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NASA NTRS2004

Impactites of the Yaxcopoil-1 drilling site, Chicxulub impact structure: Petrography, geochemistry, and depositional environment

The impact breccias encountered in drill hole Yaxcopoil-1 (Yax-1) in the Chicxulub impact structure have been subdivided into six units. The two uppermost units are redeposited suevite and suevite, and together are only 28 m thick. The two units below are interpreted as a ground surge deposit similar to a pyroclastic flow in a volcanic regime with a fine-grained top (unit 3; 23 m thick; nuee ardente) and a coarse breccia (unit 4; approx.15 m thick) below. As such, they consist of a melange of clastic matrix breccia and melt breccia. The pyroclastic ground surge deposit and the two units 5 and 6 below are related to the ejecta curtain. Unit 5 (approx.24 m thick) is a silicate impact melt breccia, whereas unit 6 (10 m thick) is largely a carbonate melt breccia with some clastic-matrix components. Unit 5 and 6 reflect an overturning of the target stratigraphy. The suevites of units 1 and 2 were deposited after emplacement of the ejecta curtain debris. Reaction of the super-heated breccias with seawater led to explosive activity similar to phreomagmatic steam explosion in volcanic regimes. This activity caused further brecciation of melt and melt fragments. The fallback suevite deposit of units 1 and 2 is much thinner than suevite deposits at larger distances from the center of the impact structure than the 60 km of the Yax-1 drill site. This is evidence that the fallback suevite deposit (units 1 and 2) originally was much thicker. Unit 1 exhibits sedimentological features suggestive of suevite redeposition. Erosion possibly has occurred right after the IUT impact due to seawater backsurge, but erosion processes spanning thousands of years may also have been active. Therefore, the top of the 100 m thick impactite sequence at Yaxcopoil, in our opinion, is not the K/T boundary.

Dressler, Burkhard O.↗

NASA NTRS1999

Keck II Mid-Infrared Imaging of the Young Stellar Object WL16

WL16 is unique among the members of the young, forming star cluster embedded in the nearby p Oph cloud core in exhibiting an extended, high surface brightness disk in the emission features originating from solid-state aromatic hydrocarbons.

Circumstellar matter dust disk mid-infrared very s↗

NASA NTRS2013

Building a 2.5D Digital Elevation Model from 2D Imagery

When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.

Padgett, Curtis W.↗

DOE OSTI2015

Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling

The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

A novel triple power cycle featuring a gas turbine cycle with supercritical carbon dioxide and organic Rankine cycles: Thermoeconomic analysis and optimization

In this study, a novel triple power cycle is proposed where waste heat from a gas turbine cycle is utilized to drive a supercritical carbon dioxide (s-CO 2 ) recompression cycle and a recuperative organic Rankine cycle (ORC) in sequence. A detailed thermoeconomic model is developed and implemented in MATLAB to evaluate the performance of the proposed cycle under different operating conditions. Optimization using a particle swarm optimization (PSO) algorithm is performed to minimize the levelized cost of electricity (LCOE) and determine the optimum design conditions of the cycle. The optimization results show that for a 100 MW cycle, the overall thermal efficiency and LCOE are 0.521 and $\$52.819$/MWh, respectively. The turbine inlet temperature of the gas turbine and s-CO 2 cycles are found as the most influential parameters on the thermoeconomic performance of the triple cycle. The proposed triple cycle shows an excellent waste energy recovery potential and superiority over a very thermodynamically efficient cycle from the literature, which included a gas turbine topping cycle and a complex cascade s-CO 2 power cycle used a bottoming cycle. As a result, the proposed triple cycle shows up to 0.9% points higher efficiency while it has fewer heat exchangers and turbomachinery than the cycle from the literature.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2018

Type III-A CRISPR-Cas Csm Complexes: Assembly, Periodic RNA Cleavage, DNase Activity Regulation, and Autoimmunity

Type ΙΙΙ CRISPR-Cas systems provide robust immunity against foreign RNA and DNA by sequence-specific RNase and target RNA-activated sequence-nonspecific DNase and RNase activities. We report on cryo-EM structures of Thermococcus onnurineus Csm crRNA binary, Csm crRNA -target RNA and Csm crRNA -target RNA anti-tag ternary complexes in the 3.1 Å range. The topological features of the crRNA 5'-repeat tag explains the 5'-ruler mechanism for defining target cleavage sites, with accessibility of positions -2 to -5 within the 5'-repeat serving as sensors for avoidance of autoimmunity. The Csm3 thumb elements introduce periodic kinks in the crRNA-target RNA duplex, facilitating cleavage of the target RNA with 6-nt periodicity. Key Glu residues within a Csm1 loop segment of Csm crRNA adopt a proposed autoinhibitory conformation suggestive of DNase activity regulation. Finally, these structural findings, complemented by mutational studies of key intermolecular contacts, provide insights into Csm crRNA complex assembly, mechanisms underlying RNA targeting and site-specific periodic cleavage, regulation of DNase cleavage activity, and autoimmunity suppression.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Meta2DB: Curated Shotgun Metagenomic Feature Sets and Metadata for Health State Prediction

