Enhancing Metal Separations by Liquid–Liquid Extraction Using Polar Solvents

The less polar phase of liquid–liquid extraction systems has been studied extensively for improving metal separations; however, the role of the more polar phase has been overlooked for far too long. Herein, we investigate the extraction of metals from a variety of polar solvents and demonstrate that, the influence of polar solvents on metal extraction is so significant that extraction of many metals can be largely tuned, and the metal separations can be significantly enhanced by selecting suitable polar solvents. Furthermore, a mechanism on how the polar solvents affect metal extraction is proposed based on comprehensive characterizations. The method of using suitable polar solvents in liquid–liquid extraction paves a new and versatile way to enhance metal separations.     

High current density electrodeposition from silver complex ionic liquids

Liquid metal salts are electrolytes with the highest possible metal concentration for electrodeposition, because the metal ion is an integral part of the solvent. This paper introduces the new ionic silver complexes [Ag(MeCN)(4)](2)[Ag(Tf(2)N)(3)], [Ag(MeCN)][Tf(2)N] and [Ag(EtIm)(2)][Tf(2)N], where MeCN stands for acetonitrile, EtIm for 1-ethylimidazole and Tf(2)N is bis(trifluoromethylsulfonyl)imide. These complexes have been characterized by differential scanning calorimetry, single crystal X-ray crystallography, thermogravimetrical analysis, Raman spectroscopy and cyclic voltammetry. [Ag(MeCN)(4)](2)[Ag(Tf(2)N)(3)] is a room temperature ionic liquid. Smooth silver layers of good quality could be deposited from it, at current densities of up to 25 A dm(-2) in unstirred solutions. [Ag(EtIm)(2)][Tf(2)N] melts at 65 °C and can be used as an electrolyte for silver deposition above this temperature. [Ag(MeCN)][Tf(2)N] has a melting point that is too high to be useful in electrodeposition. Addition of thiourea or 1H-benzotriazole to the electrolyte decreased the surface roughness of the silver coatings. The morphology of the metal layers was investigated by atomic force microscopy (AFM). Adsorption of 1H-benzotriazole on the silver metal surface has been proven by Raman spectroscopy. This work shows the usefulness of additives in improving the quality of metal films electrodeposited from ionic liquids.     

Diastereoselective aldol reaction of zincated 3-chloro-3-methyl-1-azaallylic anions as key step in the synthesis of 1,2,3,4-tetrasubstituted 3-chloroazetidines

Zincated 3-chloro-3-methyl-1-azaallylic anions undergo a stereoselective aldol addition across aromatic aldehydes and subsequent mesylation to produce syn α-chloro-β-mesyloxyketimines, which were isolated in 80-84% yield and high diastereomeric excess (dr > 97/3) after purification via flash chromatography. The syn α-chloro-β-mesyloxyketimines were further stereoselectively reduced to give stereochemically defined 3-aminopropyl mesylates, which were cyclized to 1,2,3,4-tetrasubstituted 3-chloroazetidines containing three contiguous stereogenic centers. DFT calculations on the key aldol addition revealed the presence of a highly ordered bimetallic six-membered twist-boat-like transition state structure with a tetra-coordinated metal cyclic structure. DFT calculations revealed that chelation of both zinc and lithium cations in the transition state structure leads to the experimentally observed high syn diastereoselectivity of aldol reactions.     

Controlling the gelation temperature of biomimetic polyisocyanides

The gelation temperature and mechanical properties of aqueous ethylene glycol-decorated polyisocyanide solutions strongly depends on the length of the glycol tail. Copolymerisation of monomers with different tail lengths allows for precise engineering of the gel properties.     

Enhancement of Nonlinear Optical Scattering by Gold Nanoparticles through Aggregation-Induced Plasmon Coupling in the Near-Infrared

Gold nanoparticles (AuNPs) are regarded as promising building blocks in functional nanomaterials for sensing, drug delivery and catalysis. One remarkable property of these particles is the localized surface plasmon resonance (LSPR), which gives rise to augmented optical properties through local field enhancement. LSPR also influences the nonlinear optical properties of metal NPs (MNPs) making them potentially interesting candidates for fast, high resolution nonlinear optical imaging. In this work we characterize and discuss the wavelength dependence of the hyper-Rayleigh scattering (HRS) behavior of spherical gold nanoparticles (GNP) and gold nanorods (GNR) in solution, from 850 nm up to 1300 nm, covering the near-infrared (NIR) window relevant for deep tissue imaging. The high-resolution spectral data allows discriminating between HRS and two photon photoluminescence contributions. Upon particle aggregation, we measured very large enhancements (ca. 10⁴) of the HRS intensity in the NIR, which is explained by considering aggregation-induced plasmon coupling effects and local field enhancement. These results indicate that purposely designed coupled nanostructures could prove advantageous for nonlinear optical imaging and biosensing applications.     

Evidence from current-density mapping for σ-delocalisation in the aromatic hexaiodobenzene cation

Calculation of high σ-delocalisation in the iodine periphery of the hexaiodobenzene cation, accompanied by a four-electron through-space σ ring current, provides direct computational evidence for the attribution to this ion of σ-aromaticity co-existing with the conventional π-aromaticity that it shares with its neutral parent.     

A facile strategy to prevent trifluoroacetylation of N-terminal proline peptides

Unwanted trifluoroacetylation occurred at the N-terminus of prolinyl peptides during detachment from the solid phase. This was observed when the N-α-Fmoc protecting group had been removed prior to the final TFA treatment. Subtly changing the SPPS protocol and incorporating Boc- in place of the Fmoc-protected proline as the N-terminal building block efficiently suppressed this side reaction.     

Computationally efficient evaluation of appointment schedules in health care

We consider the problem of evaluating and constructing appointment schedules for patients in a health care facility where a single physician treats patients in a consecutive manner, as is common for general practitioners, clinics and for outpatients in hospitals. Specifically, given a fixed-length session during which a physician sees K patients, each patient has to be given an appointment time during this session in advance. Optimising a schedule with respect to patient waiting times, physician idle times, session overtime, etc. usually requires a heuristic search method involving a huge number of repeated schedule evaluations. Hence, our aim is to obtain accurate predictions at very low computational cost. This is achieved by (1) using Lindley’s recursion to allow for explicit expressions and (2) choosing a discrete-time (slotted) setting to make those expressions easy to compute. We assume general, possibly distinct, distributions for the patients’ consultation times, which allows to account for multiple treatment types, emergencies and patient no-shows. The moments of waiting and idle times are obtained and the computational complexity of the algorithm is discussed. Additionally, we calculate the schedule’s performance in between appointments in order to assist a sequential scheduling strategy.     

Conservative independence-based causal structure learning in absence of adjacency faithfulness

This paper presents an extension to the Conservative PC algorithm which is able to detect violations of adjacency faithfulness under causal sufficiency and triangle faithfulness. Violations can be characterized by pseudo-independent relations and equivalent edges, both generating a pattern of conditional independencies that cannot be modeled faithfully. Both cases lead to uncertainty about specific parts of the skeleton of the causal graph. These ambiguities are modeled by an f-pattern. We prove that our Adjacency Conservative PC algorithm is able to correctly learn the f-pattern. We argue that the solution also applies for the finite sample case if we accept that only strong edges can be identified. Experiments based on simulations and the ALARM benchmark model show that the rate of false edge removals is significantly reduced, at the expense of uncertainty on the skeleton and a higher sensitivity for accidental correlations.