Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “functional properties”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cation-size mismatch as a predictive descriptor for structural distortion, configurational disorder, and valence-band splitting in II-IV-N2 semiconductors

The II-IV-N2 class of heterovalent ternary nitrides has gained significant interest as alternatives to the III-nitrides for electronic and optoelectronic applications. In this study, we apply first-principles calculations based on density functional theory to systematically investigate the effects of structural distortions due to cation size mismatch on the configurational disorder of the cation sublattice and the valence band structure in this class of materials. We find that larger size mismatch between the group-II and the group-IV cations results in stronger lattice distortions from the ideal hexagonal ratio, which in turn inhibits the propensity of these materials toward octet-rule violating cation disorder. We also demonstrate that the formation energy of a single cation antisite pair, which is fast and simple to calculate, is a strong indicator of a material's propensity toward disorder. Furthermore, the breaking of in-plane symmetry leads to a splitting of the top three valence bands at Γ, which is also directly related to the magnitude of structural distortions. Our work demonstrates that the structural and functional properties of the II-IV-N2 materials can be finely tuned through controllable structural distortions that stem from the choice of cations.

Kute, Malhar (ORCID:0000000214364564)↗
DOE OSTI2022

X-ray nano-imaging of defects in thin film catalysts via cluster analysis

Functional properties of transition-metal oxides strongly depend on crystallographic defects; crystallographic lattice deviations can affect ionic diffusion and adsorbate binding energies. Scanning x-ray nanodiffraction enables imaging of local structural distortions across an extended spatial region of thin samples. Yet, localized lattice distortions remain challenging to detect and localize using nanodiffraction, due to their weak diffuse scattering. Here, in this study, we apply an unsupervised machine learning clustering algorithm to isolate the low-intensity diffuse scattering in as-grown and alkaline-treated thin epitaxially strained SrIrO 3 films. We pinpoint the defect locations, find additional strain variation in the morphology of electrochemically cycled SrIrO 3 , and interpret the defect type by analyzing the diffraction profile through clustering. Our findings demonstrate the use of a machine learning clustering algorithm for identifying and characterizing hard-to-find crystallographic defects in thin films of electrocatalysts and highlight the potential to study electrochemical reactions at defect sites in operando experiments.

42 ENGINEERING↗
DOE OSTI2025

Polarization rotation in a ferroelectric BaTiO 3 film through low-energy He-implantation

Domain engineering in ferroelectric thin films is crucial for next-generation microelectronic and photonic technologies. Here, a method is demonstrated to precisely control domain configurations in BaTiO 3 thin films through low-energy He ion implantation. The approach transforms a mixed ferroelectric domain state with significant in-plane polarization into a uniform out-of-plane tetragonal phase by selectively modifying the strain state in the film’s top region. This structural transition significantly improves domain homogeneity and reduces polarization imprint, leading to symmetric ferroelectric switching characteristics. The demonstrated ability to manipulate ferroelectric domains post-growth enables tailored functional properties without compromising the coherently strained bottom interface. The method’s compatibility with semiconductor processing and ability to selectively modify specific regions make it particularly promising for practical implementation in integrated devices. This work establishes a versatile approach for strain-mediated domain engineering that could be extended to a wide range of ferroelectric systems, providing new opportunities for memory, sensing, and photonic applications where precise control of polarization states is essential.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strain engineering of the charge and spin-orbital interactions in Sr2IrO4

In the high spin–orbit-coupled Sr 2 IrO 4 , the high sensitivity of the ground state to the details of the local lattice structure shows a large potential for the manipulation of the functional properties by inducing local lattice distortions. We use epitaxial strain to modify the Ir–O bond geometry in Sr 2 IrO 4 and perform momentum-dependent resonant inelastic X-ray scattering (RIXS) at the metal and at the ligand sites to unveil the response of the low-energy elementary excitations. Furthermore, we observe that the pseudospin-wave dispersion for tensile-strained Sr 2 IrO 4 films displays large softening along the [h,0] direction, while along the [h,h] direction it shows hardening. This evolution reveals a renormalization of the magnetic interactions caused by a strain-driven cross-over from anisotropic to isotropic interactions between the magnetic moments. Moreover, we detect dispersive electron–hole pair excitations which shift to lower (higher) energies upon compressive (tensile) strain, manifesting a reduction (increase) in the size of the charge gap. This behavior shows an intimate coupling between charge excitations and lattice distortions in Sr 2 IrO 4 , originating from the modified hopping elements between the t 2g orbitals. Our work highlights the central role played by the lattice degrees of freedom in determining both the pseudospin and charge excitations of Sr 2 IrO 4 and provides valuable information toward the control of the ground state of complex oxides in the presence of high spin–orbit coupling.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Identification of large polarons and exciton polarons in rutile and anatase polymorphs of titanium dioxide