Meta2DB is a curated metagenomic and metadata database that provides structurally consistent microbiome taxonomy feature count tables for 13 897 samples across 84 studies, 23 disease states, and 34 geographical locations. All samples were uniformly processed using a streamlined metagenomic classification pipeline that employs a unique and comprehensive reference database indexed to contain all sequences across all kingdoms of life that were present in the NCBI Nucleotide (nt) database retrieved on 4 January 2023. This pipeline leverages high-performance computing (HPC) resources at Lawrence Livermore National Laboratory and was used to process 50TB of publicly available raw metagenomic sequence data. Extensive metadata curation was carried out through a combination of manual curation and automated parsing, producing a consistent inter-study metadata table specifically structured to facilitate training of ML models for prediction of human health.

Kok, C [Lawrence Livermore National Laboratory (LL↗

DOE OSTI2021

Ubiquity of amplitude-modulated magnetic ordering in the H - T phase diagram of the frustrated non-Fermi-liquid YbAgGe

YbAgGe contains a magnetic geometrically frustrated kagome-like lattice that also features significant local single-ion anisotropy. The electronic state is established by hybridization of 4f and conduction electrons leading to heavy electronic masses. The competition between these various interactions leads to nontrivial behavior under external magnetic field, including a sequence of magnetic phase transitions, non-Fermi-liquid states, and possibly a quantum critical point. We present a series of neutron diffraction experiments performed in the mK temperature range and under magnetic fields up to 8 T in the hexagonal plane, revealing the microscopic nature of the first four subsequent magnetic states of this phase diagram. The magnetic phases are associated with the propagation vectors K 1 =($\frac{1}{3}$ 0 $\frac{1}{3}$) for H < 2 T, K 2 = (0 0 0.32) for 2 T < H < 3 T, K 1 = ($\frac{1}{3}$ 0 $\frac{1}{3}$) for 3 T < H < 4.5 T and k 3 = (0.195 0.195 0.38) for 4.5 T < H < 7 T. Our structural refinements reveal a strong modulation of the magnetic moment amplitude in all phases. We observe that the ordered moments of the three magnetically different Yb sites become increasingly different in field, which complies with the principle local anisotropy directions relative to the field direction. While the ordered moments are aligned predominantly in the hexagonal plane, we also find a significant out-of-plane component and a ferromagnetic contribution above 2 T. Here we discuss possible scenarios that may evolve around the phase boundary at 4.5 T, which is associated with putative quantum criticality as identified by various bulk probes. We propose further steps that are required to better understand the microscopic interactions in this material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

The landscape of Chlamydomonas histone H3 lysine 4 methylation reveals both constant features and dynamic changes during the diurnal cycle

Chromatin modifications are epigenetic regulatory features with major roles in various cellular events, yet they remain understudied in algae. Here, we interrogated the genome-wide distribution pattern of mono- and trimethylated histone H3 lysine 4 (H3K4) using chromatin-immunoprecipitation followed by deep-sequencing (ChIP-seq) during key phases of the Chlamydomonas cell cycle: early G 1 phase, Zeitgeber Time 1 (ZT1), when cells initiate biomass accumulation, S/M phase (ZT13) when cells are replicating DNA and undergoing mitosis, and late G 0 phase (ZT23) when they are quiescent. Tri-methylated H3K4 was predominantly enriched at transcription start sites of the majority of protein coding genes (85%). The likelihood of a gene being marked by H3K4me3 correlated with it being transcribed at some point during the life cycle but not necessarily by continuous active transcription, as exemplified by early zygotic genes, which may remain transcriptionally dormant for thousands of generations between sexual cycles. The exceptions to this rule were around 120 loci, some of which encode non-poly-adenylated transcripts, such as small nuclear RNAs and replication-dependent histones that had H3K4me3 peaks only when they were being transcribed. Mono-methylated H3K4 was the default state for the vast majority of histones that were bound outside of transcription start sites and terminator regions of genes. A small fraction of the genome that was depleted of any H3 lysine 4 methylation was enriched for DNA cytosine methylation and the genes within these DNA methylation islands were poorly expressed. Besides marking protein coding genes, H3K4me3 ChIP-seq data served also as a annotation tool for validation of hundreds of long non-coding RNA genes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Managing genomic variant calling workflows with Swift/T

Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures.

