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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

MechElastic: A Python library for analysis of mechanical and elastic properties of bulk and 2D materials

We report the MechElastic Python package evaluates the mechanical and elastic properties of bulk and 2D materials using the elastic coefficient matrix ( C ij ) obtained from any ab-initio density-functional theory (DFT) code. The current version of this package reads the output of VASP, ABINIT, and Quantum Espresso codes (but it can be easily generalized to any other DFT code) and performs the appropriate post-processing of elastic constants as per the requirement of the user. This program can also detect the input structure's crystal symmetry and test the mechanical stability of all crystal classes using the Born-Huang criteria. Various useful material-specific properties such as elastic moduli, longitudinal and transverse elastic wave velocities, Debye temperature, elastic anisotropy, 2D layer modulus, hardness, Pugh's ratio, Cauchy's pressure, Kleinman's parameter, and Lame's coefficients, can be estimated using this program. Another existing feature of this program is to employ the ELATE package (2016) [29] and plot the spatial variation of several elastic properties such as Poisson's ratio, linear compressibility, shear modulus, and Young's modulus in three dimensions. Further, the MechElastic package can plot the equation of state (EOS) curves for energy and pressure for a variety of EOS models such as Murnaghan, Birch, Birch-Murnaghan, and Vinet, by reading the inputted energy/pressure versus volume data obtained via numerical calculations or experiments. This package is particularly useful for the high-throughput analysis of elastic and mechanical properties of materials.

2D materials↗
DOE OSTI2024

Anaerobic fungi contain abundant, diverse, and transcriptionally active Long Terminal Repeat retrotransposons

Long Terminal Repeat (LTR) retrotransposons are a class of repetitive elements that are widespread in the genomes of plants and many fungi. LTR retrotransposons have been associated with rapidly evolving gene clusters in plants and virulence factor transfer in fungal-plant parasite-host interactions. We report here the abundance and transcriptional activity of LTR retrotransposons across several species of the early-branching Neocallimastigomycota, otherwise known as the anaerobic gut fungi (AGF). The ubiquity of LTR retrotransposons in these genomes suggests key evolutionary roles in these rumen-dwelling biomass degraders, whose genomes also contain many enzymes that are horizontally transferred from other rumen-dwelling prokaryotes. Up to 10% of anaerobic fungal genomes consist of LTR retrotransposons, and the mapping of sequences from LTR retrotransposons to transcriptomes shows that the majority of clusters are transcribed, with some exhibiting expression greater than 104 reads per kilobase million mapped reads (rpkm). Many LTR retrotransposons are strongly differentially expressed upon heat stress during fungal cultivation, with several exhibiting a nearly three-log10 fold increase in expression, whereas growth substrate variation modulated transcription to a lesser extent. We show that some LTR retrotransposons contain carbohydrate-active enzymes (CAZymes), and the expansion of CAZymes within genomes and among anaerobic fungal species may be linked to retrotransposon activity. We further discuss how these widespread sequences may be a source of promoters and other parts towards the bioengineering of anaerobic fungi.

Genetics & Heredity↗
DOE OSTI2020

Implementation and verification of PyNE R2S with DAG-OpenMC

The mesh-based Rigorous-Two-Step (R2S) method has been widely used in the accurate estimation of the shutdown dose rate (SDR) of fusion systems. Several mesh-based R2S code has been implemented based on Monte Carlo particle transport code MCNP5 or DAG-MCNP5 and inventory calculation code such as FISPACT-II, ALARA or ACAB. Recently, the OpenMC, a community-developed Monte Carlo particle transport code, implemented the photon particle transport capability, which enables OpenMC to be used in R2S. In this paper, PyNE R2S is extended with the support of DAG-OpenMC, i.e., OpenMC with DAGMC. Modifications that allow PyNE to read the flux result in the state point file of OpenMC has been implemented to PyNE R2S workflow. A custom source routine of OpenMC that reads the photon source file from PyNE R2S and sampling photon particle in OpenMC photon transport has been implemented in OpenMC. With these modifications, PyNE R2S is now capable of performing R2S calculations with both DAG-MCNP5 and DAG-OpenMC. The ITER FNG dose rate benchmark problem has been used to validate the code. The FNG neutron source has been modified for neutron transport with DAG-OpenMC. The shutdown dose rate of 19 cooling times has been calculated and compared with the experimental data and the computational results of other R2S codes. The results of PyNE R2S with DAG-OpenMC show satisfactory agreement with the experimental data and other computational results. Therefore, we consider PyNE R2S with DAG-OpenMC is a reliable code to calculate the SDR of fusion systems.

