The oxidative addition of aryl halides to bipyridine- or phenanthroline-ligated nickel(I) is a commonly proposed step in nickel catalysis. However, there is a scarcity of complexes of this type that ...both are well-defined and undergo oxidative addition with aryl halides, hampering organometallic studies of this process. We report the synthesis of a well-defined Ni(I) complex, (CO2Etbpy)NiICl4 (1). Its solution-phase speciation is characterized by a significant population of monomer and a redox equilibrium that can be perturbed by π-acceptors and σ-donors. 1 reacts readily with aryl bromides, and mechanistic studies are consistent with a pathway proceeding through an initial Ni(I) → Ni(III) oxidative addition to form a Ni(III) aryl species. Such a process was demonstrated stoichiometrically for the first time, affording a structurally characterized Ni(III) aryl complex.
We present a 324.5 MHz image of the National Optical Astronomy Observatory Boötes field that was made using Very Large Array P-band observations. The image has a resolution of 5.6 × 5.1 arcsec, a ...radius of 2
$_{.}^{\circ}$
05 and a central noise of ∼0.2 mJy beam−1. Both the resolution and noise of the image are an order of magnitude better than what was previously available at this frequency and will serve as a valuable addition to the already extensive multiwavelength data that are available for this field. The final source catalogue contains 1370 sources and has a median 325–1400 MHz spectral index of −0.72. Using a radio colour–colour diagram of the unresolved sources in our catalogue, we identify 33 megahertz peaked-spectrum (MPS) sources. Based on the turnover frequency linear size relation for the gigahertz peaked-spectrum and compact steep-spectrum sources, we expect that the MPS sources that are compact on scales of tens of milliarcseconds should be young radio loud active galactic nuclei at high (z > 2) redshifts. Of the 33 MPS sources, we were able to determine redshifts for 24, with an average redshift of 1.3. Given that five of the sources are at z > 2, that the four faint sources for which we could not find redshifts are likely at even higher redshifts and that we could only select sources that are compact on a scale of ∼5 arcsec, there is encouraging evidence that the MPS method can be used to search for high-redshift sources.
We previously reported the development of an electron-deficient olefin (EDO) ligand, Fro-DO, that promotes the generation of quaternary carbon centers via Ni-catalyzed Csp3–Csp3 cross-coupling with ...aziridines. By contrast, electronically and structurally similar EDO ligands such as dimethyl fumarate and electron-deficient styrenes afford primarily β-hydride elimination side reactivity. Only a few catalyst systems have been identified that promote the formation of quaternary carbons via Ni-catalyzed Csp3–Csp3 cross-coupling. Although Fro-DO represents a promising ligand in this regard, the basis for its superior performance is not well understood. Here we describe a detailed mechanistic study of the aziridine cross-coupling reaction and the role of EDO ligands in facilitating Csp3–Csp3 bond formation. This analysis reveals that cross-coupling proceeds by a Ni0/II cycle with a NiII azametallacyclobutane catalyst resting state. Turnover-limiting C–C reductive elimination occurs from a spectroscopically observable NiII-dialkyl intermediate bound to the EDO. Computational analysis shows that Fro-DO accelerates turnover limiting reductive elimination via LUMO lowering. However, it is no more effective than dimethyl fumarate at reducing the barrier to Csp3–Csp3 reductive elimination. Instead, Fro-DO’s unique reactivity arises from its ability to associate favorably to NiII intermediates. Natural bond order second-order perturbation theory analysis of the catalytically relevant NiII intermediate indicates that Fro-DO binds to NiII through an additional stabilizing donor–acceptor interaction between its sulfonyl group and NiII. Design of new ligands to evaluate this proposal supports this model and has led to the development of a new and tunable ligand framework.
Abstract
We present a population of 19 radio-luminous supernovae (SNe) with emission reaching
L
ν
∼ 10
26
–10
29
erg s
−1
Hz
−1
in the first epoch of the Very Large Array Sky Survey (VLASS) at 2–4 ...GHz. Our sample includes one long gamma-ray burst, SN 2017iuk/GRB 171205A, and 18 core-collapse SNe detected at ≈1–60 yr after explosion. No thermonuclear explosion shows evidence for bright radio emission, and hydrogen-poor progenitors dominate the subsample of core-collapse events with spectroscopic classification at the time of explosion (79%). We interpret these findings in the context of the expected radio emission from the forward shock interaction with the circumstellar medium (CSM). We conclude that these observations require a departure from the single wind–like density profile (i.e.,
ρ
CSM
∝
r
−2
) that is expected around massive stars and/or from a spherical Newtonian shock. Viable alternatives include the shock interaction with a detached, dense shell of CSM formed by a large effective progenitor mass-loss rate,
M
̇
∼
10
−
4
–
10
−
1
M
⊙
yr
−1
(for an assumed wind velocity of 1000 km s
−1
); emission from an off-axis relativistic jet entering our line of sight; or the emergence of emission from a newly born pulsar-wind nebula. The relativistic SN 2012ap that is detected 5.7 and 8.5 yr after explosion with
L
ν
∼ 10
28
erg s
−1
Hz
−1
might constitute the first detections of an off-axis jet+cocoon system in a massive star. However, none of the VLASS SNe with archival data points are consistent with our model off-axis jet light curves. Future multiwavelength observations will distinguish among these scenarios. Our VLASS source catalogs, which were used to perform the VLASS cross-matching, are publicly available at
https://doi.org/10.5281/zenodo.4895112
.
