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Iridium Corroles Exhibit Weak Near-Infrared Phosphorescence but Efficiently Sensitize Singlet Oxygen Formation
Six-coordinate iridium(III) triarylcorrole derivatives, Ir[T p XPC)]L 2 , where T p XPC = tris( para -X-phenyl)corrole (X = CF 3 , H, Me, and OCH 3 ) and L = pyridine (py), trimethylamine (tma), isoquinoline (isoq), 4-dimethylaminopyridine (dmap), and 4-picolinic acid (4pa), have been examined, with a view to identifying axial ligands most conducive to near-infrared phosphorescence. Disappointingly, the phosphorescence quantum yield invariably turned out to be very low, about 0.02 – 0.04% at ambient temperature, with about a two-fold increase at 77 K. Phosphorescence decay times were found to be around ~5 µs at 295 K and ~10 µs at 77 K. Fortunately, two of the Ir[T p CF 3 PC)]L 2 derivatives, which were tested for their ability to sensitize singlet oxygen formation, were found to do so efficiently with quantum yields Φ( 1 O 2 ) = 0.71 and 0.38 for L = py and 4pa, respectively. Iridium corroles thus may hold promise as photosensitizers in photodynamic therapy (PDT). The possibility of varying the axial ligand and of attaching biotargeting groups at the axial positions makes iridium corroles particularly exciting as PDT drug candidates.
Collapse of Jahn-Teller phonons in La 1−x Sr x MnO 3 with weak magnetoresistance
Perovskite manganites are quantum materials exhibiting competing interactions inducing colossal magnetoresistance (CMR). The prevailing theory of CMR highlights the essential role of electron-phonon coupling (EPC), but mounting evidence suggests the underlying mechanism is more complicated. Here, we investigate phonons and spin-phonon coupling in ferromagnetic CMR manganites La 1−x Sr x MnO 3 (x=0.2,0.3) with relatively small CMR associated with melting of the magnetic order above room temperature. High-resolution neutron scattering experiments combined with density functional theory (DFT) show that the low-temperature ferromagnetic phase is conventional: neutron scattering from phonons agrees with DFT predictions and magnons follow sinusoidal dispersions. Fluctuating magnetic moments and low-energy phonons remain conventional in the high-temperature paramagnetic phase, indicating the Mn and La/Sr sublattices are not strongly perturbed by melting of ferromagnetism. In contrast, the Jahn–Teller-active optical oxygen vibrations collapse entirely above the Curie temperature, despite low CMR in these compositions, with some of the lost spectral weight reappearing as quasielastic scattering. We attribute this highly anomalous behavior to giant EPC in the charge and/or orbital channel. It drives cooperative diffusive motion of quasistatic carrier-trapping oxygen sublattice distortions once ferromagnetism disappears. We hypothesize the magnitude of magnetoresistance correlates with the rate of diffusion rather than with the strength of Jahn–Teller EPC.
Weak, shallow, dry convection over Angola increases offshore stratocumulus cloud droplet number concentrations
Boundary-layer cloud interactions involving shortwave-absorbing aerosols remain one of the least understood aerosol influences on climate. Here, we find the highest stratocumulus cloud droplet number concentrations over the southeast Atlantic occur when agricultural fires coincide with synoptically-weakened surface warming over Angola, occurring June-early August. Dry convection fills a shallow continental boundary layer with smoke, and a nighttime (local solar time 2-9) land breeze transports the aerosol into the marine boundary layer. Offshore aerosol transport is strengthened by low-level easterlies from a continental pressure high southeast of Angola. Simultaneously, the South Atlantic subtropical high is weaker, allowing extensive dispersal of aerosol offshore into the boundary layer, obscuring cloud brightening from shipping. Meteorological co-variation at synoptic scales compensates for cloud brightening by the smoke. Outgoing shortwave radiation increases by 15–20% of the monthly mean in June and July when offshore droplet numbers are less but the stratocumulus deck is more developed.
