Bottom-up construction of a superstructure in a porous uranium-organic crystal
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The quest for achieving high coercivity in Sm(Fe,Co,Ti) 12 alloys, despite their inherent strong magnetocrystalline anisotropy, has posed significant challenges. Recently, (Sm,Zr)(Fe,Co,Ti) 12 monocrystalline particles have exhibited coercivity μ 0 H c > 1.2 T, showcasing promising prospects and significant potential for both manufacturing and research endeavors. This study delves into the structural evolution of (Sm,Zr)(Fe,Co,Ti) 12 (1:12) alloy particles made via the calciothermic reduction-diffusion synthesis process as influenced by the molar ratios of Ca atoms to O 2- ions (Ca/O), annealing time and annealing temperature. Critical insight that informs conditions to optimize the magnetic response is gained via systematic experimentation and advanced electron microscopy. Complex structural features, including core-shell morphologies and intricate multiphase compositions within individual particles, are unveiled. An optimal Ca/O ratio of 1.30 produces particles with a coercivity up to μ 0 H c = 1.63 T, while higher Ca/O ratios induce the formation of a Sm-rich TbCu 7 -type (1: 7 ) phase, which only partially transforms into the desired 1:12 phase during annealing. Persistent remnants of the 1:7 phase locally impact atomic structure, particle morphology, and coercivity. Furthermore, these findings underscore the complex interplay between synthesis parameters, resulting structures, and magnetic properties, informing the design and optimization of high-performance permanent magnets comprised of the (1:12) compound.
With the development of local electrode atom probe tomography (LEAP), the materials systems feasible for atomic structure determination has expanded from predominantly metals to include heterogeneous materials with complex structure and compositions. This makes the 3D atomic structure determination possible for most energy materials in battery, fuel cell, semiconductor, and nuclear applications. Atom probe tomography (APT) has been utilized to study multiphase materials with segregation and interface problems. The unique and quantitative information retrieved from APT can provide a foundation for the study of kinetic pathways, nanoscale composition mapping, multilayer interfacial segregation, dislocations and grain boundaries. However, a new challenge surfaces when the materials systems expand into heterogeneous materials: the traditional structure reconstruction introduces false magnification and large artifacts due to the underlying assumption of uniform and isotropic evaporation.
SETD8 is a histone H4–K20 methyltransferase that plays an essential role in the maintenance of genomic integrity during mitosis and in DNA damage repair, making it an intriguing target for cancer research. While some small molecule inhibitors for SETD8 have been reported, the structural binding modes for these inhibitors have not been revealed. Using the complex structure of the substrate peptide bound to SETD8 as a starting point, different natural and unnatural amino acid substitutions were tested, and a potent (Ki 50 nM, IC 50 0.33 μM) and selective norleucine containing peptide inhibitor has been obtained.
Spectrometry is combined with first-principles simulations of solvated Cu 2+ complexes to elucidate the roles of ligand coordination, d-orbital fine structure, complex geometry, and solvation environment in determining optical absorption profiles.
When designing femtosecond laser mirrors, one tries to minimize the peak intensity within the high-index layers to increase the laser-induced damage threshold. Typically, the optimization procedure utilizes the electric field distribution in the layer stack generated by monochromatic irradiation. Furthermore, this approach is sufficient for certain structures like high-reflectors based on quarter-wave films. More complex structures require to take into account the exact evolution of the pulse parameters such as peak intensity and duration within the multi-layer system. We exemplify this by discussing a merit function that can be included in femtosecond optics design.
