Energy Sciences

Luminescent metal-organic frameworks (LMOFs) with diverse structural features and promising fluorescence-based applications have attracted wide attention in the past two decades. In this work, a LMOF with the formula [Ca₄(tcbpe-F)₂(H₂O)₃] (1, LMOF-411) has been constructed from calcium (Ca) and 1,1,2,2-tetrakis(4-(4-carboxyphenyl)phenyl)ethene (H₄tcbpe-F). Compound 1 features a three-dimensional framework with a 10-nodal net topology. Due to the relatively high hydration energy of Ca²⁺, compound 1 readily transforms into a new phase formulated as [Ca(H₂tcbpe-F)(H₂O)₂] (1') upon exposure to water. Combining experimental characterization and theoretical calculations, we elucidated the mechanism of H₂O-induced phase transition from 1 to 1'. Notably, the water induced phase transformation can be detected visibly from the change in luminescence, which originates from the fluorescent linker. Compound 1 emits green light (λ _em = 490 nm) under UV excitation, while compound 1' emits bright yellow light (λ _em = 550 nm) under blue excitation (450 nm). Compound 1' represents the first Ca based LMOF yellow phosphor and its luminescence quantum yield reaches 68%. It can be coated directly onto a commercial blue light-emitting-diode (LED) chip to fabricate a white LED (WLED).

Background: The unfolded protein response (UPR) controls the protein folding capacity of the endoplasmic reticulum (ER). Central to this signaling pathway is the ER-resident bifunctional transmembrane kinase/endoribonuclease Ire1. The endoribonuclease (RNase) domain of Ire1 initiates a non-conventional mRNA splicing reaction, leading to the production of a transcription factor that controls UPR target genes. The mRNA splicing reaction is an obligatory step of Ire1 signaling, yet its mechanism has remained poorly understood due to the absence of substrate-bound crystal structures of Ire1, the lack of structural similarity between Ire1 and other RNases, and a scarcity of quantitative enzymological data. Here, we experimentally define the active site of Ire1 RNase and quantitatively evaluate the contribution of the key active site residues to catalysis.Results: This analysis and two new crystal structures suggest that Ire1 RNase uses histidine H1061 and tyrosine Y1043 as the general acid-general base pair contributing ≥ 7.6 kcal/mol and 1.4 kcal/mol to transition state stabilization, respectively, and asparagine N1057 and arginine R1056 for coordination of the scissile phosphate. Investigation of the stem-loop recognition revealed that additionally to the stem-loops derived from the classic Ire1 substrates HAC1 and Xbp1 mRNA, Ire1 can site-specifically and rapidly cleave anticodon stem-loop (ASL) of unmodified tRNAPhe, extending known substrate specificity of Ire1 RNase.Conclusions: Our data define the catalytic center of Ire1 RNase and suggest a mechanism of RNA cleavage: each RNase monomer apparently contains a separate catalytic apparatus for RNA cleavage, whereas two RNase subunits contribute to RNA stem-loop docking. Conservation of the key residues among Ire1 homologues suggests that the mechanism elucidated here for yeast Ire1 applies to Ire1 in metazoan cells, and to the only known Ire1 homologue RNase L. © 2011 Korennykh et al; licensee BioMed Central Ltd.

Structural versatility and multifunctionality of biological materials have resulted in countless bioinspired strategies seeking to emulate the properties of nature. The nanostructured egg case of swell sharks is one of the toughest permeable membranes known and, thus, presents itself as a model system for materials where the conflicting properties, strength and porosity, are desirable. The egg case possesses an intricately ordered structure that is designed to protect delicate embryos from the external environment while enabling respiratory and metabolic exchange, achieving a tactical balance between conflicting properties. Herein, structural analyses revealed an enabling nanolattice architecture that constitutes a Bouligand-like nanoribbon hierarchical assembly. Three distinct hierarchical architectural adaptations enhance egg case survival: Bouligand-like organization for in-plane isotropic reinforcement, noncylindrical nanoribbons maximizing interfacial stress distribution, and highly ordered nanolattices enabling permeability and lattice-governed toughening mechanisms. These discoveries provide fundamental insights for the improvement of multifunctional membranes, fiber-reinforced soft composites, and mechanical metamaterials.

