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At least 361 records · Page 20

bnl/pub-Maffettone_2020_08

The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Maffettone, PhillipM [Brookhaven National Lab. (BN↗

Computational and Experimental Characterization of Intermediate Amorphous Phases in Geological Materials

In the subsurface, MgO engineered barriers are employed at the Waste Isolation Pilot Plant (WIPP), a transuranic waste repository near Carlsbad, NM. During service, the MgO will be exposed to high concentration brine environments and may form stable intermediate phases that can alter the barriers effectiveness. Here, MgO was aged in water and three different brine solutions. X-ray diffraction (XRD) and 1 H nuclear magnetic resonance (NMR) analysis were performed to identify the formation of secondary phases. After aging, ~4% of the MgO was hydrated and fine-grained powders resulted in greater loss of crystallinity than hard granular grains. 1 H magic angle spinning (MAS) NMR spectra resolved minor phases not visible in XRD, indicating that diverse 1 H environments are present along with Mg(OH) 2 . Density functional theory (DFT) simulations for several proposed Mg-O-H, Mg-CI-O-H, and Na-O-H containing phases were performed to index peaks in the experimental 1 H MAS NMR spectra. While proposed intermediate crystal structures exhibited overlapping 1 H NMR peaks, Mg-O-H intermediates were attributed to the growth of the 1.0-0.0ppm peak while the Mg-CI-O-H structures contributed to the 2.5- 5.0ppm peak in the chloride containing brines. Overall, NMR analysis of aged MgO indicates the formation of a range of possible intermediate structures that cannot be resolved with XRD analysis alone.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Structural OFF/ON transitions of myosin in relaxed porcine myocardium predict calcium-activated force

Contraction in striated muscle is initiated by calcium binding to troponin complexes, but it is now understood that dynamic transition of myosin between resting, ordered OFF states on thick filaments and active, disordered ON states that can bind to thin filaments is critical in regulating muscle contractility. These structural OFF to ON transitions of myosin are widely assumed to correspond to transitions from the biochemically defined, energy-sparing, super-relaxed (SRX) state to the higher ATPase disordered-relaxed (DRX) state. Here, in this study, we examined the effect of 2’-deoxy-ATP (dATP), a naturally occurring energy substrate for myosin, on the structural OFF to ON transitions of myosin motors in porcine cardiac muscle thick filaments. Small-angle X-ray diffraction revealed that titrating dATP in relaxation solutions progressively moves the myosin heads from ordered OFF states on the thick filament backbone to disordered ON states closer to thin filaments. Importantly, we found that the structural OFF to ON transitions are not equivalent to the biochemically defined SRX to DRX transitions and that the dATP-induced structural OFF to ON transitions of myosin motors in relaxed muscle are strongly correlated with submaximal force augmentation by dATP. These results indicate that structural OFF to ON transitions of myosin in relaxed muscle can predict the level of force attained in calcium-activated cardiac muscle. Computational modeling and stiffness measurements suggest a final step in the OFF to ON transition may involve a subset of DRX myosins that form weakly bound cross-bridges prior to becoming active force-producing cross-bridges.

59 BASIC BIOLOGICAL SCIENCES↗

Further Investigations of Racemic and Chiral Molecular Sieves of the STW Topology

Large single crystals of pure-silica STW-type molecular sieves are prepared using 1,2,3,4,5-pentamethylimidazolium (12345PMI) and 2-ethyl-1,3,4-trimethylimidazolium (2E134TMI) as organic structure-directing agents (OSDAs) and α-amino acid additives. The effects of the amount and type of amino acid on the crystallization of pure-silica STW materials are investigated. Room-temperature single-crystal X-ray diffractometry shows that 12345PMI better fits the STW cage than 2E134TMI and is fully consistent with computed simulations. The synthesis of an enantioenriched R-STW-type molecular sieve having a Si/Ge ratio of 2.2 is achieved using a chiral, dicationic OSDA that contains two stereocenters. Furthermore, the conformation of the chiral OSDA in the chiral framework has been obtained from a Rietveld refinement using synchrotron powder diffraction data and is the first structure refinement of an enantioenriched, inorganic molecular sieve prepared from a pure, asymmetric OSDA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallography companion agent for high-throughput materials discovery

The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time-consuming, error-prone and impossible to scale. With the advent of autonomous robotic scientists or self-driving laboratories, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which outputs probabilistic classifications—rather than absolutes—to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering substantial time savings. It is demonstrated on a diverse set of organic and inorganic materials characterization challenges. This method is directly applicable to inverse design approaches and robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

36 MATERIALS SCIENCE↗

Machine Learning Based System for Automated Estimation of Crystal Unit Cell Parameters from X-ray Diffraction Powder Patterns (MLCell) v0.1

This software uses machine learning models to perform inference on X-ray diffraction powder patterns, output from a diffractometer, to estimate all 6 unit cell parameters of crystalline lattices. Novel aspects of this software originated from the incorporation of concepts from crystallography to an ML-based approach; The resulting method achieves new performance capabilities without significant loss of accuracy and with less computationally intensive models.