Titanium dioxide (TiO 2 ) is a wide-gap semiconductor with numerous applications in photocatalysis, photovoltaics, and neuromorphic computing. The unique functional properties of this material critically depend on its ability to transport charge in the form of polarons, namely narrow electron wavepackets accompanied by local distortions of the crystal lattice. It is currently well established that the most important polymorphs of TiO 2 , the rutile and anatase phases, harbor small electron polarons and small hole polarons, respectively. However, whether additional polaronic species exist in TiO 2 , and under which conditions, remain open questions. Here, we provide definitive answers to these questions by exploring the rich landscape of polaron quasiparticles in TiO 2 via recently developed ab initio techniques. In addition to the already known small polarons, we identify three species, namely a large hole polaron in rutile, a large quasi-two-dimensional electron polaron in anatase, and a large exciton polaron in anatase. These findings complete the puzzle on the polaron physics of TiO 2 and pave the way for systematically probing and manipulating polarons in a broad class of complex oxides and quantum materials.

Dai, Zhenbang↗
DOE OSTI2022

Nanosynthesis by atmospheric arc discharges excited with pulsed-DC power: a review

Plasma technology is actively used for nanoparticle synthesis and modification. All plasma techniques share the ambition of providing high quality, nanostructured materials with full control over their crystalline state and functional properties. Pulsed-DC physical/chemical vapour deposition, high power impulse magnetron sputtering, and pulsed cathodic arc are consolidated low-temperature plasma processes for the synthesis of high-quality nanocomposite films in vacuum environment. However, atmospheric arc discharge stands out thanks to the high throughput, wide variety, and excellent quality of obtained stand-alone nanomaterials, mainly core–shell nanoparticles, transition metal dichalcogenide monolayers, and carbon-based nanostructures, like graphene and carbon nanotubes. Unique capabilities of this arc technique are due to its flexibility and wide range of plasma parameters achievable by modulation of the frequency, duty cycle, and amplitude of pulse waveform. The many possibilities offered by pulsed arc discharges applied on synthesis of low-dimensional materials are reviewed here. Periodical variations in temperature and density of the pulsing arc plasma enable nanosynthesis with a more rational use of the supplied power. Parameters such as plasma composition, consumed power, process stability, material properties, and economical aspects, are discussed. Lastly a brief outlook towards future tendencies of nanomaterial preparation is proposed. Atmospheric pulsed arcs constitute promising, clean processes providing ecological and sustainable development in the production of nanomaterials both in industry and research laboratories.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Polarization-controlled volatile ferroelectric and capacitive switching in Sn 2 P 2 S 6

Abstract Smart electronic circuits that support neuromorphic computing on the hardware level necessitate materials with memristive, memcapacitive, and neuromorphic- like functional properties; in short, the electronic response must depend on the voltage history, thus enabling learning algorithms. Here we demonstrate volatile ferroelectric switching of Sn 2 P 2 S 6 at room temperature and see that initial polarization orientation strongly determines the properties of polarization switching. In particular, polarization switching hysteresis is strongly imprinted by the original polarization state, shifting the regions of non-linearity toward zero-bias. As a corollary, polarization switching also enables effective capacitive switching, approaching the sought-after regime of memcapacitance. Landau–Ginzburg–Devonshire simulations demonstrate that one mechanism by which polarization can control the shape of the hysteresis loop is the existence of charged domain walls (DWs) decorating the periphery of the repolarization nucleus. These walls oppose the growth of the switched domain and favor back-switching, thus creating a scenario of controlled volatile ferroelectric switching. Although the measurements were carried out with single crystals, prospectively volatile polarization switching can be tuned by tailoring sample thickness, DW mobility and electric fields, paving way to non-linear dielectric properties for smart electronic circuits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multipolar multiferroics in 4⁢𝑑 2 /5⁢𝑑 2 Mott insulators

Here, we extend the concept of conventional multiferroicity—where ferroelectric and ferromagnetic orders coexist—to include multipolar degrees of freedom. Specifically, we explore how this phenomenon emerges in 4⁢𝑑 2 /5⁢𝑑 2 Mott insulators with strong spin-orbit and Hund's couplings. Our study uncovers the origin of magnetic multipolar interactions in these systems and demonstrates that a combination of quadrupolar and octupolar magnetic order can simultaneously induce both electrical quadrupolar moments and ferroelectric polarization. By expanding the multiferroic framework to higher-order multipoles, we reveal the possibility of coexisting multipolar orders of different or same ranks, paving the way for different functional properties in a large class of strongly correlated materials.

