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At least 505 records · Page 28

Identifying crystal structures and chemical reactions at the interface of stanene on Bi 2 Te 3

Synthesizing monolayers and heterostructures is an enabling approach to extract new physical phenomena from bulk materials. Among the structures amenable to this approach is stanene, which is a monolayer of tin, similar to graphene, and has been predicted to host one-dimensional topological states at its edges. Stanene can be tuned by decorating with different adatoms, which makes it a promising platform on which to engineer topological devices. Here, we deposit Sn on Bi 2 Te 3 and characterize the growth using anomalous synchrotron x-ray scattering and x-ray photoelectron spectroscopy (XPS). X-ray diffraction data reveal the formation of epitaxial Sn-based structures, along with penetration of Sn into the Bi 2 Te 3 , with Sn intercalating between the upper 10 Bi 2 Te 3 quintuple layers. Additionally, XPS data show deposited Sn reacting to form SnTe and Bi at the Bi 2 Te 3 surface. The calculated heat of reaction for Sn and Bi2Te3 is consistent with an exothermic reaction to SnTe and Bi. Using thermodynamic calculations as a guide, we identify several candidate substrates that can stabilize the stanene phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring the electron temperature and identifying plasma detachment using machine learning and spectroscopy

A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from operation of the DIII-D tokamak using extreme ultraviolet/vacuum ultraviolet emission spectroscopy matched with high-accuracy divertor Thomson scattering measurements of the electron temperature, T e . This NN is shown to be particularly good at predicting T e at low temperatures (T e < 10 eV) where the NN demonstrated a mean average error of less than 1 eV. Trained to detect plasma detachment in the tokamak divertor, a NN classifier was able to correctly identify detached states (T e < 5 eV) with a 99% accuracy (an F 1 score of 0.96) at an acquisition rate 10× faster than the Thomson scattering measurement. The performance of the model is understood by examining a set of 4800 theoretical spectra generated using collisional radiative modeling that was also used to predict the performance of a low-cost spectrometer viewing nitrogen emission in the visible wavelengths. Furthermore, these results provide a proof-of-principle that low-cost spectrometers leveraged with machine learning can be used to boost the performance of more expensive diagnostics on fusion devices and be used independently as a fast and accurate T e measurement and detachment classifier.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Identifying spinon excitations from dynamic structure factor of spin-1/2 Heisenberg antiferromagnet on the Kagome lattice

Significance In frustrated quantum magnets, the interplay between quantum fluctuation and geometric frustration may prevent magnetic ordering and result in exotic quantum spin liquids, where the spin degrees of freedom form disordered liquid-like states with novel fractionalized excitations. Here, we study the dynamical response of spin liquids on a Kagome lattice Heisenberg antiferromagnet. Our results reproduce the main observations in the inelastic neutron scattering measurements of herbertsmithite and unveil the spin liquid nature of the ground state with fractionalized spinon excitations. By crossing the quantum-phase transition between the spin liquid and magnetically ordered phase, we identify the condensation of two-spinon bound state as the driving force.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

Identifying functional enhancer elements in metazoan systems is a major challenge. Large-scale validation of enhancers predicted by ENCODE reveal false-positive rates of at least 70%. We used the pregrastrula-patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held-out data results from heterogeneity of functional signatures in enhancer elements. We show that at least two classes of enhancers are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, greater than 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well-predicted elements is composed predominantly of enhancers driving multistage segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naïve Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome. An analysis of 32 SDEs using whole-mount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.

54 ENVIRONMENTAL SCIENCES↗

Reaction intermediates during operando electrocatalysis identified from full solvent quantum mechanics molecular dynamics

Electrocatalysis provides a powerful means to selectively transform molecules, but a serious impediment in making rapid progress is the lack of a molecular-based understanding of the reactive mechanisms or intermediates at the electrode–electrolyte interface (EEI). Recent experimental techniques have been developed for operando identification of reaction intermediates using surface infrared (IR) and Raman spectroscopy. However, large noises in the experimental spectrum pose great challenges in resolving the atomistic structures of reactive intermediates. To provide an interpretation of these experimental studies and target for additional studies, we report the results from quantum mechanics molecular dynamics (QM-MD) with explicit consideration of solvent, electrode–electrolyte interface, and applied potential at 298 K, which conceptually resemble the operando experimental condition, leading to a prototype of operando QM-MD (o-QM-MD). With o-QM-MD, we characterize 22 possible reactive intermediates in carbon dioxide reduction reactions ( C O 2 RRs). Furthermore, we report the vibrational density of states (v-DoSs) of these intermediates from two-phase thermodynamic (2PT) analysis. Accordingly, we identify important intermediates such as chemisorbed C O 2 ( b - C O 2 ), *HOC-COH, *C-CH, and *C-COH in our o-QM-MD likely to explain the experimental spectrum. Indeed, we assign the experimental peak at 1,191 cm −1 to the mode of C-O stretch in *HOC-COH predicted at 1,189 cm −1 and the experimental peak at 1,584 cm −1 to the mode of C-C stretch in *C-COD predicted at 1,581 cm −1 . Interestingly, we find that surface ketene (*C=C=O), arising from *HOC-COH dehydration, also shows signals at around 1,584 cm −1 , which indicates a nonelectrochemical pathway of hydrocarbon formation at low overpotential and high pH conditions.

