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Results for “motifs”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Online data analysis and reduction: An important co-design motif for extreme-scale computers

A growing disparity between supercomputer computation speeds and I/O rates means that it is rapidly becoming infeasible to analyze supercomputer application output only after that output has been written to a file system. Instead, data-generating applications must run concurrently with data reduction and/or analysis operations, with which they exchange information via high-speed methods such as interprocess communications. The resulting parallel computing motif, online data analysis and reduction (ODAR), has important implications for both application and HPC systems design. Here we introduce the ODAR motif and its co-design concerns, describe a co-design process for identifying and addressing those concerns, present tools that assist in the co-design process, and present case studies to illustrate the use of the process and tools in practical settings.

Data Analysis↗
DOE OSTI2017

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2 -spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Prediction of crystal structures and motifs in the Fe–Mg–O system at Earth’s core pressures

Abstract Fe, Mg, and O are among the most abundant elements in terrestrial planets. While the behavior of the Fe–O, Mg–O, and Fe–Mg binary systems under pressure have been investigated, there are still very few studies of the Fe–Mg–O ternary system at relevant Earth’s core and super-Earth’s mantle pressures. Here, we use the adaptive genetic algorithm (AGA) to study ternary Fe x Mg y O z phases in a wide range of stoichiometries at 200 GPa and 350 GPa. We discovered three dynamically stable phases with stoichiometries FeMg 2 O 4 , Fe 2 MgO 4, and FeMg 3 O 4 with lower enthalpy than any known combination of Fe–Mg–O high-pressure compounds at 350 GPa. With the discovery of these phases, we construct the Fe–Mg–O ternary convex hull. We further clarify the composition- and pressure-dependence of structural motifs with the analysis of the AGA-found stable and metastable structures. Analysis of binary and ternary stable phases suggest that O, Mg, or both could stabilize a BCC iron alloy at inner core pressures.

Wang, Renhai↗
DOE OSTI2018

Towards Noble-Metal-Free Dyads: Ground and Excited State Tuning by a Cobalt Dimethylglyoxime Motif Connected to an Iron N-Heterocyclic Carbene Photosensitizer: Towards Noble-Metal-Free Dyads: Ground and Excited State Tuning by a Cobalt Dimethylglyoxime Motif Connected to an Iron N-Heterocyclic Carbene Photose

Heteroleptic iron based complexes bearing the 2,6-bis[3-(2,6-diisopropylphenyl)imidazol-2-ylidene]pyridine motif and a polypridine ligand have been synthesized and characterized in their ground and excited state. This series of complexes includes a first example of a hetero-bimetallic complex connecting an iron N-heterocyclic carbene photosensitizer with a cobalt dimethylglyoxime fragment. Focus is set on the influence of the linker and cobalt center as second ligand at the iron center on the photophysics. While electronic absorption spectroscopy and cyclic voltammetry reveal a weak mutual influence of the single ligands in the heteroleptic complexes, an increasing MLCT lifetime with larger pi-accepting abilities was found by time-resolved transient absorption spectroscopy, with maximum lifetime in the case of the hetero-bimetallic dyad. Concurrently the MC lifetimes were observed to decrease. The reported results will allow to develop guidelines for designing bimetallic devices, which may allow electron transfer from the photosensitizer fragment to a catalytically active center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Electronic structures and binding motifs of sodium polysulfide clusters NaSn- (n = 5-9): a joint negative ion photoelectron spectroscopy and computational investigation

Motivated by the significant biological functions of polysulfides in life processes and important applications of sodium polysulfides in battery sciences, herein we report a joint experimental and computational study on the electronic and geometric structures of a series of NaSn- (n = 5-9) clusters. The cryogenic, size-selective, negative ion photoelectron spectroscopy (NIPES) is employed to obtain their photoelectron spectra, in which distinctive spectral features with electron binding energy (EBE) up to 6.4 eV are unraveled. The EBE of the first peak in each spectrum for NaSn- (n =5-9), assigned to the transition from the ground state of anion to the ground state of each neutral radical, is observed to increase with cluster size. The vertical detachment energies (VDEs), determined from the first peak maximum, are 3.43 ± 0.02, 3.57 ± 0.02, 3.82 ± 0.03, 3.86 ± 0.02, and 4.00 ± 0.02 eV and the adiabatic detachment energies (ADEs), determined by the onset of the first peak, are 3.27 ± 0.05, 3.44 ± 0.05, 3.65 ± 0.05, 3.75 ± 0.05, and 3.93 ± 0.05 eV, for n = 5-9, respectively. A plural of low-lying isomers of anions are screened and identified with density functional theory calculations, showing that all featuring preference for a chain-like polysulfide moiety electrostatically interacted with a sodium cation. The calculated VDEs and ADEs using the high-level CCSD(T)/aug-cc-pVTZ method are in excellent agreement with experimental results, further confirming the identified isomers as most stable ones. Further analyses based on the excited-state transition, molecular orbitals and natural population charge are performed to assign all observed spectral bands along the binding energy axis, suggesting that the electron detachment process and observed excitations mainly derived from the polysulfide chain of NaSn- clusters. This work provides a fundamental understanding of the intrinsic molecular properties of sodium polysulfide systems, which widely exist in life science and sodium-sulfur cells.