fusion↗
DOE OSTI2014

Effect of Cerebellum Radiation Dosimetry on Cognitive Outcomes in Children With Infratentorial Ependymoma

Purpose: Cognitive decline is a recognized effect of radiation therapy (RT) in children treated for brain tumors. The importance of the cerebellum and its contribution to cognition have been recognized; however, the effect of RT on cerebellum-linked neurocognitive deficits has yet to be explored. Methods and Materials: Seventy-six children (39 males) at a median 3.3 years of age (range, 1-17 years old) were irradiated for infratentorial ependymoma from 1997 to 2008. The total prescribed dose was 54 to 59.4 Gy administered to the postoperative tumor bed with 5- or 10-mm clinical target volume margin. Age-appropriate cognitive and academic testing was performed prior to the start of RT and was then repeated at 6 months and annually throughout 5 years. The anterior and posterior cerebellum and other normal brain volumes were contoured on postcontrast, T1-weighted postoperative magnetic resonance images registered to treatment planning computed tomography images. Mean doses were calculated and used with time after RT and other clinical covariates to model their effect on neurocognitive test scores. Results: Considering only the statistically significant rates in longitudinal changes for test scores and models that included mean dose, there was a correlation between mean infratentorial dose and intelligence quotient (IQ; −0.190 patients/Gy/year; P=.001), math (−0.164 patients/Gy/year; P=.010), reading (−0.137 patients/Gy/year; P=.011), and spelling scores (−0.147 patients/Gy/year; P=.012), where Gy was measured as the difference between the mean dose received by an individual patient and the mean dose received by the patient group. There was a correlation between mean anterior cerebellum dose and IQ scores (−0.116 patients/Gy/year; P=.042) and mean posterior cerebellum dose and IQ (−0.150 patients/Gy/year; P=.002), math (−0.120 patients/Gy/year; P=.023), reading (−0.111 patients/Gy/year; P=.012), and spelling (−0.117 patients/Gy/year; P=.015) scores. Conclusions: Sparing portions of the cerebellum should be considered in RT planning for children with infratentorial ependymoma because of the potential impact of radiation dose on cognitive function.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

A Simple and Efficient Methodology To Improve Geometric Accuracy in Gamma Knife Radiation Surgery: Implementation in Multiple Brain Metastases

Purpose: To propose, verify, and implement a simple and efficient methodology for the improvement of total geometric accuracy in multiple brain metastases gamma knife (GK) radiation surgery. Methods and Materials: The proposed methodology exploits the directional dependence of magnetic resonance imaging (MRI)-related spatial distortions stemming from background field inhomogeneities, also known as sequence-dependent distortions, with respect to the read-gradient polarity during MRI acquisition. First, an extra MRI pulse sequence is acquired with the same imaging parameters as those used for routine patient imaging, aside from a reversal in the read-gradient polarity. Then, “average” image data are compounded from data acquired from the 2 MRI sequences and are used for treatment planning purposes. The method was applied and verified in a polymer gel phantom irradiated with multiple shots in an extended region of the GK stereotactic space. Its clinical impact in dose delivery accuracy was assessed in 15 patients with a total of 96 relatively small (<2 cm) metastases treated with GK radiation surgery. Results: Phantom study results showed that use of average MR images eliminates the effect of sequence-dependent distortions, leading to a total spatial uncertainty of less than 0.3 mm, attributed mainly to gradient nonlinearities. In brain metastases patients, non-eliminated sequence-dependent distortions lead to target localization uncertainties of up to 1.3 mm (mean: 0.51 ± 0.37 mm) with respect to the corresponding target locations in the “average” MRI series. Due to these uncertainties, a considerable underdosage (5%-32% of the prescription dose) was found in 33% of the studied targets. Conclusions: The proposed methodology is simple and straightforward in its implementation. Regarding multiple brain metastases applications, the suggested approach may substantially improve total GK dose delivery accuracy in smaller, outlying targets.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Comparative Studies of Optoelectrical Properties of Prominent PV Materials: Halide Perovskite, CdTe, and GaAs