Science & Technology - Other Topics↗

DOE OSTI2022

One fold, many functions—M23 family of peptidoglycan hydrolases

Bacterial cell walls are the guards of cell integrity. They are composed of peptidoglycan that provides rigidity to sustain internal turgor and ensures isolation from the external environment. In addition, they harbor the enzymatic machinery to secure cell wall modulations needed throughout the bacterial lifespan. The main players in this process are peptidoglycan hydrolases, a large group of enzymes with diverse specificities and different mechanisms of action. They are commonly, but not exclusively, found in prokaryotes. Although in most cases, these enzymes share the same molecular function, namely peptidoglycan hydrolysis, they are leveraged to perform a variety of physiological roles. A well-investigated family of peptidoglycan hydrolases is M23 peptidases, which display a very conserved fold, but their spectrum of lytic action is broad and includes both Gram- positive and Gram- negative bacteria. In this review, we summarize the structural, biochemical, and functional studies concerning the M23 family of peptidases based on literature and complement this knowledge by performing large-scale analyses of available protein sequences. This review has led us to gain new insight into the role of surface charge in the activity of this group of enzymes. We present relevant conclusions drawn from the analysis of available structures and indicate the main structural features that play a crucial role in specificity determination and mechanisms of latency. Our work systematizes the knowledge of the M23 family enzymes in the context of their unique antimicrobial potential against drug-resistant pathogens and presents possibilities to modulate and engineer their features to develop perfect antibacterial weapons.

Razew, Alicja↗

NASA NTRS1975

The automated multi-stage substructuring system for NASTRAN

The substructuring capability developed for eventual installation in Level 16 is now operational in a test version of NASTRAN. Its features are summarized. These include the user-oriented, Case Control type control language, the automated multi-stage matrix processing, the independent direct access data storage facilities, and the static and normal modes solution capabilities. A complete problem analysis sequence is presented with card-by-card description of the user input.

Field, E. I.↗

NASA NTRS1975

Accretion and the nova outburst

Evolutionary sequences of thermonuclear runaways in the hydrogen-rich envelopes of carbon-oxygen white dwarfs are presented which include the effects of accretion of infalling material, allow the initial envelope to be out of equilibrium, and reproduce the gross features of the nova outburst. The models show that massive infall rates produce strong shocks at the stellar surface, that material passing through the shocks reaches nuclear-ignition temperatures, and that the thermonuclear runaway proceeds with an extended envelope around the star in the most extreme cases. The major effect of accretion is found to be a reduction in the amount of material ejected for a given degree of CNO enhancement as compared with previous nonaccretion models. It is also found that all the heating that causes ejection occurs in the deeper layers and that the light curves produced by the present models are in closer agreement with observed nova light curves that the previous models.

Starrfield, S. G.↗

NASA NTRS2004

Turbulent Jet Flames Into a Vitiated Coflow

Examined is the vitiated coflow flame, an experimental condition that decouples the combustion processes of flows found in practical combustors from the associated recirculating fluid mechanics. The configuration consists of a 4.57 mm diameter fuel jet into a coaxial flow of hot combustion products from a lean premixed flame. The 210 mm diameter coflow isolates the jet flame from the cool ambient, providing a hot environment similar to the operating conditions of advanced combustors; this important high temperature element is lacking in the traditional laboratory experiments of jet flames into cool (room) air. A family of flows of increasing complexity is presented: 1) nonreacting flow, 2) all hydrogen flame (fuel jet and premixed coflow), and 3) set of methane flames. This sequence of experiments provides a convenient ordering of validation data for combustion models. Laser Raman-Rayleigh-LIF diagnostics at the Turbulent Diffusion Flame laboratory of Sandia National Laboratories produced instantaneous multiscalar point measurements. These results attest to the attractive features of the vitiated coflow burner and the well-defined boundary conditions provided by the coflow. The coflow is uniform and steady, isolating the jet flame from the laboratory air for a downstream distance ranging from z/d = 50-70. The statistical results show that differential diffusion effects in this highly turbulent flow are negligible. Complementing the comprehensive set of multiscalar measurements is a parametric study of lifted methane flames that was conducted to analyze flame sensitivity to jet and coflow velocity, as well as coflow temperature. The linear relationship found between the lift-off height and the jet velocity is consistent with previous experiments. New linear sensitivities were found correlating the lift-off height to coflow velocity and temperature. A blow-off study revealed that the methane flame blows off at a common coflow temperature (1260 K), regardless of coflow or jet velocity. An explanation for this phenomenon is that entrainment of ambient air at the high lift-off heights prevents autoignition. Analysis of the results suggests that flame stabilization occurs through a combination of flame propagation, autoignition, and localized extinction processes. Proposed is an expanded view of distributed reaction combustion based on analysis of the distributions of probe volume conditions at the stabilization region of the lifted hydrogen and methane flames. Turbulent eddies the size of the flame thickness mix fuel and hot coflow across the flame front, thereby enhancing the reaction zone with autoignition of reactants at elevated temperatures; this is the reverse effect of turbulent flames in ambient air, where intense turbulence in cool mixtures result in localized extinction. Each of the three processes (i.e., flame propagation, autoignition and localized extinction) contributes to flame stabilization in varying degrees, depending on flow conditions.