Directed polymorphism and mechanofluorochromism of conjugated materials through weak non-covalent control
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Understanding the thermally activated charge transport in NaPb m SbQ m+2 (Q = S, Se, Te) thermoelectrics: weak dielectric screening leads to grain boundary dominated charge carrier scattering
Many thermoelectric materials feature irregular electrical conductivity with thermally activated transport below ~600 K and metallic behavior at high temperatures, despite possessing degenerate carrier concentrations. The suppression of the electrical conductivity ultimately degrades the thermoelectric performance on the cold side and limits the device energy conversion efficiency. As such, establishing the origin of the low temperature scattering and developing strategies to mitigate its effect are paramount issues. To date, the correct microscopic description of the low temperature carrier scattering remains an open issue, and there is little work addressing why some thermoelectric materials are more susceptible to the deleterious behavior. Here, we use the promising thermoelectric alloys of PbQ and NaSbQ 2 (Q = S, Se, Te) as model systems to address these concerns. We directly show the thermally activated transport stems from the scattering of charge carriers by the grain boundaries (GBs), and that the expected metallic electrical conductivity is recovered by preparing large grained samples with reduced densities of GBs. We furthermore study the electrical properties NaPb m SbSe m+2 as a function of NaSbSe 2 fraction, as well as those of the chalcogenide analogues, PbTe–NaSbTe 2 and PbS–NaSbS 2 , and demonstrate that the strength of GB scattering can be understood by utilizing simple chemical principles. By considering the polarizability of the host atoms, we directly relate the magnitude of GB scattering to the relative degree of charge carrier screening in each material, and demonstrate that GB scattering is strongest in the ionic NaSbQ 2 -rich compounds and weakest in more polarizable PbQ-rich phases. We finally show how these chemical arguments elegantly explain the strong GB scattering in numerous other thermoelectric materials. By uniting the deleterious charge transport properties exhibited by many different compounds into a common picture, we discuss how our work gives design principles for proper microstructure engineering in emerging thermoelectric materials.
Potent strategy towards strongly emissive nitroaromatics through a weakly electron-deficient core
Nitroaromatics seldom fluoresce. The importance of electron-deficient (n-type) conjugates, however, has inspired a number of strategies for suppressing the emission-quenching effects of the strongly electron-withdrawing nitro group. Here, we demonstrate how such strategies yield fluorescent nitroaryl derivatives of dipyrrolonaphthyridinedione (DPND). Nitro groups near the DPND core quench its fluorescence. Conversely, nitro groups placed farther from the core allow some of the highest fluorescence quantum yields ever recorded for nitroaromatics. This strategy of preventing the known processes that compete with photoemission, however, leads to the emergence of unprecedented alternative mechanisms for fluorescence quenching, involving transitions to dark nπ* singlet states and aborted photochemistry. Forming nπ* triplet states from ππ* singlets is a classical pathway for fluorescence quenching. In nitro-DPNDs, however, these ππ* and nπ* excited states are both singlets, and they are common for nitroaryl conjugates. Understanding the excited-state dynamics of such nitroaromatics is crucial for designing strongly fluorescent electron-deficient conjugates.
Nanoribbons or weakly connected acenes? The influence of pyrene insertion on linearly extended ring systems
Derived from the lateral fusion of benzene rings, acenes are a class of π-conjugated molecules containing a single aromatic sextet, where system size is inversely correlated with chemical stability. In the pursuit of creating graphene nanoribbons/nanowires, several extended-ring structures have been synthesized through linear combinations of azaacenes and pyrene. Importantly, these extended systems demonstrate enhanced chemical stability and allow for the construction of macromolecular-sized structures. In this report we present a combined quantum-chemical and experimental study to reveal the cost of these improved characteristics in fully carbon-based systems. The results clearly show that pyrene moieties inserted among acene units do not result in long acene-like structures, rather the pyrene-inserted acene is, electronically, a series of (nearly) isolated acenes. The origin of pyrene's electronic blocking effect and implications on oxidized and photoexcited states of these extended-ring systems are detailed. The results of this investigation definitively show that coupling pyrene in an orthogonal orientation (through the 4, 5/9, 10 positions or e/l faces) to acenes should be eschewed if nanographene-/nanowire-like structures are desired.