We compare three representative high performance PV materials: halide perovskite MAPbI3, CdTe, and GaAs, in terms of photoluminescence (PL) efficiency, PL lineshape, carrier diffusion, and surface recombination and passivation, over multiple orders of photo-excitation density or carrier density appropriate for different applications. An analytic model is used to describe the excitation density dependence of PL intensity and extract the internal PL efficiency and multiple pertinent recombination parameters. A PL imaging technique is used to obtain carrier diffusion length without using a PL quencher, thus, free of unintended influence beyond pure diffusion. Our results show that perovskite samples tend to exhibit lower Shockley-Read-Hall (SRH) recombination rate in both bulk and surface, thus higher PL efficiency than the inorganic counterparts, particularly under low excitation density, even with no or preliminary surface passivation. PL lineshape and diffusion analysis indicate that there is considerable structural disordering in the perovskite materials, and thus photo-generated carriers are not in global thermal equilibrium, which in turn suppresses the nonradiative recombination. This study suggests that relatively low point-defect density, less detrimental surface recombination, and moderate structural disordering contribute to the high PV efficiency in the perovskite. This comparative photovoltaics study provides more insights into the fundamental material science and the search for optimal device designs by learning from different technologies.

14 SOLAR ENERGY↗
DOE OSTI2014

Helical tomotherapy quality assurance with ArcCHECK

To design a quality assurance (QA) procedure for helical tomotherapy that measures multiple beam parameters with 1 delivery and uses a rotating gantry to simulate treatment conditions. The customized QA procedure was preprogrammed on the tomotherapy operator station. The dosimetry measurements were performed using an ArcCHECK diode array and an A1SL ion chamber inserted in the central holder. The ArcCHECK was positioned 10 cm above the isocenter so that the 21-cm diameter detector array could measure the 40-cm wide tomotherapy beam. During the implementation of the new QA procedure, separate comparative measurements were made using ion chambers in both liquid and solid water, the tomotherapy onboard detector array, and a MapCHECK diode array for a period of 10 weeks. There was good agreement (within 1.3%) for the beam output and cone ratio obtained with the new procedure and the routine QA measurements. The measured beam energy was comparable (0.3%) to solid water measurement during the 10-week evaluation period, excluding 2 of the 10 measurements with unusually high background. The symmetry reading was similarly compromised for those 2 weeks, and on the other weeks, it deviated from the solid water reading by ∼2.5%. The ArcCHECK phantom presents a suitable alternative for performing helical tomotherapy QA, provided the background is collected properly. The proposed weekly procedure using ArcCHECK and water phantom makes the QA process more efficient.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Design and status of the Mu2e electromagnetic calorimeter

Here, the Mu2e experiment at Fermilab aims at measuring the neutrinoless conversion of a negative muon into an electron and reach a single event sensitivity of 2.5×10 –17 after three years of data taking. The monoenergetic electron produced in the final state, is detected by a high precision tracker and a crystal calorimeter, all embedded in a large superconducting solenoid (SD) surrounded by a cosmic ray veto system. The calorimeter is complementary to the tracker, allowing an independent trigger and powerful particle identification, while seeding the track reconstruction and contributing to remove background tracks mimicking the signal. In order to match these requirements, the calorimeter should have an energy resolution of O(5)% and a time resolution better than 500 ps at 100 MeV. The baseline solution is a calorimeter composed of two disks of BaF 2 crystals read by UV extended, solar blind, Avalanche Photodiode (APDs), which are under development from a JPL, Caltech, RMD consortium. In this paper, the calorimeter design, the R&D; studies carried out so far and the status of engineering are described. A backup alternative setup consisting of a pure CsI crystal matrix read by UV extended Hamamatsu MPPC's is also presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

The calorimeter system of the new muon g -2 experiment at Fermilab

The electromagnetic calorimeter for the new muon ( g −2) experiment at Fermilab will consist of arrays of PbF 2 Čerenkov crystals read out by large-area silicon photo-multiplier (SiPM) sensors. We report here the requirements for this system, the achieved solution and the results obtained from a test beam using 2.0–4.5 GeV electrons with a 28-element prototype array.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Performance of the CMS RPC upgrade using 2D fast timing readout system

Here, we present a new generation of Resistive Plate Chambers (RPC) that are able to withstand high particle fluxes (up to 2 kHz cm -2 ). These chambers will be instrumented with a precise timing readout electronics and they are proposed to equip two of the four high eta stations of the CMS muon system.Two-gap RPC detectors, with each gap made of two 1.4 mm High Pressure Laminate (HPL) electrodes and separated by a gas gap of the same thickness, are proposed. The new scheme reduces the amount of the avalanche charge produced by the passage of a charged particle through the detector. This improves the RPC rate capability by reducing the needed time to absorb this charge. To keep the RPC efficiency high a sensitive, low-noise and high time resolution Front-End Electronics Board (FEB) is needed to cope with the low charge signal. An ASIC called PETIROC that has all these characteristics is proposed to read out the new chambers. A thin (0.6 mm) Printed Circuit Board (PCB), 165 cm long, equipped with pickup strips of average pitch of 0.75 cm is inserted between the two RPC gaps. The strips are read out from both ends and the arrival time difference of the two signals is used to determine the particle position along the strip ( η position). The absolute time measurement will also be used to reduce the data ambiguity due to the expected high pileup at the High-Luminosity phase of the Large Hadron Collider (HL-LHC).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Performance of the Muon g - 2 calorimeter and readout systems measured with test beam data