Holdeman, James D.↗

NASA NTRS2013

Computational Modeling of Cephalad Fluid Shift for Application to Microgravity-Induced Visual Impairment

An improved understanding of spaceflight-induced ocular pathology, including the loss of visual acuity, globe flattening, optic disk edema and distension of the optic nerve and optic nerve sheath, is of keen interest to space medicine. Cephalad fluid shift causes a profoundly altered distribution of fluid within the compartments of the head and body, and may indirectly generate phenomena that are biomechanically relevant to visual function, such as choroidal engorgement, compromised drainage of blood and cerebrospinal fluid (CSF), and altered translaminar pressure gradient posterior to the eye. The experimental body of evidence with respect to the consequences of fluid shift has not yet been able to provide a definitive picture of the sequence of events. On earth, elevated intracranial pressure (ICP) is associated with idiopathic intracranial hypertension (IIH), which can produce ocular pathologies that look similar to those seen in some astronauts returning from long-duration flight. However, the clinically observable features of the Visual Impairment and Intracranial Pressure (VIIP) syndrome in space and IIH on earth are not entirely consistent. Moreover, there are at present no experimental measurements of ICP in microgravity. By its very nature, physiological measurements in spaceflight are sparse, and the space environment does not lend itself to well-controlled experiments. In the absence of such data, numerical modeling can play a role in the investigation of biomechanical causal pathways that are suspected of involvement in VIIP. In this work, we describe the conceptual framework for modeling the altered compartmental fluid distribution that represents an equilibrium fluid distribution resulting from the loss of hydrostatic pressure gradient.

Nelson, Emily S.↗

NASA NTRS2016

ISS Double-Gimbaled CMG Subsystem Simulation Using the Agile Development Method

This paper presents an evolutionary approach in simulating a cluster of 4 Control Moment Gyros (CMG) on the International Space Station (ISS) using a common sense approach (the agile development method) for concurrent mathematical modeling and simulation of the CMG subsystem. This simulation is part of Training systems for the 21st Century simulator which will provide training for crew members, instructors, and flight controllers. The basic idea of how the CMGs on the space station are used for its non-propulsive attitude control is briefly explained to set up the context for simulating a CMG subsystem. Next different reference frames and the detailed equations of motion (EOM) for multiple double-gimbal variable-speed control moment gyroscopes (DGVs) are presented. Fixing some of the terms in the EOM becomes the special case EOM for ISS's double-gimbaled fixed speed CMGs. CMG simulation development using the agile development method is presented in which customer's requirements and solutions evolve through iterative analysis, design, coding, unit testing and acceptance testing. At the end of the iteration a set of features implemented in that iteration are demonstrated to the flight controllers thus creating a short feedback loop and helping in creating adaptive development cycles. The unified modeling language (UML) tool is used in illustrating the user stories, class designs and sequence diagrams. This incremental development approach of mathematical modeling and simulating the CMG subsystem involved the development team and the customer early on, thus improving the quality of the working CMG system in each iteration and helping the team to accurately predict the cost, schedule and delivery of the software.

Inampudi, Ravi↗

DOE OSTI2021

Precipitation Hardening in Ferroelectric Ceramics

Domain wall motion in ferroics, similar to dislocation motion in metals, can be tuned by well-concepted microstructural elements. In demanding high-power applications of piezoelectric materials, the domain wall motion is considered as a lossy hysteretic mechanism that should be restricted. Current applications for so-called hard piezoelectrics are abundant and hinge on the use of an acceptor-doping scheme. However, this mechanism features severe limitations due to enhanced mobility of oxygen vacancies at moderate temperatures. By analogy with metal technology, the authors present here a new solution for electroceramics, where precipitates are utilized to pin domain walls and improve piezoelectric properties. Through a sequence of sintering, nucleation, and precipitate growth, intragranular precipitates leading to a fine domain structure are developed as shown by transmission electron microscopy, piezoresponse force microscopy, and phase-field simulation. This structure impedes the domain wall motion as elucidated by electromechanical characterization. As a result, the mechanical quality factor is increased by ≈50% and the hysteresis in electrostrain is suppressed considerably. This is even achieved with slightly increased piezoelectric coefficient and electromechanical coupling factor. This novel process can be smoothly implemented in industrial production processes and is accessible to simple laboratory experimentation for microstructure optimization and implementation in various ferroelectric systems.

36 MATERIALS SCIENCE↗