Oklejas, Vanessa↗

Solidification modes during additive manufacturing of steel revealed by high-speed X-ray diffraction

Solidification during fusion-based additive manufacturing (AM) is characterized by high solidification velocities and large thermal gradients, two factors that control the solidification mode of metals and alloys. Using two synchrotron-based, in situ setups, we perform high-speed X-ray diffraction measurements to investigate the impact of the solidification velocities and thermal gradients on the solidification mode of a hot-work tool steel over a wide range of thermal conditions of relevance to AM of metals. The solidification mode of primary δ-ferrite is observed at a cooling rate of 2.12x10 4 K/s, and at a higher cooling rate of 1.5x10 6 K/s, δ-ferrite is sup-pressed, and primary austenite is observed. The experimental thermal conditions are evaluated and linked to a Kurz-Giovanola-Trivedi (KGT) based solidification model. The modelling results show that the predictions from the multicomponent KGT model agree with the experimental observations. This work highlights the role of in situ XRD measurements for a fundamental understanding of the microstructure evolution during AM and for vali-dation of computational thermodynamics and kinetics models, facilitating parameter and alloy development for AM processes.

36 MATERIALS SCIENCE↗

Experimental Pathways for Detecting Double Superionicity in Planetary Ices

The ice giant planets Uranus and Neptune are assumed to contain large amounts of planetary ices such as water, methane, and ammonia. The properties of mixtures of such ices at the extreme pressures and temperatures of planetary interiors are not yet well understood. Ab initio computer simulations have predicted that a number of ices exhibit a hydrogen superionic state and a doubly superionic state. Since the latter state has not yet been generated with experiments, we outline here two possible pathways for reaching and detecting such a state with dynamic compression experiments. Here, we suggest X-ray diffraction as the principal tool for detecting when the material becomes doubly superionic and the sublattice of one of the heavy nuclei melts. That would require a temperature of ~3500 K and pressures greater than ~200 GPa for H 3 NO 4 , which we use as an example material here. Such conditions can be reached with experiments that employ an initial shock that is followed by a ramp compression wave. Alternatively, one may use triple-shock compression because a single shock does not yield sufficiently high densities.

Neptune↗

IMS Rapid Response FY21 Summary Report for: Integrating Patterned Probes with Four-Dimensional Scanning Transmission Electron Microscopy for Unrivaled Crystallographic Structure Determination in Nanomaterials

The initial goal of our 4-dimensional scanning transmission electron microscopy (4D-STEM)-based project was to develop strain resolution two orders of magnitude better than what is now currently possible with electron-based scattering techniques, all while collecting scattering information from 7 different tilt axes at one time [multi-beam electron diffraction (MBED)1 ] through the development of a new electron probe-forming aperture with non-circular features (patterned probes 2 ). We set out to accomplish this through a collaboration with Drs. Colin Ophus and Ben Savitsky at Lawrence Berkeley Laboratory (they are the world-leading experts in developing the complex computational codes required to perform orientation analysis and quantitative strain mapping on our 4D-STEM data sets. We are motivated to invest in this area as it will be the only technique sensitive enough to perform three- dimensional automated crystallographic orientation mapping (ACOM) and strain mapping for materials exposed to external stimulus (a focus of our larger efforts).