The versatile crosslinking chemistry of poly(dimethylsiloxane) (PDMS) based materials affords a large research space in which polymers with widely varying elastomeric properties may be synthesized. Parameters such as chain length, crosslink density, crosslink functionality, filler content, and chain chemistry can all be modified to produce materials with specific physical and mechanical properties. Commercial polysiloxane based, ‘silicone’ elastomers are generally intractable, which makes the precise characterization of their networks problematic. We report here the application of equilibrium solvent uptake analysis and 1 H double-quantum nuclear magnetic resonance ( 1 H DQ NMR) spectroscopy to determine the network topology of end-linked PDMS networks with non-ideal network topology. Despite their structural complexity, we can quantify both the classical and non-classical contributions to network structure using 1 H DQ NMR which are in reasonable agreement with solvent uptake data. These findings serve as the foundation for future investigations of even more complex commercial silicones using 1 H DQ NMR.
The ability to fabricate larger complex silicon carbide composites is an enabling technology for advanced reactors. Processing techniques to make complex SiC/SiC structures must be versatile enough to facilitate fabrication of both very large components (>1 m), as well as very small feature sizes (<1 mm), minimize the amount of machining required to complete the final part, and must also provide composite material with similar performance to bulk properties previously established for planar SiC/SiC composite material. This paper presents results on fabrication of complex silicon carbide structures and targeted testing aimed specifically at understanding how complex features impact composite performance. Silicon carbide (SiC) and silicon carbide matrix, silicon carbide fiber-reinforced composites (SiC/SiC) are a strong candidate for cladding and core structure used in advanced reactor concepts such as General Atomics' (GA) Energy Multiplier Module (EM{sup 2}) as well as accident tolerant fuel (ATF) in LWRs. SiC retains its strength up to very high temperatures, is stable under irradiation, and shows favorable neutronics and oxidation resistance compared to alloy alternatives. However, unlike metals, SiC cannot be easily machined, formed or welded to make the more complex core components needed to fully realize the benefits of advanced high temperature reactors. TEP processing provides an appealing route to achieving SiC/SiC composite structures with enhanced feature complexity. This is a critical development in the maturation of SiC/SiC for in-core structural materials in advanced reactors. This processing route provides an avenue to make large, dense, complex structures. Experiments have shown retention of strength and pseudo-ductility with hole spacing as small as 4 mm with potential for still smaller feature spacing. The results indicate that feature spacing is not limited by processing effects, but instead by the fiber architecture. The lower limit of feature spacing will likely have implications on potential core loading limits in advanced nuclear reactors utilizing SiC/SiC. (authors)
Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.
Protein import into chloroplasts is carried out by the protein translocons at the outer and inner envelope membranes (TOC and TIC). Detailed structures for these translocons are lacking, with only a low-resolution TOC complex structure available. Recently, we showed that the TOC/TIC translocons can import folded proteins, a rather unique feat for a coupled double membrane system. In this work we also determined the maximum functional TOC/TIC pore size to be 30–35 Å. Here, we discuss how such large pores could form and compare the structural dynamics of the pore-forming Toc75 subunit to its bacterial/mitochondrial Omp85 family homologs. We put forward structural models that can be empirically tested and also briefly review the pore dynamics of other protein translocons with known structures.
We provide the initial performance evaluation of a 21 Tesla Fourier transform ion cyclotron resonance mass spectrometer operating at the Environmental Molecular Sciences Laboratory at Pacific Northwest National Laboratory. The spectrometer constructed for the 21T system employs a commercial dual linear ion trap mass spectrometer coupled to a FTICR spectrometer designed and built in-house. Performance gains from moving to higher magnetic field strength are exemplified by the measurement of peptide isotopic fine structure, complex natural organic matter mixtures, and large proteins. Accurate determination of isotopic fine structure was demonstrated for doubly charged substance P with minimal spectral averaging, and 8,158 molecular formulas assigned to Suwannee River Fulvic Acid standard with RMS error of 10 ppb. We also demonstrated superior performance for intact proteins; namely, broadband isotopic resolution of the entire charge state distribution of apotransferrin (78 kDa) and facile isotopic resolution of monoclonal antibody under a variety of acquisition parameters (e.g. 6 s time-domains with absorption mode processing yielded resolution of approximately 1M at m/z =2,700).
