Variable control of the electronic states of a silver nanocluster via protonation/deprotonation of polyoxometalate ligands

The properties of metal nanoclusters depend on both their structures and electronic states. However, in contrast to the significant advances achieved in the synthesis of structurally well-defined metal nanoclusters, systematic control of their electronic states is still challenging. In particular, stimuli-responsive and reversible control of the electronic states of metal nanoclusters is attractive from the viewpoint of their practical applications. Recently, we developed a synthesis method for atomically precise Ag nanoclusters using polyoxometalates (POMs) as inorganic ligands. Herein, we exploited the acid/base nature of POMs to reversibly change the electronic states of an atomically precise {Ag₂₇} nanocluster via protonation/deprotonation of the surrounding POM ligands. We succeeded in systematically controlling the electronic states of the {Ag₂₇} nanocluster by adding an acid or a base (0–6 equivalents), which was accompanied by drastic changes in the ultraviolet-visible absorption spectra of the nanocluster solutions. These results demonstrate the great potential of Ag nanoclusters for unprecedented applications in various fields such as sensing, biolabeling, electronics, and catalysis.

The electronic states of Ag nanoclusters were reversibly controlled driven by protonation/deprotonation of polyoxometalate ligands.     

Polymer Distribution Change During Irreversible Depolymerization by Chain‐End Scission

The change in polymer distribution during depolymerization in which monomer molecules are severed one by one from the chain ends, is considered. Assuming irreversible depolymerization and equal reactivity of all the chain ends, a general formula to calculate the MWD is proposed. After the removal of monomers severed from the chains, the MWDs of depolymerized polymers always approach the most probable distribution whose PDI is practically equal to 2. It may appear to be counterintuitive, but the average MWs of polymers may increase during chain scission when the initial distribution is broader than the most probable (PDI > 2). The interpretation of the MWD data of polymers during depolymerization, such as those obtained by GPC, are not straightforward especially for the initial broad MWDs.

     

One‐step preparation of some 2‐isopropenyl‐2,3‐dihydronaphtho‐[2,3‐b]furan‐4,9‐diones

Some 2‐isopropenyl‐2,3‐dihydronaphtho[2,3‐b]furan‐4,9‐diones la‐f,b',f were prepared by one‐step cyclizations of 2‐hydroxy‐1,4‐naphthoquinones 2a‐f with 1,4‐dibromo‐2‐methyl‐2‐butene ( 3 ).     

Analytical calculus and Monte Carlo simulation of crosslinked polymer formation in the copolymerization of tetraethoxysilane and poly(dimethylsiloxane)

To understand the fundamental aspects of the polycondensation reaction of hydrolyzed tetraethoxysilane (TEOS) and silanol‐terminated poly(dimethylsiloxane) (PDMS), we modeled the reaction system as a step‐growth polymerization of A₄ and polydisperse A₂, assuming the reactivities of all functional groups are equal. The analytical solution for the weight‐average molecular weight is developed, and in addition, a Monte Carlo simulation is conducted to investigate the detailed structural development. It was found that as long as the molecular weight of PDMS is much larger than TEOS, the apparent behavior is significantly different from usual gelling systems. The gel point is relatively insensitive to the weight fraction of crosslinker (TEOS), the polydispersity index may decrease during polymerization before the rapid increase to infinity, and the molecular weight distribution profile may not show a significant broadening toward gelation. Even though the present model assumes a complete random reaction process among functional groups, formation of a heterogeneous structure in which a tight core consisting of TEOS‐based molecules is surrounded by soft PDMS chains was observed in the Monte Carlo simulation.     