36 MATERIALS SCIENCE↗

A Diazo Linker Ligand Promotes Flexibility and Induced Fit Binding in a Microporous Copper Coordination Network

Abstract Flexible organic linkers represent an intuitive and effective strategy to design flexible metal–organic materials. We report herein a systematic study concerning the effect of varying the central bond of mixed pyridyl‐benzoate linkers, L, upon the flexibility of three isostructuralkddtopology microporous coordination networks (CNs) of formula ML 2 :X‐kdd‐1‐Cu,1= L = (E)‐4‐(pyridin‐4‐yldiazenyl)benzoate;X‐kdd‐2‐Cu,2= L = (E)‐4‐(2‐(pyridin‐4‐yl)vinyl)benzoate; the previously reportedX‐kdd‐3‐Cu,3= L = 4‐(pyridin‐4‐ylethynyl)benzoate. As revealed by single crystal x‐ray diffraction (SCXRD) and gas sorption studies,X‐kdd‐1‐Cu, exhibited gate‐opening during CO 2 and hydrocarbon (C2 and C8) sorption experiments whereas the other two CNs did not. Insight into these phase transformations was gained from in situ variable‐pressure and variable temperature powder X‐ray diffraction (PXRD), SCXRD, and modeling. Rotation of ligand1around the diazo bond, torsion angle changes between phenyl and carboxylate moieties, and deformation of the Cu‐based rod building blocks enabled activatedX‐kdd‐1‐Cuto form new phases with C8 isomers and CH 2 Cl 2 , CH 2 Cl 2 inducing contraction of the activated phase. Computational studies suggest that1enables flexibility thanks to its lower barrier of deformation versus2or3. This study teaches that diazo moieties could offer a general strategy to enhance the flexibility of CNs.

Chemistry↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Structural Characterisation and DFT-Aided Interpretation of Vibrational Spectra for Cyclo(l-Cys-d-Cys) Cyclic Dipeptide in a Solid State

Cyclic dipeptides with two intramolecular peptide bonds forming a six-membered 2,5-diketopiperazine ring are gaining significant attention due to their biological and chemical properties. Small changes in the local geometry of such molecules (from cis to trans) can lead to significant structural differences. This work presents the results of a study of cyclo(l-Cys-d-Cys), a dipeptide comprising two cysteine molecules in opposite chiral configurations, with the functional groups situated at both sides of the diketopiperazine ring. X-ray diffraction (XRD) experiment revealed that the molecule crystallises in the $P$-1 space group, which includes the centre of inversion. The IR and Raman vibrational spectra of the molecule were acquired and interpreted in terms of the potential energy distribution (PED) according to the results of density functional theory (DFT) calculations. The DFT-assisted analysis of energy frameworks for the hydrogen bond network within molecular crystals was performed to support the interpretation of X-ray structural data. The optimisation of the computational model based on three-molecule geometry sections from the crystallographic structure, selected to appropriately reflect the intermolecular interactions responsible for the formation of 1D molecular tapes in cyclo(l-Cys-d-Cys) crystal, allowed for better correspondence between theoretical and experimental vibrational spectra. This work can be considered the first complete structural characterisation of cyclo(l-Cys-d-Cys), complemented via vibrational spectroscopy results with full band assignment aided with the use of the DFT method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling High Current Pulsed Discharge in AA Battery Cathodes: The Effect of Localized Charging during Rest

During high current operation, substantial heterogeneity develops within battery cathodes, particularly when their thickness is large. Heterogeneity relaxation during subsequent rest is important for understanding battery performance under pulsed conditions. Localized charge balancing phenomena within batteries at zero net current are not well understood and merit investigation. In this work, the heterogeneity within cathodes of commercial alkaline Zn–MnO 2 batteries is measured during discharge and monitored during rest using energy dispersive X-ray diffraction (EDXRD). Significant gradients in protonation form during discharge and partially relax under rest. It is demonstrated that the proton gradient relaxation is through local redox activity at zero net current, where local (de)protonation works to redistribute charge across the cathode thickness. To support this redox-based relaxation, a fundamental kinetic study on prismatic MnO 2 cathodes is conducted to determine an appropriate model to describe both discharge and charge kinetics of MnO 2 . These kinetics are incorporated into a computational model to simulate the proton gradient formation and partial relaxation under identical discharge conditions as the operando EDXRD experiments. Model and experimental data are found to be in excellent agreement, correctly predicting localized charge balancing at rest.

