different architectures to make predictions on out-of-domain applications, with an uncertainty estimation based on deep ensembles. The proposed approach provides a robust alternative to empirical/semi-empirical models for CRs modeling, offering the potential for more accurate and efficient materials design and optimization.
High-pressure phase transitions in a laser directed energy deposited Fe-33Cu Alloy
Here, additively manufactured Fe-Cu alloys contain both equilibrium face-centered cubic (FCC) and metastable body-centered cubic (BCC) crystal structure Cu precipitates depending on their size. However, the stability of these nanoscale precipitates under extreme conditions such as high pressures has not been reported. This study investigates the phase transformations and microstructural stability of laser directed energy deposition (DED-LB) made Fe67Cu33 alloy (nominal composition in at.%) under high static pressure deformation using in-situ synchrotron X-ray diffraction under pressure, postmortem high-resolution scanning transmission electron microscopy (HR-STEM), and molecular dynamics (MD) simulations. In-situ XRD results reveal a reversible phase transformation from BCC to the hexagonal close-packed (HCP) structure in the Fe grains at an onset pressure of 16.4 GPa, significantly higher than reported in the literature for pure Fe. Although no high-pressure phase transition was observed in the FCC Cu grains through XRD, HR-STEM analysis uncovers a phase transition to the HCP structure in nanoscale metastable BCC Cu precipitates within the BCC Fe matrix. After decompression, the Fe matrix reverted back to the BCC structure with periodic lath martensite, while regions of the nanoscale BCC Cu precipitates retained the metastable HCP structure. MD simulations support the BCC → HCP transition in the embedded nanoscale coherent Cu precipitates, consistent with the classical Burgers mechanism. Thus, by leveraging in-situ XRD observation, postmortem high-resolution S/TEM microscopy, and MD simulations, this study offers profound insights into the distinctive phase transformations induced by high pressure in DED-LB Fe67Cu33 alloy, which is distinguished by its hierarchical microstructure.
Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings
Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure this performance. Some metrics have been applied to simulation results, but most fall short of exploring the complexities in real building applications. There are practical metrics used in individual demand response field studies but they alone cannot fulfil the job of DF benchmarking across a diverse group of buildings. The electrical grid's geographically diverse and changing nature presents challenges to comparing building DF performance measured under different conditions (i.e., benchmarking DF). To address this challenge, a novel DF benchmarking framework focused on load shedding and shifting is presented; the foundation is a set of simple, proven single-event metrics with attributes describing event conditions. These enable benchmarking and visualization in different dimensions for identifying trends that represent how these attributes influence DF. To test its feasibility and scalability, the DF framework was applied to two case studies of 11 office buildings and 121 big-box retail buildings with demand response participation data. Furthermore, these examples provided a pathway for using both building level benchmarking and aggregation to extract insights into building DF about magnitude, consistency, and influential factors. Potential applications of the framework and real-world values have been identified for grid and building stakeholders.
Urbanization effects on the spatial patterns of spring vegetation phenology depend on the climatic background
Cities have been considered ideal surrogates for evaluating ecological responses to climate warming. Although research has revealed that the urban heat island effect is not the only determinant that drives the rural-urban difference in spring phenology, limited attempts further explore the effect of complex interactions between urbanization and climates on the start of the season (SOS). Here, we employed the percentage of impervious surface area as an indicator of urbanization levels, incorporating the urban heat island (UHI) effect and climates to decipher the multiple effects on the temporal shift in SOS. Our results suggest that urbanization, the UHI effect, and climates jointly drive the phenological timing in cities. Further, the SOS is highly linearly correlated with urbanization levels and UHI effects (p<0.001) in the zones with warm and humid climates, whereas relatively warmer, cooler, or arid climates break down the linearity. Geographically, the SOS is north-south symmetrical for the rural-urban ecosystem at the national scale, which initiates at the mid-latitudes (around 30 °N, 67.58 DOY ± 2.23 days) first and then towards the low (around 20 °N, 105.25 DOY ± 1.31 days) and high-latitudes (45 °N, 123.01 DOY ± 1.45 days). Chilling accumulation and spring temperature jointly contribute to this phenomenon. As the UHI effect is similar to the projected global warming in the future, understanding the phenological responses to urbanization in various climates is insightful for evaluating the impact of future warming on plants' phenological behavior in the global ecosystem.
Regulating the surface Pt coordination environment in the PtN overlayers on PtCuN hollow nanospheres for efficient oxygen reduction reaction
Engineering the surface Pt coordination environment is a promising strategy for promoting the kinetically sluggish oxygen reduction reaction (ORR) on Pt-based catalysts. Here, in this study, we achieve the compressive strain effect and electronic effect by Cu and N co-doping to synthesize the PtCuN hollow nanospheres with PtN overlayers (PtCuN@PtN HNSs) using a facile solvothermal synthesis. Electrochemical investigations show that the constructed disordered Pt–N coordination structures effectively facilitate the ORR and stabilize Pt atoms in the compressed lattice, whereas an excessive N-doping can lead to the formation of a structurally unstable Pt nitride phase. Theoretical analyses confirm that the oxygen reduction kinetics on the compressed PtN overlayers are regulated by a synergistic effect resulting from N-doping and lattice compression, circumventing the traditional linear scaling relationships (LSR). The optimized PtCuN@PtN HNSs, with the composition of PtCu 0.29 N 1.1 , demonstrate an area-specific activity of 1.98 mA cm –2 and a mass-specific activity of 1.81 A mg Pt –1 .
Origin of hetero-nuclear Au-Co dual atoms for efficient acidic oxygen reduction
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Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems
Integrated electricity and gas systems are constructed to facilitate the gas-fired generation, and the distributed operation of these integrated systems have received much attention due to the increased emphasis on data security and privacy between different agencies. This paper proposes an extended convex hull based method to address optimal energy flow problems for the integrated electricity and gas systems in a distributed manner. First, a multi-block electricity-gas system model is constructed by dividing the whole system into N blocks considering both physical and regional differences. This multi-block model is then convexified by replacing the nonconvex gas transmission equation with the extended convex hull-based constraints. The Jacobi-Proximal alternating direction method of multipliers algorithm is adopted to solve the convexified model and minimize its operation cost. Finally, the feasibility of the optimal solution for the convexified model is checked, and a sufficient condition is developed. If the sufficient condition is satisfied, the optimal solution for the original nonconvex problem can be recovered from that for the convexified problem. Simulation results demonstrate that the proposed method is tractable and effective in obtaining feasible optimal solutions for multi-block optimal energy flow problems.