Mott insulators↗
DOE OSTI2022

Learning Grain-Boundary Segregation: From First Principles to Polycrystals

The segregation of solute atoms at grain boundaries (GBs) can strongly impact the structural and functional properties of polycrystals. Yet, due to the limited availability of simulation tools to study polycrystals at the atomistic scale (i.e., interatomic potentials), there is a minimal understanding of the variation of solute segregation tendencies across the very complex space of GB microenvironments and the large range of alloys in which it can occur. Here, we develop an algorithmic framework that can directly learn the full spectrum of segregation energies for a metal solute atom in a metal polycrystal from ab initio methods, bypassing the need for alloy interatomic potentials. This framework offers a pathway to a comprehensive catalog of GB solute segregation with quantum accuracy, for the entire alloy space. As an initial demonstration in this pursuit, we build an extensive GB segregation database for aluminum-based alloys across the periodic table, including dozens of alloys for which there are substantially no prior data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Low-dimensional metal–organic frameworks: a pathway to design, explore and tune magnetic structures

Here, the magnetic structure adopted by a material relies on symmetry, the hierarchy of exchange interactions between magnetic ions and local anisotropy. A direct pathway to control the magnetic interactions is to enforce dimensionality within the material, from zero-dimensional isolated magnetic ions, one-dimensional (1D) spin-chains, two-dimensional (2D) layers to three-dimensional (3D) order. Being able to design a material with a specific dimensionality for the phenomena of interest is non-trivial. While many advances have been made in the area of inorganic magnetic materials, organic compounds offer distinct and potentially more fertile ground for material design. In particular magnetic metal–organic frameworks (mMOFs) combine magnetism with non-magnetic property functionality on the organic linkers within the structural framework, which can further be tuned with mild perturbations of pressure and field to induce phase transitions. Here, it is examined how neutron scattering measurements on mMOFs can be used to directly determine the magnetic structure when the magnetic ions are in a 2D layered environment within the wider 3D crystalline framework. The hydrated formate, in deuterated form, Co(DCOO) 2 ·2D 2 O, which was one of the first magnetic MOFs to be investigated with neutron diffraction, is reinvestigated as an exemplar case.

magnetism↗
DOE OSTI2024

Melt Pool characteristics on surface roughness and printability of 316L stainless steel in laser powder bed fusion

Purpose Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel. Design/methodology/approach A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy. Findings The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm 3 ) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation. Originality/value This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Engineering↗
DOE OSTI2024

AI for Materials Design and Discovery Using Atomistic Scale Information [Industrial and Governmental Activities]

The design and discovery of materials with desired functional properties is pivotal to the scientific mission of the United States Department of Energy (US-DOE) [1], which includes within its portfolio several important applications for the national economy and security. Importantly, these applications range from: renewable energy (e.g., solar cells, organic photovoltaics, and organic light-emitting diodes), energy storage (e.g., batteries and supercapacitors), and carbon capture and sequestration, to synthesis of manufacturing of new materials (e.g., drugs, or materials with desired conductivity, thermal stability, and catalytic activity), and nuclear energy (e.g., highly performant nuclear fuels and materials with improved nuclear shielding properties).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Toward sustainable production of value‐added bioenergy and industrial oils in oilseed and biomass feedstocks

Abstract Plant fatty acids are used for food, feed, fuel, and industrial materials. Structurally and chemically diverse fatty acids, referred to as unusual or specialized fatty acids, are found in the seed oils of diverse plant species. Many unusual fatty acids have potential use as alternative and renewable sources of biofuels and bio‐based industrial feedstocks due to their variant structures' physical or functional properties. Oils enriched in these fatty acids can increase the value of oilseed crops and provide co‐products that can be readily extracted from lignocellulosic materials in biomass crops. Here, we describe recent progress in strategies for enhancement of oil production and quality in oilseed crops and the extension of this knowledge for metabolic engineering of biomass crops. Successful implementation of these strategies, in part, through the use of emerging synthetic biology tools, will provide added product value for the economic sustainability of biomass crops as bioenergy feedstocks.