36 MATERIALS SCIENCE↗

GDGT cyclization proteins identify the dominant archaeal sources of tetraether lipids in the ocean

Glycerol dibiphytanyl glycerol tetraethers (GDGTs) are distinctive archaeal membrane-spanning lipids with up to eight cyclopentane rings and/or one cyclohexane ring. The number of rings added to the GDGT core structure can vary as a function of environmental conditions, such as changes in growth temperature. This physiological response enables cyclic GDGTs preserved in sediments to be employed as proxies for reconstructing past global and regional temperatures and to provide fundamental insights into ancient climate variability. Yet, confidence in GDGT-based paleotemperature proxies is hindered by uncertainty concerning the archaeal communities contributing to GDGT pools in modern environments and ambiguity in the environmental and physiological factors that affect GDGT cyclization in extant archaea. To properly constrain these uncertainties, a comprehensive understanding of GDGT biosynthesis is required. Here in this paper, we identify 2 GDGT ring synthases, GrsA and GrsB, essential for GDGT ring formation in Sulfolobus acidocaldarius . Both proteins are radical S-adenosylmethionine proteins, indicating that GDGT cyclization occurs through a free radical mechanism. In addition, we demonstrate that GrsA introduces rings specifically at the C-7 position of the core GDGT lipid, while GrsB cyclizes at the C-3 position, suggesting that cyclization patterns are differentially controlled by 2 separate enzymes and potentially influenced by distinct environmental factors. Finally, phylogenetic analyses of the Grs proteins reveal that marine Thaumarchaeota, and not Euryarchaeota, are the dominant source of cyclized GDGTs in open ocean settings, addressing a major source of uncertainty in GDGT-based paleotemperature proxy applications.

59 BASIC BIOLOGICAL SCIENCES↗

Spatiotemporal analysis identifies ABF2 and ABF3 as key hubs of endodermal response to nitrate

Nitrate is a nutrient and a potent signal that impacts global gene expression in plants. However, the regulatory factors controlling temporal and cell type–specific nitrate responses remain largely unknown. We assayed nitrate-responsive transcriptome changes in five major root cell types of the Arabidopsis thaliana root as a function of time. We found that gene-expression response to nitrate is dynamic and highly localized and predicted cell type–specific transcription factor (TF)–target interactions. Among cell types, the endodermis stands out as having the largest and most connected nitrate-regulatory gene network. ABF2 and ABF3 are major hubs for transcriptional responses in the endodermis cell layer. We experimentally validated TF–target interactions for ABF2 and ABF3 by chromatin immunoprecipitation followed by sequencing and a cell-based system to detect TF regulation genome-wide. Validated targets of ABF2 and ABF3 account for more than 50% of the nitrate-responsive transcriptome in the endodermis. Moreover, ABF2 and ABF3 are involved in nitrate-induced lateral root growth. Our approach offers an unprecedented spatiotemporal resolution of the root response to nitrate and identifies important components of cell-specific gene regulatory networks.

59 BASIC BIOLOGICAL SCIENCES↗

A protein phosphatase 1 specific phos phatase ta rgeting p eptide (PhosTAP) to identify the PP1 phosphatome

Phosphoprotein phosphatases (PPPs) are the key serine/threonine phosphatases that regulate all essential signaling cascades. In particular, Protein Phosphatase 1 (PP1) dephosphorylates ~80% of all ser/thr phosphorylation sites. Here, we developed a phosphatase targeting peptide (PhosTAP) that binds all PP1 isoforms and does so with a stronger affinity than any other known PP1 regulator. This PhosTAP can be used as a PP1 recruitment tool for Phosphorylation Targeting Chimera (PhosTAC)-type recruitment in in vitro and cellular experiments, as well as in phosphoproteomics experiments to identify PP1-specific substrates and phosphosites. The latter is especially important to further our understanding of cellular signaling, as the identification of substrates and especially phosphosites that are targeted by specific phosphatases lags behind that of their kinase counterparts. Using PhosTAP-based proteomics, we show that, counter to our current understanding, many PP1 regulators are also substrates, that the number of residues between regulator PP1-binding and phosphosites vary significantly, and that PP1 counteracts the activities of mitotic kinases. Finally, we also found that Haspin kinase is a direct substrate of PP1 and that its PP1-dependent dephosphorylation modulates its activity during anaphase. Together, we show that PP1-specific PhosTAPs are a powerful tool for +studying PP1 activity in vitro and in cells.