Nonlinear Hugoniot for Idealized Composites under Weak Shock Compression
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Potential vorticity transport in weakly and strongly magnetized plasmas
Tangled magnetic fields, often coexisting with an ordered mean field, have a major impact on turbulence and momentum transport in many plasmas, including those found in the solar tachocline and magnetic confinement devices. We present a novel mean field theory of potential vorticity mixing in β-plane magnetohydrodynamic (MHD) and drift wave turbulence. Our results show that mean square stochastic fields strongly reduce Reynolds stress coherence. This decoherence of potential vorticity flux due to stochastic field scattering leads to suppression of momentum transport and zonal flow formation. A simple calculation suggests that the breaking of the shear-eddy tilting feedback loop by stochastic fields is the key underlying physics mechanism. Furthermore, a dimensionless parameter that quantifies the increment in power threshold is identified and used to assess the impact of stochastic field on the L-H transition. We discuss a model of stochastic fields as a resisto-elastic network.
Strong-Weak Duality via Jordan-Wigner Transformation: Using Fermionic Methods for Strongly Correlated su(2) Spin Systems
The Jordan-Wigner transformation establishes a duality between $su(2)$ and fermionic algebras. We present qualitative arguments and numerical evidence that when mapping spins to fermions, the transformation makes strong correlation weaker, as demonstrated by the Hartree-Fock approximation to the transformed Hamiltonian. This result can be rationalized in terms of rank reduction of spin shift terms when transformed to fermions. Conversely, the mapping of fermions to qubits makes strong correlation stronger, complicating its solution when one uses qubit-based correlators. The presence of string operators poses challenges to the implementation of quantum chemistry methods on classical computers, but these can be dealt with using established techniques of low computational cost. Here, our proof of principle results for XXZ and J1-J2 Heisenberg (in 1D and 2D) indicate that the JW transformed fermionic Hamiltonian has reduced complexity in key regions of their phase diagrams, and provides a better starting point for addressing challenging spin problems.
Evolution of coupled weakly driven waves in a dissipative plasma
The nonlinear collisional dynamics of coupled driven plasma waves in the presence of background dissipation is studied analytically within kinetic theory. Sufficiently near marginal stability, phase space correlations are poorly preserved and time delays become unimportant. The system is then shown to be governed by two first-order coupled autonomous differential equations of cubic order for the wave amplitudes and two complementary first-order equations for the evolution of their phases. That system of equations can be decoupled and further simplified to a single second-order differential equation of Liénard's type for each amplitude. Numerical solutions for this equation are obtained in the general case, while analytic solutions are obtained for special cases in terms of parameters related to the spacing of the resonances of the two waves in frequency space, e.g., wave lengths and oscillation frequencies. These parameters are further analyzed to find classes of quasi-steady saturation and pulsating scenarios. To classify equilibrium points, local stability analysis is applied, and bifurcation conditions are determined. When the two waves saturate at similar amplitude levels, their combined signal is shown to invariably exhibit amplitude beating and phase jumps of nearly π. In conclusion, the obtained analytical results can be used to benchmark simulations and to interpret eigenmode amplitude measurements in fusion experiments.
Mesoscale simulation of granular materials under weak shock compaction–pore size distribution effects
This research established a systematic method to generate various pore-size distributions (PSDs) and studied the effect of PSDs on the shock compaction response of granular materials using two-dimensional mesoscale simulations under identical porosity. Simulations utilized various PSDs for three particle shapes (circle, ellipse, and square). Contacting particle configurations using three PSDs, characterized by spatially uniform distributed pores to heterogeneous distributed pores, and non-contacting particle configurations under a single case of PSD were tested. The PSD of generated particle sets was characterized using coordination number, mean diameter, and bimodality coefficient as statistical metrics. Mesoscale simulations showed that regardless of the conditions of pore distributions, shock compaction of granular materials consistently demonstrates a precursor, shock compaction front, and end. However, the shock compaction velocity of contacting particles was dependent on the PSDs despite the constant initial porosity. The compaction velocity was faster in particle configurations with relatively uniform pore distributions than in heterogeneous pore distributions, which our study demonstrated can be attributed to particle rearrangement during compaction. Circular-shaped particles had high sensitivity in shock compaction response to the various PSDs. Furthermore, a contacting particle configuration tended to propagate the shock compaction wave relatively faster than particles that were in a non-contact configuration. This study established the relative importance of considering PSD as a metric over the coordination number in studies of the shock compaction response of granular materials. Further, insights are provided on the evolving shock substructure to characterize the shock compaction response of granular materials.