Batteries↗

13 C ENDOR Characterization of the Central Carbon within the Nitrogenase Catalytic Cofactor Indicates That the CFe 6 Core Is a Stabilizing “Heart of Steel”

Substrates and inhibitors of Mo-dependent nitrogenase bind and react at Fe ions of the active-site FeMo-cofactor [7Fe–9S–C–Mo–homocitrate] contained within the MoFe protein α-subunit. The cofactor contains a CFe 6 core, a carbon centered within a trigonal prism of six Fe, whose role in catalysis is unknown. Targeted 13 C labeling of the carbon enables electron-nuclear double resonance (ENDOR) spectroscopy to sensitively monitor the electronic properties of the Fe–C bonds and the spin-coupling scheme adopted by the FeMo-cofactor metal ions. Here this report compares 13 CFe 6 ENDOR measurements for (i) the wild-type protein resting state (E 0 ; α-Val 70 ) to those of (ii) α-Ile 70 , (iii) α-Ala 70 -substituted proteins; (iv) crystallographically characterized CO-inhibited “hi-CO” state; (v) E 4 (4H) Janus intermediate, activated for N 2 binding/reduction by accumulation of 4[ e– /H + ]; (vi) E 4 (2H)* state containing a doubly reduced FeMo-cofactor without Fe-bound substrates; and (vii) propargyl alcohol reduction intermediate having allyl alcohol bound as a ferracycle to FeMo-cofactor Fe6. All states examined, both S = 1/2 and 3/2 exhibited near-zero 13 C isotropic hyperfine coupling constants, $^Ca$ = [-1.3 ↔ +2.7] MHz. Density functional theory computations and natural bond orbital analysis of the Fe-C bonds show that this occurs because a (3 spin-up/3 spin-down) spin-exchange configuration of CFe 6 Fe-ion spins produces cancellation of large spin-transfers to carbon in each Fe–C bond. Previous X-ray diffraction and DFT both indicate that trigonal-prismatic geometry around carbon is maintained with high precision in all these states. The persistent structure and Fe–C bonding of the CFe 6 core indicate that it does not provide a functionally dynamic (hemilabile) “beating heart”-instead it acts as “a heart of steel”, stabilizing the structure of the FeMo-cofactor-active site during nitrogenase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlated Anion Disorder in Heteroanionic Cubic TiOF 2

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO 3 -type) TiOF 2 using X-ray pair distribution function (PDF), 19 F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF 2 , characterized by predominant cis-[O 2 F 4 ] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19 F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19 F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF 4 . We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of a mixed close-packed structure in superionic water

The study of superionic (SI) water has been a highly active research area since its theoretical prediction. Despite significant experimental and computational efforts, its melting curve and the stability of different oxygen lattices remain debated, impacting our understanding of SI ice’s peculiar transport properties. Experimental results at lower pressures show disagreement, whereas data at higher pressures are scarce due to the extreme challenges of such experiments. In this work, we present ultrafast X-ray diffraction results of water compressed by multiple shocks to pressures up to ~ 180 GPa. At pressures exceeding 150 GPa and temperatures around 2500 K, our diffraction patterns challenge the pure FCC-SI phase model, providing experimental evidence of the mixed close-packed superionic phase predicted by advanced ab initio calculations. At lower pressures, we observe simultaneous signatures of BCC and FCC structures within a pressure-temperature range consistent with some static-compression experiments, helping to resolve contradictory results in literature. These insights offer new constraints on the stability domains of SI phases and reveal detailed structural features, such as stacking faults. Our results advance the structural understanding of high-pressure SI ice to a level approaching that of ice I polymorphs, with potential implications for water-rich interiors of giant planets.

Andriambariarijaona, Leon [Centre National de la R↗

Exploring the phase space of Zn 2 SbN 3 , a novel semiconducting nitride

The novel semiconductor Zn 2 SbN 3 is one of a growing list of ternary nitrides with promise for optoelectronic and energy applications. Previous work by Arca et al. [Materials Horizons, 2019, 6, 1669–1974] first reported synthesis of this material, but did not explore the effects of growth conditions on material formation. In this work, we present a semi-automated study of the relationship between growth conditions and crystallinity via high-throughput RF sputtering and a custom X-ray diffraction analysis routine. Zn 2 SbN 3 is found to crystallize in a wide range of growth conditions, and the formation of several contaminant phases is examined. Electron microscopy of these secondary phases, caused both by off-stoichiometry and by growth conditions, provides insight into the growth mechanisms of Zn 2 SbN 3 . Furthermore, computational work relates this material to other Zn-based ternary nitrides and offers an explanation for the difficulty of growing cation-ordered material despite the wide range of growth conditions explored.

36 MATERIALS SCIENCE↗

Shock behavior of materials

The physics governing the response of materials to shock loading has many applications in various fields, ranging from Earth and planetary science to engineering and ballistics. Elucidating the behavior of materials experiencing the passage of shock waves motivates active research worldwide, including experimental developments with in situ and time-resolved measurements, modern computational approaches, and multi-scale simulations.

36 MATERIALS SCIENCE↗