Modern storage-ring designs often require an uneven bunch distribution pattern. An uneven bunch fill pattern can result in complex structures for the beam current spectra. Particularly at high average beam currents, these complex current spectra need to be taken into account in concern of beam-dynamical effects. In this study, we analyze a beam current spectrum for various filling patterns with bunch trains and gaps. The characteristics of the resulting beam current spectra are illustrated and discussed.
Composite structures are increasing in prevalence throughout the aerospace, wind, defense, and transportation industries, but the many advantages of these materials come with unique challenges, particularly in inspecting and repairing these structures. Because composites of- ten undergo sub-surface damage mechanisms which compromise the structure without a clear visual indication, inspection of these components is critical to safely deploying composite re- placements to traditionally metallic structures. Impact damage to composites presents one of the most signi fi cant challenges because the area which is vulnerable to impact damage is generally large and sometimes very dif fi cult to access. This work seeks to further evolve iden- ti fi cation technology by developing a system which can detect the impact load location and magnitude in real time, while giving an assessment of the con fi dence in that estimate. Fur- thermore, we identify ways by which impact damage could be more effectively identi fi ed by leveraging impact load identi fi cation information to better characterize damage. The impact load identi fi cation algorithm was applied to a commercial scale wind turbine blade, and results show the capability to detect impact magnitude and location using a single accelerometer, re- gardless of sensor location. A technique for better evaluating the uncertainty of the impact estimates was developed by quantifying how well the impact force estimate meets the assump- tions underlying the force estimation technique. This uncertainty quanti fi cation technique was found to reduce the 95% con fi dence interval by more than a factor of two for impact force estimates showing the least uncertainty, and widening the 95% con fi dence interval by a fac- tor of two for the most uncertain force estimates, avoiding the possibility of understating the uncertainty associated with these estimates. Linear vibration based damage detection tech- niques were investigated in the context of structural stiffness reductions and impact damage. A method by which the sensitivity to damage could be increased for simple structures was presented, and the challenges of applying that technique to a more complex structure were identi fi ed. The structural dynamic changes in a weak adhesive bond were investigated, and the results showed promise for identifying weak bonds that show little or no static reduction in stiffness. To address these challenges in identifying highly localized impact damage, the possi- bility of detecting damage through nonlinear dynamic characteristics was also identi fi ed, with a proposed technique which would leverage impact location estimates to enable the detection of impact damage. This nonlinear damage identi fi cation concept was evaluated on a composite panel with a substructure disbond, and the results showed that the nonlinear dynamics at the damage site could be observed without a baseline healthy reference. By further developing impact load identi fi cation technology and combining load and damage estimation techniques into an integrated solution, the challenges associated with impact detection in composite struc- tures can be effectively solved, thereby reducing costs, improving safety, and enhancing the operational readiness and availability of high value assets.
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A high-affinity anti-cocaine monoclonal antibody, designated h2E2, is entering phase 1 clinical trials for cocaine abuse therapy. To gain insight into the molecular details of its structure that are important for binding cocaine and cocaine metabolites, the Fab fragment was generated and crystallized with and without ligand. Structures of the unliganded Fab and the Fab fragment bound to benzoylecgonine were determined, and were compared with each other and with other crystallized anti-cocaine antibodies. The affinity of the h2E2 antibody for cocaine is 4 nM, while that of the cocaine metabolite benzoylecgonine is 20 nM. Both are higher than the reported affinity for cocaine of the two previously crystallized anti-cocaine antibodies. Consistent with cocaine fluorescent quenching binding studies for the h2E2 mAb, four aromatic residues in the CDR regions of the Fab (TyrL32, TyrL96, TrpL91 and TrpH33) were found to be involved in ligand binding. The aromatic side chains surround and trap the tropane moiety of the ligand in the complex structure, forming significant van der Waals interactions which may account for the higher affinity observed for the h2E2 antibody. A water molecule mediates hydrogen bonding between the antibody and the carbonyl group of the benzoyl ester. Finally, the affinity of binding to h2E2 of benzoylecgonine differs only by a factor of five compared with that of cocaine; therefore, it is suggested that h2E2 would bind cocaine in the same way as observed in the Fab–benzoylecgonine complex, with minor rearrangements of some hypervariable segments of the antibody.