Science & Technology - Other Topics↗

Identifying candidate structured RNAs in CRISPR operons

Noncoding RNAs with secondary structures play important roles in CRISPR-Cas systems. Many of these structures likely remain undiscovered. We used a large-scale comparative genomics approach to predict 156 novel candidate structured RNAs from 36,111 CRISPR-Cas systems. A number of these were found to overlap with coding genes, including palindromic candidates that overlapped with a variety of Cas genes in type I and III systems. Among these 156 candidates, we identified 46 new models of CRISPR direct repeats and 1 tracrRNA. This tracrRNA model occasionally overlapped with predicted cas9 coding regions, emphasizing the importance of expanding our search windows for novel structure RNAs in coding regions. We also demonstrated that the antirepeat sequence in this tracrRNA model can be used to accurately assign thousands of predicted CRISPR arrays to type II-C systems. This study highlights the importance of unbiased identification of candidate structured RNAs across CRISPR-Cas systems.

59 BASIC BIOLOGICAL SCIENCES↗

A strategy to identify materials exhibiting a large nonlinear phononics response: tuning the ultrafast structural response of LaAlO 3 with pressure

We use theory and first-principles calculations to investigate how structural changes induced by ultrafast optical excitation of infrared-active phonons change with hydrostatic pressure in LaAlO 3 . Our calculations show that the observed structural changes are sensitive to pressure, with the largest changes occurring at pressures near the boundary between the cubic perovskite and rhombohedral phases. We rationalize our findings by defining a figure of merit that depends only on intrinsic materials quantities, and show that the peak response near the phase boundary is dictated by different microscopic materials properties depending on the particular phonon mode being excited. Our work demonstrates how it is possible to systematically identify materials that may exhibit particularly large changes in structure and properties due to optical excitation of infrared-active phonons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Identifying the electron–positron cascade regimes in high-intensity laser-matter interactions

Strong-field quantum electrodynamics predicts electron-seeded electron–positron pair cascades when the electric field in the rest-frame of the seed electron approaches the Sauter–Schwinger field, i.e. $\eta ={E}_{{\rm{RF}}}/{E}_{S}\sim 1$. Electrons in the focus of next generation multi-PW lasers are expected to reach this threshold. We identify three distinct cascading regimes in the interaction of counter-propagating, circularly-polarised laser pulses with a thin foil by performing a comprehensive scan over the laser intensity (from 10 23 to 5 × 10 24 W cm –2 ) and initial foil target density (from 10 26 to 10 31 m –3 ). For low densities and intensities the number of pairs grows exponentially. If the intensity and target density are high enough the number density of created pairs reaches the relativistically-corrected critical density, the pair plasma efficiently absorbs the laser energy (through radiation reaction) and the cascade saturates. If the initial density is too high, such that the initial target is overdense, the cascade is suppressed by the skin effect. Here, we derive a semi-analytical model which predicts that dense pair plasmas are endemic features of these interactions for intensities above 10 24 W cm –2 provided the target's relativistic skin-depth is longer than the laser wavelength. Further, it shows that pair production is maximised in near-critical-density targets, providing a guide for near-term experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Identifying the microtearing modes in the pedestal of DIII-D H-modes using gyrokinetic simulations

Recent evidence points toward the microtearing mode (MTM) as an important fluctuation in the H-mode pedestal for anomalous electron heat transport. A study of the instabilities in the pedestal region carried out using gyrokinetic simulations to model an ELMy H-mode DIII-D discharge (USN configuration, 1.4 MA plasma current, and 3 MW heating power) is presented. The simulations produce MTMs, identified by predominantly electromagnetic heat flux, small particle flux, and a substantial degree of tearing parity. The magnetic spectrogram from Mirnov coils exhibits three distinct frequency bands—two narrow bands at lower frequency (~35–55 kHz and ~70–105 kHz) and a broader band at higher frequency (~300–500 kHz). Global linear GENE simulations produce MTMs that are centered at the peak of the ω* profile and correspond closely with the bands in the spectrogram. The three distinctive frequency bands can be understood from the basic physical mechanisms underlying the instabilities. For example (i) instability of certain toroidal mode numbers (n) is controlled by the alignment of their rational surfaces with the peak in the ω* profile, and (ii) MTM instabilities in the lower n bands are the conventional collisional slab MTM, whereas the higher n band depends on curvature drive. While many features of the modes can be captured with the local approximation, a global treatment is necessary to quantitatively reproduce the detailed band gaps of the low-n fluctuations. Notably, the transport signatures of the MTM are consistent with careful edge modeling by SOLPS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: A. identifying options for the control parameters*