Context.
Giant radio galaxies (GRGs) are the largest single structures in the Universe. Exhibiting extended radio morphology, their projected sizes range from 0.7 Mpc up to 4.9 Mpc. LOFAR has opened ...a new window on the discovery and investigation of GRGs and, despite the hundreds that are known today, their main growth catalyst is still under debate.
Aims.
One natural explanation for the exceptional size of GRGs is their old age. In this context, hard X-ray selected GRGs show evidence of restarting activity, with the giant radio lobes being mostly disconnected from the nuclear source, if any are present at all. In this paper, we present the serendipitous discovery of a distant (
z
= 0.629), medium X-ray-selected GRG in the Boötes field.
Methods.
High-quality, deep
Chandra
and LOFAR data allow for a robust study of the connection between the nucleus and the lobes, at a larger redshift, which has thus far been inaccessible to coded-mask hard X-ray instruments.
Results.
The radio morphology of the GRG presented in this work does not show evidence for restarted activity and the nuclear radio core spectrum does not appear to be gigahertz-peaked spectrum (GPS)-like. On the other hand, the X-ray properties of the new GRG are perfectly consistent with the ones previously studied with
Swift
/BAT and INTEGRAL at lower redshift. In particular, the bolometric luminosity measured from the X-ray spectrum is a factor of six larger than the one derived from the radio lobes, although the large uncertainties make them formally consistent at 1
σ
. Finally, the moderately dense environment around the GRG, traced by the spatial distribution of galaxies, supports recent findings that the growth of GRGs is not primarily driven by underdense environments.
While the oxidative addition of Ni(I) to aryl iodides has been commonly proposed in catalytic methods, an in-depth mechanistic understanding of this fundamental process is still lacking. Herein, we ...describe a detailed mechanistic study of the oxidative addition process using electroanalytical and statistical modeling techniques. Electroanalytical techniques allowed rapid measurement of the oxidative addition rates for a diverse set of aryl iodide substrates and four classes of catalytically relevant complexes (Ni(MeBPy), Ni(MePhen), Ni(Terpy), and Ni(BPP)). With >200 experimental rate measurements, we were able to identify essential electronic and steric factors impacting the rate of oxidative addition through multivariate linear regression models. This has led to a classification of oxidative addition mechanisms, either through a three-center concerted or halogen-atom abstraction pathway based on the ligand type. A global heat map of predicted oxidative addition rates was created and shown applicable to a better understanding of the reaction outcome in a case study of a Ni-catalyzed coupling reaction.
Organic chemistry is replete with complex relationships: for example, how a reactant’s structure relates to the resulting product formed; how reaction conditions relate to yield; how a catalyst’s ...structure relates to enantioselectivity. Questions like these are at the foundation of understanding reactivity and developing novel and improved reactions. An approach to probing these questions that is both longstanding and contemporary is data-driven modeling. Here, we provide a synopsis of the history of data-driven modeling in organic chemistry and the terms used to describe these endeavors. We include a timeline of the steps that led to its current state. The case studies included highlight how, as a community, we have advanced physical organic chemistry tools with the aid of computers and data to augment the intuition of expert chemists and to facilitate the prediction of structure–activity and structure–property relationships.
The arylation of 2-alkyl aziridines by nucleophilic ring-opening or transition-metal-catalyzed cross-coupling enables facile access to biologically relevant β-phenethylamine derivatives. However, ...both approaches largely favor C–C bond formation at the less-substituted carbon of the aziridine, thus enabling access to only linear products. Consequently, despite the attractive bond disconnection that it poses, the synthesis of branched arylated products from 2-alkyl aziridines has remained inaccessible. Herein, we address this long-standing challenge and report the first branched-selective cross-coupling of 2-alkyl aziridines with aryl iodides. This unique selectivity is enabled by a Ti/Ni dual-catalytic system. We demonstrate the robustness of the method by a twofold approach: an additive screening campaign to probe functional group tolerance and a feature-driven substrate scope to study the effect of the local steric and electronic profile of each coupling partner on reactivity. Furthermore, the diversity of this feature-driven substrate scope enabled the generation of predictive reactivity models that guided mechanistic understanding. Mechanistic studies demonstrated that the branched selectivity arises from a TiIII-induced radical ring-opening of the aziridine.
ABSTRACT Modern high-sensitivity radio telescopes are discovering an increased number of resolved sources with intricate radio structures and fainter radio emissions. These sources often present a ...challenge because source detectors might identify them as separate radio sources rather than components belonging to the same physically connected radio source. Currently, there are no reliable automatic methods to determine which radio components are single radio sources or part of multicomponent sources. We propose a deep-learning classifier to identify those sources that are part of a multicomponent system and require component association on data from the LOFAR Two-Metre Sky Survey. We combine different types of input data using multimodal deep learning to extract spatial and local information about the radio source components: a convolutional neural network component that processes radio images is combined with a neural network component that uses parameters measured from the radio sources and their nearest neighbours. Our model retrieves 94 per cent of the sources with multiple components on a balanced test set with 2683 sources and achieves almost 97 per cent accuracy in the real imbalanced data (323 103 sources). The approach holds potential for integration into pipelines for automatic radio component association and cross-identification. Our work demonstrates how deep learning can be used to integrate different types of data and create an effective solution for managing modern radio surveys.
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