Molecular dynamics simulations of intrinsically disordered proteins (IDPs) can provide high resolution structural ensembles if the force field is accurate enough and if the simulation sufficiently samples the conformational space of the IDP with the correct weighting of sub-populations. Here, we investigate the combined force field-sampling problem by testing a standard force field as well as newer fixed charge force fields, the latter specifically motivated for better description of unfolded states and IDPs, and comparing them with a standard temperature replica exchange (TREx) protocol and a non-equilibrium Temperature Cool Walking (TCW) sampling algorithm. The force field and sampling combinations are used to characterize the structural ensembles of the amyloid-beta peptides Aβ42 and Aβ43, which both should be random coils as shown recently by experimental nuclear magnetic resonance (NMR) and 2D Förster resonance energy transfer (FRET) experiments. The results illustrate the key importance of the sampling algorithm: while the standard force field using TREx is in poor agreement with the NMR J-coupling and nuclear Overhauser effect and 2D FRET data, when using the TCW method, the standard and optimized protein-water force field combinations are in very good agreement with the same experimental data since the TCW sampling method produces qualitatively different ensembles than TREx. We also discuss the relative merit of the 2D FRET data when validating structural ensembles using the different force fields and sampling protocols investigated in this work for small IDPs such as the Aβ42 and Aβ43 peptides.

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time evolved expansion states, and connects the method to the classical filter diagonalization algorithm. Further, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise which substantially improves previous considerations. The unitary formulation allows for a direct comparison to iterative phase estimation. Our results mark VQPE as both a natural and highly efficient quantum algorithm for ground and excited state calculations of general many-body systems. We demonstrate a hardware implementation of VQPE for the transverse field Ising model. Further, we illustrate its power on a paradigmatic example of strong correlation (Cr2 in the SVP basis set), and show that it is possible to reach chemical accuracy with as few as ~50 timesteps.

Glassy polymers are often used for gas separations because of their high selectivity. Although the dual-mode permeation model correctly fits their sorption and permeation isotherms, its physical interpretation is disputed, and it does not describe permeation far from steady state, a condition expected when separations involve intermittent renewable energy sources. To develop a more comprehensive permeation model, we combine experiment, molecular dynamics, and multiscale reaction–diffusion modeling to characterize the time-dependent permeation of N2 and CO2 through a glassy poly(dimethyl phenylene oxide) membrane, a model system. Simulations of experimental time-dependent permeation data for both gases in the presteady-state and steady-state regimes show that both single- and dual-mode reaction–diffusion models reproduce the experimental observations, and that sorbed gas concentrations lag the external pressure rise. The results point to environment-sensitive diffusion coefficients as a vital characteristic of transport in glassy polymers.

Ca-ion electrochemical systems have been pushed to the forefront of recent multivalent energy storage advances due to their use of earth-abundant redox materials and their high theoretical specific densities in relation to monovalent or even other more widely explored multivalent-charge carriers. However, significant pitfalls in metal plating and stripping arise from electrolyte decomposition and can be related to the coordination environment around Ca2+ with both the negatively charged anion and the organic-aprotic solvent. In this study, we apply multiple spectroscopic techniques in conjunction with density functional theory to evaluate the coordination environment of Ca2+ across a class of ethereal solvents. Through the combination of X-ray absorption fine structure and time-dependent density functional theory, descriptive measures of the local geometry, coordination, and electronic structure of Ca-ethereal complexes provide distinct structural trends depending on the extent of the Ca2+-solvent interaction. Finally, we correlate these findings with electrochemical measurements of calcium tetrakis(hexafluoroisopropoxy)borate (CaBHFIP2) salts dissolved within this class of solvents to provide insight into the preferred structural configuration of Ca2+ electrolytic solutions for optimized electrochemical plating and stripping.

The discovery of intrinsic magnetic topological order in MnBi₂Te₄ has invigorated the search for materials with coexisting magnetic and topological phases. These multiorder quantum materials are expected to exhibit new topological phases that can be tuned with magnetic fields, but the search for such materials is stymied by difficulties in predicting magnetic structure and stability. Here, we compute more than 27,000 unique magnetic orderings for more than 3000 transition metal oxides in the Materials Project database to determine their magnetic ground states and estimate their effective exchange parameters and critical temperatures. We perform a high-throughput band topology analysis of centrosymmetric magnetic materials, calculate topological invariants, and identify 18 new candidate ferromagnetic topological semimetals, axion insulators, and antiferromagnetic topological insulators. To accelerate future efforts, machine learning classifiers are trained to predict both magnetic ground states and magnetic topological order without requiring first-principles calculations.