Abscisic acid (ABA) is an essential hormone for plants to survive environmental stresses. At the center of the ABA signaling network is a subfamily of type 2C protein phosphatases (PP2Cs), which form exclusive interactions with ABA receptors and subfamily 2 Snfl-related kinase (SnRK2s). Here, we report a SnRK2-PP2C complex structure, which reveals marked similarity in PP2C recognition by SnRK2 and ABA receptors. In the complex, the kinase activation loop docks into the active site of PP2C, while the conserved ABA-sensing tryptophan of PP2C inserts into the kinase catalytic cleft, thus mimicking receptor-PP2C interactions. These structural results provide a simple mechanism that directly couples ABA binding to SnRK2 kinase activation and highlight a new paradigm of kinase-phosphatase regulation through mutual packing of their catalytic sites.
Two novel quaternary oxyarsenides, Eu 8 Zn 2 As 6 O and Eu 14 Zn 5 As 12 O, were synthesized through metal flux reactions, and their crystal structures were established by single-crystal X-ray diffraction methods. Eu 8 Zn 2 As 6 O crystallizes in the orthorhombic space group Pbca, featuring polyanionic ribbons composed of corner-shared triangular [ZnAs 3 ] units, running along the [100] direction. The structure of Eu 14 Zn 5 As 12 O crystallizes in the monoclinic space group P2/m and its anionic substructure can be described as an infinite “ribbonlike” chain comprised of [ZnAs 3 ] trigonal-planar units, although the structural complexity here is greater and also amplified by disorder on multiple crystallographic positions. In both structures, the O 2– anion occupies an octahedral void with six neighboring Eu 2+ cations. Formal electron counting, electronic structure calculations, and transport properties reveal the charge-balanced semiconducting nature of these heteroanionic Zintl phases. High-temperature thermoelectric transport properties measurements on Eu 14 Zn 5 As 12 O reveal relatively high resistivity (ρ 500K = 8 Ω·cm) and Seebeck coefficient values (S 500K = 220 μV K –1 ), along with a low concentration and mobility of holes as the dominant charge-carriers (n 500K = 8.0 × 10 17 cm –3 , μ 500K = 6.4 cm 2 /V s). Magnetic studies indicate the presence of divalent Eu 2+ species in Eu 14 Zn 5 As 12 O and complex magnetic ordering, with two transitions observed at T 1 = 21.6 K and T 2 = 9 K.
The crystal structure and magnetic properties of Cu 0.6 Mn 2.4 Ge 2 have been re-investigated by a combination of extensive magnetic measurements and neutron scattering experiments, aided by electronic structure calculations. The material is found to be a soft ferromagnet with the ordering temperature T C = 316 K. The magnetocaloric effect evaluated from field-dependent magnetization isotherms is equal to 1.2 J/(kg·K) and 2.5 J/(kg·K) under the maximum applied magnetic field of 2 T and 5 T, respectively. The compound crystallizes in the hexagonal space group P6 3 /mmc. A complex structural disorder necessitated testing of several disorder models against the results of non-polarized and polarized neutron scattering experiments and magnetization measurements. Simulations at the density-functional theory level were also performed to identify the most robust solution that properly described the data observed. The final magnetic structure model reveals non-equal magnetic moments on the Mn1 and Mn2 atoms (2.29(9) µ B and 2.7(1) µ B , respectively) and the presence of vacancies and minor Cu substitution defects in both Mn sites. The work demonstrates how the non-polarized and polarized neutron scattering methods can be combined with electronic structure calculations to establish the microscopic structure of magnetic materials with complex crystallographic disorder.