Li, Zhipeng↗
DOE OSTI2019

The Plasmodium falciparum MESA erythrocyte cytoskeleton-binding (MEC) motif binds to erythrocyte ankyrin

The MESA erythrocyte cytoskeleton binding (MEC) motif is a 13-amino acid sequence found in 14 exported Plasmodium falciparum proteins. First identified in the P. falciparum Mature-parasite-infected Erythrocyte Surface Antigen (MESA), the MEC motif is sufficient to target proteins to the infected red blood cell cytoskeleton. To identify host cell targets, purified MESA MEC motif was incubated with a soluble extract from uninfected erythrocytes, precipitated and subjected to mass spectrometry. The most abundant co-purifying protein was erythrocyte ankyrin (ANK1). A direct interaction between the MEC motif and ANK1 was independently verified using co-purification experiments, the split-luciferase assay, and the yeast two-hybrid assay. A systematic mutational analysis of the MEC motif demonstrated the critical role of the conserved aspartic acid residue at the C-terminus of the MEC motif for binding to both erythrocyte inside-out vesicles and to ANK1. Using a panel of ANK1 constructs, the MEC motif binding site was localized to the ZU5C domain, which has no known function. The MEC motif had no impact on erythrocyte deformability when introduced into uninfected erythrocyte ghosts, suggesting the MEC motif’s primary function is to target exported proteins to the cytoskeleton. Finally, we show that PF3D7_0402100 (PFD0095c) binds to ANK1 and band 4.1, likely through its MEC and PHIST motifs, respectively. In conclusion, we have provided multiple lines of evidence that the MEC motif binds to erythrocyte ANK1.

Kilili, Geoffrey K.↗
DOE OSTI2024

GOLEM: GOld standard for Learning and Evaluation of Motifs

Motifs are distinctive, recurring, widely used idiom-like words or phrases, often originating from folklore, whose meaning is anchored in a narrative and have a significance as communicative devices across a wide range of media, including news, literature, and propaganda. Many motifs concisely imply a large constellation of culturally relevant information, and their broad usage suggests their cognitive importance as touchstones of cultural knowledge. As such, their detection is a step towards culturally aware natural language processing. We present GOLEM (GOld standard for Learning and Evaluation of Motifs) a dataset of English news articles, opinion pieces, and broadcast transcripts annotated for motific information. The dataset identifies 25,737 motif candidates across 34 motif types drawn from three cultural or national groups: Jewish, Irish, and Puerto Rican. The dataset contains 2,024,141 words split into 25,737 text snippets drawn from 8,073 articles. Each motif candidate is labeled according to a scheme which identifies the type of usage (motific, referential, eponymic, or unrelated), resulting in 1,743 actual motific instances in the data. Annotation was performed by individuals identifying as members of each group and achieved a Fleiss’ kappa (?) of > 0.55. In addition to the data, we demonstrate that classification of the candidate type is a challenging task for Large Language Models (LLMs) using a few-shot approach; recent models such as T5, FLAN-T5, GPT-2, and Llama 2 (7B) achieved a performance of 41% accuracy at best, where the majority class accuracy is 41% and the average chance accuracy is 27%. These data will support development of new models and approaches for detecting (and reasoning about) motific information in text.

motif, culture, natural language, artificial intel↗
DOE OSTI2021

LxCxD motif of the APC/C coactivator subunit FZR1 is critical for interaction with the retinoblastoma protein