Park, Kiyoul↗
DOE OSTI2022

Functional Traits Resolve Mechanisms Governing the Assembly and Distribution of Nitrogen-Cycling Microbial Communities in the Global Ocean

Microorganisms drive much of the marine nitrogen (N) cycle, which jointly controls the primary production in the global ocean. However, our understanding of the microbial communities driving the global ocean N cycle remains fragmented. Focusing on “who is doing what, where, and how?”, this study draws a clear picture describing the global biogeography of marine N-cycling microbial communities by utilizing the Tara Oceans shotgun metagenomes. The marine N-cycling communities are highly variable taxonomically but relatively even at the functional trait level, showing clear functional redundancy properties. The functional traits and taxonomic groups are shaped by the same set of geo-environmental factors, among which, depth is the major factor impacting marine N-cycling communities, differentiating mesopelagic from epipelagic communities. Latitudinal diversity gradients and distance-decay relationships are observed for taxonomic groups, but rarely or weakly for functional traits. The composition of functional traits is strongly deterministic as revealed by null model analysis, while a higher degree of stochasticity is observed for taxonomic composition. Integrating multiple lines of evidence, in addition to drawing a biogeographic picture of marine N-cycling communities, this study also demonstrated an essential microbial ecological theory—determinism governs the assembly of microbial communities performing essential biogeochemical processes; the environment selects functional traits rather than taxonomic groups; functional redundancy underlies stochastic taxonomic community assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning

This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.

Biagioni, David↗
DOE OSTI2025

ProteinTuneRL

ProteinTuneRL is a framework designed to harness the power of reinforcement learning for advanced protein design. The project enables fine-tuning of generative models to explore and optimize protein sequences with tailored structural and functional properties.

Landajuela Larma, Mikel [Lawrence Livermore Nation↗
DOE OSTI2021

Protocols for isolating and characterizing polysaccharides from plant cell walls: a case study using rhamnogalacturonan-II

Abstract Background In plants, a large diversity of polysaccharides comprise the cell wall. Each major type of plant cell wall polysaccharide, including cellulose, hemicellulose, and pectin, has distinct structures and functions that contribute to wall mechanics and influence plant morphogenesis. In recent years, pectin valorization has attracted much attention due to its expanding roles in biomass deconstruction, food and material science, and environmental remediation. However, pectin utilization has been limited by our incomplete knowledge of its structure. Herein, we present a workflow of principles relevant for the characterization of polysaccharide primary structure using nature’s most complex polysaccharide, rhamnogalacturonan-II (RG-II), as a model. Results We outline how to isolate RG-II from celery and duckweed cell walls and from red wine using chemical or enzymatic treatments coupled with size-exclusion chromatography. From there, we applied mass spectrometry (MS)-based techniques to determine the glycosyl residue and linkage compositions of the intact RG-II and derived oligosaccharides including special considerations for labile monosaccharides. In doing so, we demonstrated that in the duckweed Wolffiella repanda the arabinopyranosyl (Ara p ) residue of side chain B is substituted at O- 2 with rhamnose. We used electrospray-MS techniques to identify non-glycosyl modifications including methyl-ethers, methyl-esters, and acetyl-esters on RG-II-derived oligosaccharides. We then showed the utility of proton nuclear magnetic resonance spectroscopy ( 1 H-NMR) to investigate the structure of intact RG-II and to complement the RG-II dimerization studies performed using size-exclusion chromatography. Conclusions The complexity of pectic polysaccharide structures has hampered efforts aimed at their valorization. In this work, we used RG-II as a model to demonstrate the steps necessary to isolate and characterize polysaccharides using chromatographic, MS, and NMR techniques. The principles can be applied to the characterization of other saccharide structures and will help inform researchers on how saccharide structure relates to functional properties in the future.

09 BIOMASS FUELS↗
DOE OSTI2020

Raman-based sorting of microbial cells to link functions to their genes

In our recent work, we developed an optofluidic platform that allows a direct link to be made between the phenotypes (functions) and the genotypes (genes) of microbial cells within natural communities. By combining stable isotope probing, optical tweezers, Raman microspectroscopy, and microfluidics, the platform performs automated Raman-based sorting of taxa from within a complex community in terms of their functional properties. In comparison with manual sorting approaches, our method provides high throughput (up to 500 cells per hour) and very high sorting accuracy (98.3 ± 1.7%), and significantly reduces the human labour required. The system provides an efficient manner to untangle the contributions of individual members within environmental and host-associated microbiomes. In this News and Thoughts, we provide an overview of our platform, describe potential applications, suggest ways in which the system could be improved, and discuss future directions in which Raman-based analysis of microbial populations might be developed.

59 BASIC BIOLOGICAL SCIENCES↗