New ideas for low-mass dark matter direct detection suggest that narrow band gap materials, such as Dirac semiconductors, are sensitive to the absorption of meV dark matter or the scattering of keV dark matter. Here we propose spin-orbit semiconductors - materials whose band gap arises due to spin-orbit coupling - as low-mass dark matter targets owing to their O(10 meV) band gaps. We present three material families that are predicted to be spin-orbit semiconductors using density functional theory (DFT), assess their electronic and topological features, and evaluate their use as low-mass dark matter targets. In particular, we find that the tin pnictide compounds are especially suitable having a tunable range of meV-scale band gaps with anisotropic Fermi velocities allowing directional detection. Finally, we address the pitfalls in the DFT methods that must be considered in the ab initio prediction of narrow-gapped materials, including those close to the topological critical point.

We propose the use of three-dimensional Dirac materials as targets for direct detection of sub-MeV dark matter. Dirac materials are characterized by a linear dispersion for low-energy electronic excitations, with a small band gap of O(meV) if lattice symmetries are broken. Dark matter at the keV scale carrying kinetic energy as small as a few meV can scatter and excite an electron across the gap. Alternatively, bosonic dark matter as light as a few meV can be absorbed by the electrons in the target. We develop the formalism for dark matter scattering and absorption in Dirac materials and calculate the experimental reach of these target materials. We find that Dirac materials can play a crucial role in detecting dark matter in the keV to MeV mass range that scatters with electrons via a kinetically mixed dark photon, as the dark photon does not develop an in-medium effective mass. The same target materials provide excellent sensitivity to absorption of light bosonic dark matter in the meV to hundreds of meV mass range, superior to all other existing proposals when the dark matter is a kinetically mixed dark photon.

A single-molecule three-dimensional (3D) structure is essential for understanding the thermal vibrations and dynamics as well as the conformational changes during the chemical reaction of macromolecules. Individual-particle electron tomography (IPET) is an approach for obtaining a snap-shot 3D structure of an individual macromolecule particle by aligning the tilt series of electron tomographic (ET) images of a targeted particle through a focused iterative 3D reconstruction method. The method can reduce the influence on the 3D reconstruction from large-scale image distortion and deformation. Due to the mechanical tilt limitation, 3D reconstruction often contains missing-wedge artifacts, presented as elongation and an anisotropic resolution. Here, we report a post-processing method to correct the missing-wedge artifact. This low-tilt tomographic reconstruction (LoTToR) method contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination.

We report the design and synthesis of an imine-based two-dimensional covalent organic framework (2D COF) with a novel brick-wall topology by judiciously choosing a tritopic T-shaped building block and a ditopic linear linker. Unlike the main body of COF frameworks reported to-date, which consists of higher-symmetry 2D topologies, the unconventional layered brick-wall topology have only been proposed but never been realized experimentally. The brick-wall structure was characterized by powder X-ray diffraction analysis, FT-IR, solid state ¹³C NMR spectroscopy, nitrogen, and carbon oxide adsorption-desorption measurements as well as theoretical simulations. Our present work opens the door to the design of novel 2D COFs and will broaden the scope of emerging COF materials.

Transmission electron microscopy (TEM) is a potent technique for the determination of three-dimensional atomic scale structure of samples in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined using phase-contrast single-particle cryo-electron microscopy from thousands of identical proteins, and reconstructions have reached atomic resolution for specific proteins. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using a combination of annular dark field (ADF) scanning transmission electron microscopic (STEM) tomography and subpixel localization of atomic peaks, in a method termed atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform mixed-state electron ptychography from 34.5 million diffraction patterns to reconstruct a high-resolution tilt series of a double wall-carbon nanotube (DW-CNT), encapsulating a complex $\mathrm{ZrTe}$ sandwich structure. Class averaging of the resulting reconstructions and subpixel localization of the atomic peaks in the reconstructed volume reveals the complex three-dimensional atomic structure of the core-shell heterostructure with 17 picometer precision. From these measurements, we solve the full $\mathrm{Zr_{11}Te_{50}}$ structure, which contains a previously unobserved $\mathrm{ZrTe_{2}}$ phase in the core. The experimental realization of ptychographic atomic electron tomography (PAET) will allow for structural determination of a wide range of nanomaterials which are beam-sensitive or contain light elements.