Identifying strengths and weaknesses of methods for computational network inference from single-cell RNA-seq data
Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional programs of different cellular states by measuring the transcriptome of thousands of individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regulatory networks and a number of methods with different learning frameworks have been developed to address this problem. Here, we present an expanded benchmarking study of eleven recent network inference methods on seven published scRNA-seq datasets in human, mouse, and yeast considering different types of gold standard networks and evaluation metrics. We evaluate methods based on their computing requirements as well as on their ability to recover the network structure. We find that, while most methods have a modest recovery of experimentally derived interactions based on global metrics such as Area Under the Precision Recall curve, methods are able to capture targets of regulators that are relevant to the system under study. Among the top performing methods that use only expression were SCENIC, PIDC, MERLIN or Correlation. Addition of prior biological knowledge and the estimation of transcription factor activities resulted in the best overall performance with the Inferelator and MERLIN methods that use prior knowledge outperforming methods that use expression alone. We found that imputation for network inference did not improve network inference accuracy and could be detrimental. Comparisons of inferred networks for comparable bulk conditions showed that the networks inferred from scRNA-seq datasets are often better or at par with the networks inferred from bulk datasets. Our analysis should be beneficial in selecting methods for network inference. At the same time, this highlights the need for improved methods and better gold standards for regulatory network inference from scRNAseq datasets.
Shape, colour, and distance in weak gravitational flexion
ABSTRACT Canonically, elliptical galaxies might be expected to have a perfect rotational symmetry, making them ideal targets for flexion studies – however, this assumption has not been tested. We have undertaken an analysis of low- and high-redshift galaxy catalogues of known morphological type with a new gravitational lensing code, Lenser. Using colour measurements in the u − r bands and fit Sérsic index values, objects with characteristics consistent with early-type galaxies are found to have a lower intrinsic scatter in flexion signal than late-type galaxies. We find this measured flexion noise can be reduced by more than a factor of two at both low and high redshift.
Projecting the likely importance of weak-interaction-driven bulk viscosity in neutron star mergers
ABSTRACT In this work, we estimate how much bulk viscosity driven by Urca processes is likely to affect the gravitational wave signal of a neutron star coalescence. In the late inspiral, we show that bulk viscosity affects the binding energy at fourth post-Newtonian order. Even though this effect is enhanced by the square of the gravitational compactness, the coefficient of bulk viscosity is likely too small to lead to observable effects in the waveform during the late inspiral, when only considering the orbital motion itself. In the post-merger, however, the characteristic time-scales and spatial scales are different, potentially leading to the opposite conclusion. We post-process data from a state-of-the-art equal-mass binary neutron star merger simulation to estimate the effects of bulk viscosity (which was not included in the simulation itself). In that scenario, we find that bulk viscosity can reach high values in regions of the merger. We compute several estimates of how much it might directly affect the global dynamics of the considered merger scenario, and find that it could become significant. Even larger effects could arise in different merger scenarios or in simulations that include non-linear effects. This assessment is reinforced by a quantitative comparison with relativistic heavy-ion collisions where such effects have been explored extensively.
Accelerating cosmological inference with Gaussian processes and neural networks – an application to LSST Y1 weak lensing and galaxy clustering
ABSTRACT Studying the impact of systematic effects, optimizing survey strategies, assessing tensions between different probes and exploring synergies of different data sets require a large number of simulated likelihood analyses, each of which cost thousands of CPU hours. In this paper, we present a method to accelerate cosmological inference using emulators based on Gaussian process regression and neural networks. We iteratively acquire training samples in regions of high posterior probability which enables accurate emulation of data vectors even in high dimensional parameter spaces. We showcase the performance of our emulator with a simulated 3×2 point analysis of LSST-Y1 with realistic theoretical and systematics modelling. We show that our emulator leads to high-fidelity posterior contours, with an order of magnitude speed-up. Most importantly, the trained emulator can be re-used for extremely fast impact and optimization studies. We demonstrate this feature by studying baryonic physics effects in LSST-Y1 3×2 point analyses where each one of our MCMC runs takes approximately 5 min. This technique enables future cosmological analyses to map out the science return as a function of analysis choices and survey strategy.