Highlights: • Several oncogenic viral proteins bind to tumor suppressor pRB via LxCxE motif. • LxCxE present in many cellular proteins that interact with pRB. • APC/C interacts with pRB via this motif in its FZR1 subunit. • FZR1 LxCxE-like LxCxD critical for FZR1-pRB direct binding and SKP2 ubiquitylation. • Mutation of FZR1 LxCxD alters cell cycle. Retinoblastoma protein (pRB) regulates cell cycle by utilizing different regions of its pocket domain for interacting with E2F family of transcription factors and with cellular and viral proteins containing an LxCxE motif. An LxCxE-like motif, LxCxD, is present in FZR1, an adaptor protein of the multi-subunit E3 ligase complex anaphase-promoting complex/cyclosome (APC/C). The APC/C{sup FZR1} complex regulates the timely degradation of multiple cell cycle proteins for mitotic exit and maintains G1 state. We report that FZR1 interacts with pRB via its LxCxD motif. By using point mutations, we found that the cysteine residue in the FZR1 LxCxD motif is critical for direct interaction with pRb. The direct binding of the LxCxD motif of FZR1 to the pRB LxCxE binding pocket is confirmed by using human papillomavirus protein E7 as a competitor, both in vitro and in vivo. While mutation of the cysteine residue significantly disrupts FZR1 interaction with pRB, this motif does not affect FZR1 and core APC/C association. Expression of the FZR1 point mutant results in accumulation of S-phase kinase-associated protein 2 (SKP2) and Polo-like kinase 1 (PLK1), while p27{sup Kip1} and p21{sup Cip1} proteins are downregulated, indicating a G1 cell cycle defect. Consistently, cells containing point mutant FZR1 enter the S phase prematurely. Together our results suggest that the LxCxD motif of FZR1 is a critical determinant for the interaction between FZR1 and pRB and is important for G1 restriction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Automated Identification of Molecular Crystals’ Packing Motifs

Packing motifs—patterns in how molecules orient relative to one another in a crystal structure—are an important concept in many subdisciplines of materials science because of correlations observed between specific packing motifs and properties of interest. That said, packing motif data sets have remained small and noisy due to intensive manual labeling processes and insufficient labeling schemes. The most prominent labeling algorithms calculate relative interplanar angles of nearest neighbor molecules to determine the packing motif of a molecular crystal, but this simple approach can fail when neighbors are naively sampled isotropically around the crystal structure. To remedy this issue, here we propose an optimization algorithm, which rotates the molecular crystal structure to find representative molecules that inform the packing motif. We package this algorithm into an automated framework—Autopack—which both optimally rotates the crystal structure and labels the packing motif based on the appropriate neighboring molecules. In this work, we detail the Autopack framework and its performance, which shows improvements compared to previous state-of-the-art labeling methods, providing the first quantitative point of comparison for packing motif labeling algorithms. Furthermore, using Autopack (available at https://ipo.llnl.gov/technologies/software/autopack), we perform the first large-scale study of potential relationships between chemicals’ compositions and packing motifs, which shows that these relationships are more complex than previously hypothesized from studies that used only tens of polycyclic aromatic hydrocarbon molecules. Autopack’s capabilities help pose next steps for crystal engineering research focusing not only on a molecule’s adoption of a specific packing motif but also on new structure–property relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Probabilistic variable-length segmentation of protein sequences for discriminative motif discovery (DiMotif) and sequence embedding (ProtVecX)

In this paper, we present peptide-pair encoding (PPE), a general-purpose probabilistic segmentation of protein sequences into commonly occurring variable-length sub-sequences. The idea of PPE segmentation is inspired by the byte-pair encoding (BPE) text compression algorithm, which has recently gained popularity in subword neural machine translation. We modify this algorithm by adding a sampling framework allowing for multiple ways of segmenting a sequence. PPE segmentation steps can be learned over a large set of protein sequences (Swiss-Prot) or even a domain-specific dataset and then applied to a set of unseen sequences. This representation can be widely used as the input to any downstream machine learning tasks in protein bioinformatics. In particular, here, we introduce this representation through protein motif discovery and protein sequence embedding. (i) DiMotif: we present DiMotif as an alignment-free discriminative motif discovery method and evaluate the method for finding protein motifs in three different settings: (1) comparison of DiMotif with two existing approaches on 20 distinct motif discovery problems which are experimentally verified, (2) classification-based approach for the motifs extracted for integrins, integrin-binding proteins, and biofilm formation, and (3) in sequence pattern searching for nuclear localization signal. The DiMotif, in general, obtained high recall scores, while having a comparable F1 score with other methods in the discovery of experimentally verified motifs. Having high recall suggests that the DiMotif can be used for short-list creation for further experimental investigations on motifs. In the classification-based evaluation, the extracted motifs could reliably detect the integrins, integrin-binding, and biofilm formation-related proteins on a reserved set of sequences with high F1 scores. (ii) ProtVecX: we extend k-mer based protein vector (ProtVec) embedding to variablelength protein embedding using PPE sub-sequences. We show that the new method of embedding can marginally outperform ProtVec in enzyme prediction as well as toxin prediction tasks. In addition, we conclude that the embeddings are beneficial in protein classification tasks when they are combined with raw amino acids k-mer features.

59 BASIC BIOLOGICAL SCIENCES↗