Monte Carlo simulation of size exclusion chromatography for randomly branched and crosslinked polymers

The elution curves of size exclusion chromatography for nonlinear polymers formed through random branching and crosslinking of long polymer chains were simulated with a Monte Carlo method. We considered two types of measured molecular weight distributions (MWDs): (1) the MWD calibrated relative to standard linear polymers and (2) the MWD obtained with a light scattering (LS) photometer in which the weight‐average molecular weight of polymers within the elution volume is determined directly. The calibrated MWDs clearly underestimate the molecular weights for both randomly branched and crosslinked polymers, and this technique can be used to assess the degree of deviation from the true MWD. When the primary chains conform to the most probable distribution, the calibrated MWD can be estimated reasonably well with the Zimm–Stockmayer equation for the g factor with the help of the relationship between the average number of branch points per molecule and the degree of polymerization. However, the LS method gives good estimates of the true MWD for both randomly branched and crosslinked polymers, although the agreement is better for the branched ones. © 2000 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 38: 2009–2018, 2000     

Molecular weight distribution formed during free‐radical polymerization in the presence of polyfunctional chain transfer agents

Free‐radical polymerization of styrene was carried out in the presence of chain transfer agents (CTAs) with functionality, f = 1–4. The size exclusion chromatography (SEC) with an ultraviolet absorption detector (UV) was used to measure the molecular weight distribution (MWD). A Monte Carlo simulation method proposed earlier was used to investigate the experimental results. In this simulation method, one can observe the structure of each polymer molecule directly, and very detailed information can be obtained in a straightforward manner, including the elution curve of SEC. It was found that up to the functionality f = 3, the equal reactivity model that assumes the reactivity of all functional groups in a CTA is equal agrees reasonably well with the experimental results. However, with f = 4, the reactivity of the fourth functional group seems to decrease and the substitution effects may need to be accounted for to fine control the formed branched structure. © 1999 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 37: 1267–1275, 1999     

Cyclometalated Iridium(III) Complex–Cationic Peptide Hybrids Trigger Paraptosis in Cancer Cells via an Intracellular Ca2+ Overload from the Endoplasmic Reticulum and a Decrease in Mitochondrial Membrane Potential

In our previous paper, we reported that amphiphilic Ir complex–peptide hybrids (IPHs) containing basic peptides such as KK(K)GG (K: lysine, G: glycine) (e.g., ASb-2) exhibited potent anticancer activity against Jurkat cells, with the dead cells showing a strong green emission. Our initial mechanistic studies of this cell death suggest that IPHs would bind to the calcium (Ca²⁺)–calmodulin (CaM) complex and induce an overload of intracellular Ca²⁺, resulting in the induction of non-apoptotic programmed cell death. In this work, we conduct a detailed mechanistic study of cell death induced by ASb-2, a typical example of IPHs, and describe how ASb-2 induces paraptotic programmed cell death in a manner similar to that of celastrol, a naturally occurring triterpenoid that is known to function as a paraptosis inducer in cancer cells. It is suggested that ASb-2 (50 µM) induces ER stress and decreases the mitochondrial membrane potential (ΔΨ_m), thus triggering intracellular signaling pathways and resulting in cytoplasmic vacuolization in Jurkat cells (which is a typical phenomenon of paraptosis), while the change in ΔΨ_m values is negligibly induced by celastrol and curcumin. Other experimental data imply that both ASb-2 and celastrol induce paraptotic cell death in Jurkat cells, but this induction occurs via different signaling pathways.     

General matrix formula for the weight-average molecular weights of crosslinked polymer systems

On the basis of the first-order Markovian statistics, we propose a general matrix formula for the weight-average molecular weight of crosslinked polymer systems, explicitly given by M̄_w = M̄_w,0 + WX₀ (I − X)⁻¹ S_f . This equation is valid for both step and chain-growth polymerizations, including those in a nonequilibrium state irrespective of the reactor types used. In the context of the present theory, the onset of gelation is simply stated as a point at which the largest eigenvalue of the matrix X reaches unity (i.e., det( I − X ) = 0). The present theory provides a unified point of view for various types of gelling systems. © 1998 John Wiley & Sons, Inc. J. Polym. Sci. B Polym. Phys. 36: 2423–2433, 1998