A single calorimeter station for the Muon $g-2$ experiment at Fermilab includes the following subsystems: a 54-element array of PbF$_{2}$ Cherenkov crystals read out by large-area SiPMs, bias and slow-control electronics, a suite of 800 MSPS waveform digitizers, a clock and control distribution network, a gain calibration and monitoring system, and a GPU-based frontend read out through a MIDAS data acquisition environment. The entire system performance was evaluated using 2.5 - 5 GeV electrons at the End Station Test Beam at SLAC. This paper includes a description of the individual subsystems and the results of measurements of the energy response and resolution, energy-scale stability, timing resolution, and spatial uniformity. All measured performances meet or exceed the $g-2$ experimental requirements. Based on the success of the tests, the complete production of the required 24 calorimeter stations has been made and installation into the main experiment is complete. Furthermore, the calorimeter response measurements determined here informed the design of the reconstruction algorithms that are now employed in the running $g-2$ experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Integration of the FastIC front-end electronics into the Picosec MicroMegas detector

The Picosec MicroMegas collaboration aims to develop gaseous fast-timing detectors; experimentally, intrinsic time resolutions from around 50 ps to better than 20 ps are obtained, depending on the exact detector configuration. Parts of developments focus on exploring various options of fast-timing multi-channel front-end electronics, to meet the data processing demands of experimental applications. One option is the FastIC, which was developed for reading out positive and negative input polarity sensors with intrinsic amplification. In this paper, the first results from reading out the gaseous Picosec MicroMegas detector with the FastIC are presented. In laboratory studies, a basic description of the data processing chain was performed using a function generator. The results from test beam measurements are used to characterise the timing performance and the charge processing of the combination of FastIC and Picosec MicroMegas, as well as to demonstrate the possibility of a multi-channel detector readout. Although the timing-at-threshold level of the FastIC introduces a time walk of around 1.5 ns, time resolutions of around 50 ps have been achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Microbiomes of frozen blood plasma samples reveal potential pathogens in wild birds and rodents

The lack of genomic data on pathogens from wildlife severely limits our ability to track transmission patterns and trace the origins of an outbreak. There are currently millions of wildlife samples in biobanks around the world, including blood samples. Blood has traditionally been viewed as a sterile environment in healthy individuals, but recent evidence suggests that this is not the case, especially for wild animals. Our goal was to determine whether frozen plasma samples can be surveyed using 16S sequencing to provide information about potential hosts for pathogens for a more complete understanding of disease systems. We sequenced blood plasma from wild North American deer mice ( Peromyscus maniculatus ) and American kestrels ( Falco sparverius ) that were cryogenically stored for 7 and 13 years, respectively, and compared two DNA extraction kits. The kestrel samples contained a very high number of reads that could not be identified to phylum compared to the mouse samples. The two kits differed in the phyla and genera that were detected, and the Zymo kit, which is optimized for plasma and serum, produced more high-quality reads for both kestrel and mouse samples. We identified several pathogenic genera, including Mycoplasma, Escherichia-Shigella , and Bartonella . Sequencing blood samples for pathogens could potentially have broad applications for identifying important reservoir hosts for pathogen transmission and provide a reduced set of species on which to follow up.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Dispersive Fourier transformation for megahertz detection of coherent stokes and anti-stokes Raman spectra