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter-erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding. This part A of the present study reports new results for largely the same ITER cases, confirming the strong correlations reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne [Ne/s], and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In the companion report, part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction 2 point modelling, Rev2PM. The input to the reduced model is a value of the variable pair (T et @q ⟂,pk ,Inj Ne ) and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , n e,Xpt (the electron density at the poloidal location of the X-point), etc. In part B the reduced model is quantitatively characterized using one half of the code cases; it is then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half of the cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Identifying heavy-flavor jets using vectors of locally aggregated descriptors

Abstract Jets of collimated particles serve a multitude of purposes in high energy collisions. Recently, studies of jet interaction with the quark-gluon plasma (QGP) created in high energy heavy ion collisions are of growing interest, particularly towards understanding partonic energy loss in the QGP medium and its related modifications of the jet shower and fragmentation. Since the QGP is a colored medium, the extent of jet quenching and consequently, the transport properties of the medium are expected to be sensitive to fundamental properties of the jets such as the flavor of the parton that initiates the jet. Identifying the jet flavor enables an extraction of the mass dependence in jet-QGP interactions. We present a novel approach to tagging heavy-flavor jets at collider experiments utilizing the information contained within jet constituents via the model architecture. We show the performance of this model in proton-proton collisions at center of mass energy √(s) = 200 GeV as characterized by common metrics and showcase its ability to extract high purity heavy-flavor jet sample at various jet momenta and realistic production cross-sections including a brief discussion on the impact of out-of-time pile-up. Such studies open new opportunities for future high purity heavy-flavor measurements at jet energies accessible at current and future collider experiments.

Instruments & Instrumentation↗

TranSyT , an innovative framework for identifying transport systems

The importance and rate of development of genome-scale metabolic models have been growing for the last few years, increasing the demand for software solutions that automate several steps of this process. However, since TRIAGE’s release, software development for the automatic integration of transport reactions into models has stalled. Here, in this paper, we present the Transport Systems Tracker (TranSyT). Unlike other transport systems annotation software, TranSyT does not rely on manual curation to expand its internal database, which is derived from highly curated records retrieved from the Transporters Classification Database and complemented with information from other data sources. TranSyT compiles information regarding transporter families and proteins, and derives reactions into its internal database, making it available for rapid annotation of complete genomes. All transport reactions have GPR associations and can be exported with identifiers from four different metabolite databases. TranSyT is currently available as a plugin for merlin v4.0 and an app for KBase.

59 BASIC BIOLOGICAL SCIENCES↗

GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.

59 BASIC BIOLOGICAL SCIENCES↗

Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum

Abstract Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35–43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying Spectral Descriptors for Protonation in BaZr 0.8 Y 0.2 O 3-x with Electron Energy Loss Spectroscopy

Hydrogen economy is of paramount importance in the global transition to a sustainable, clean energy source that contributes to decarbonization efforts. In particular, the proton conducting proton ceramic fuel cells (PCFCs) play a crucial role in promoting hydrogen energy technology [1-5]. In a PCFC, the electrolyte is typically a solid oxide material that enables proton transport and can operate at temperatures lower than those of traditional oxygen ion conducting fuel cells [6]. The reduced operating temperature of PCFCs contributes to their durability, scalability, and efficiency [7,8]. BaZr 0.8 Y 0.2 O 3-x (BZY) is a promising proton conducting solid oxide electrolyte [9,10]. The emphasis on proton conductivity entails the importance of understanding proton content in the system. However, previous studies have largely relied on bulk techniques such as electrochemical impedance spectroscopy [7,11], Karl-Fischer titration [12,13], and thermogravimetric analysis [14] to obtain proton concentration. This is due to the small atomic size and light mass of hydrogen species making direct detection challenging. Bulk methods may be useful in estimating the proton content; however, it overlooks possible proton concentration gradient or segregation that may occur across or within a nanoparticle, especially when proton incorporation occurs nonuniformly through steam exposure on powder samples. In this paper, BZY is protonated at an estimated 0.15 mol of protons via steam exposure. Electron energy loss spectroscopy (EELS) with nanoscale spatial resolution is explored to identify proxy signals for proton detection using a JEOL ARM300 microscope operated at 300 kV with a Gatan GIF Continuum detector.

08 HYDROGEN↗