In many fields of study, from coherent Raman microscopy on living cells to time-resolved coherent Raman spectroscopy of gas-phase turbulence and combustion reaction dynamics, the need for the capability to time-resolve fast dynamical and nonrepetitive processes has led to the continued development of high-speed coherent Raman methods and new high-repetition rate laser sources, such as pulse-burst laser systems. However, much less emphasis has been placed on our ability to detect shot to shot coherent Raman spectra at equivalently high scan rates, across the kilohertz to megahertz regime. This is beyond the capability of modern scientific charge coupled device (CCD) cameras, for instance, as would be employed with a Czerny-Turner type spectrograph. In this paper, as an alternative detection strategy with megahertz spectral detection rate, we demonstrate dispersive Fourier transformation detection of pulsed (~90 ps) coherent Raman signals in the time-domain. Instead of reading the frequency domain signal out using a spectrometer and CCD, the signal is transformed into a time-domain waveform through dispersive Fourier transformation in a long single-mode fiber and read-out with a fast sampling photodiode and oscilloscope. Molecular O- and S-branch rotational sideband spectra from both N 2 and H 2 were acquired employing this scheme, and the waveform is fitted to show highly quantitative agreement with a molecular model. Finally, the total detection time for the rotational spectrum was 20 ns, indicating an upper limit to the detection frequency of ~50 MHz, significantly faster than any other reported spectrally-resolved coherent anti-Stokes Raman detection strategy to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

An integrated QSAR-PBK/D modelling approach for predicting detoxification and DNA adduct formation of 18 acyclic food-borne α,β-unsaturated aldehydes

Acyclic α,β-unsaturated aldehydes present in food raise a concern because the α,β-unsaturated aldehyde moiety is considered a structural alert for genotoxicity. However, controversy remains on whether in vivo at realistic dietary exposure DNA adduct formation is significant. The aim of the present study was to develop physiologically based kinetic/dynamic (PBK/D) models to examine dose-dependent detoxification and DNA adduct formation of a group of 18 food-borne acyclic α,β-unsaturated aldehydes without 2- or 3-alkylation, and with no more than one conjugated double bond. Parameters for the PBK/D models were obtained using quantitative structure–activity relationships (QSARs) defined with a training set of six selected aldehydes. Using the QSARs, PBK/D models for the other 12 aldehydes were defined. Results revealed that DNA adduct formation in the liver increases with decreasing bulkiness of the molecule especially due to less efficient detoxification. 2-Propenal (acrolein) was identified to induce the highest DNA adduct levels. At realistic dietary intake, the predicted DNA adduct levels for all aldehydes were two orders of magnitude lower than endogenous background levels observed in disease free human liver, suggesting that for all 18 aldehydes DNA adduct formation is negligible at the relevant levels of dietary intake. The present study provides a proof of principle for the use of QSAR-based PBK/D modelling to facilitate group evaluations and read-across in risk assessment. - Highlights: • Physiologically based in silico models were made for 18 α,β-unsaturated aldehydes. • Kinetic parameters were determined by in vitro incubations and a QSAR approach. • DNA adduct formation was negligible at levels relevant for dietary intake. • The use of QSAR-based PBK/D modelling facilitates group evaluations and read-across.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Unraveling Microbial Communities Associated with Methylmercury Production in Paddy Soils

Here, we report rice consumption is now recognized as an important pathway of human exposure to the neurotoxin methylmercury (MeHg), particularly in countries where rice is a staple food. Although the discovery of a two-gene cluster hgcAB has linked Hg methylation to several phylogenetically diverse groups of anaerobic microorganisms converting inorganic mercury (Hg) to MeHg, the prevalence and diversity of Hg methylators in microbial communities of rice paddy soils remain unclear. We characterized the abundance and distribution of hgcAB genes using third-generation PacBio long-read sequencing and Illumina short-read metagenomic sequencing, in combination with quantitative PCR analyses in several mine-impacted paddy soils from southwest China. Both Illumina and PacBio sequencing analyses revealed that Hg methylating communities were dominated by iron-reducing bacteria (i.e., Geobacter ) and methanogens, with a relatively low abundance of hgcA + sulfate-reducing bacteria in the soil. A positive correlation was observed between the MeHg content in soil and the relative abundance of Geobacter carrying the hgcA gene. Phylogenetic analysis also uncovered some hgcAB sequences closely related to three novel Hg methylators, Geobacter anodireducens , Desulfuromonas sp. DDH964, and Desulfovibrio sp. J2, among which G. anodireducens was validated for its ability to methylate Hg. Lastly, these findings shed new light on microbial community composition and major clades likely driving Hg methylation in rice paddy soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data

In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. Furthermore, the new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data.

42 ENGINEERING↗
DOE OSTI2024

JOINT APPOINTEE: Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries

Combinatorial spread libraries offer a innovative approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated Piezoresponse Force Microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling over macroscopic samples. The concentration dependence of pertinent ferroelectric parameters has been determined and used to develop the mathematical framework based on Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in the high-throughput materials discovery. We make the data sets open to the community and hope that this will stimulate other efforts to interpret and understand the physics of these systems.

Automated Microscopy, Combinatorial Library, Ferro↗