Biomass-derived carbon dots as fluorescent quantum probes to visualize and modulate inflammation.

Quantum dots, which won the Nobel Prize in Chemistry, have recently gained significant attention in precision medicine due to their unique properties, such as size-tunable emission, high photostability, efficient light absorption, and vibrant luminescence. Consequently, there is a growing demand to identify new types of quantum dots from various sources and explore their potential applications as stimuli-responsive biosensors, biomolecular imaging probes, and targeted drug delivery agents. Biomass-waste-derived carbon quantum dots (CQDs) are an attractive alternative to conventional QDs, which often require expensive and toxic precursors, as they offer several merits in eco-friendly synthesis, preparation from renewable sources, and cost-effective production. In this study, we evaluated three CQDs derived from biomass waste for their potential application as non-toxic bioimaging agents in various cell lines, including human dermal fibroblasts, HeLa, cardiomyocytes, induced pluripotent stem cells, and an in-vivo medaka fish (Oryzias latipes) model. Confocal microscopic studies revealed that CQDs could assist in visualizing inflammatory processes in the cells, as they were taken up more by cells treated with tumor necrosis factor-α than untreated cells. In addition, our quantitative real-time PCR gene expression analysis has revealed that citric acid-based CQDs can potentially reduce inflammatory markers such as Interleukin-6. Our studies suggest that CQDs have potential as theragnostic agents, which can simultaneously identify and modulate inflammatory markers and may lead to targeted therapy for immune system-associated diseases.

Suppression of Charge Recombination by Vertical Arrangement of A Donor Moiety on Flat Planar Dyes for Efficient Dye-Sensitized Solar Cells.

In dye-sensitized solar cells (DSSCs), flat planar dyes (e. g., highly light-harvesting porphyrins and corroles) with multiple anchoring groups are known to adopt a horizontal orientation on TiO2 through the multiple binding to TiO2. Due to the strong electronic coupling between the dye and TiO2, fast charge recombination between the oxidized dye and an electron in TiO2 occurs, lowering the power conversion efficiency (η). To overcome this situation, an additional donor moiety can be placed on top of the planar dye on TiO2 to slow down the undesirable charge recombination. Here we report the synthesis and photovoltaic properties of a triarylamine (TAA)-tethered gold(III) corrole (TAA-AuCor). The DSSC with TAA-AuCor using iodine redox shuttle exhibited the highest η-value among corrole-based DSSCs, which is much higher than that with the reference AuCor. The transient absorption spectroscopies clearly demonstrated that fast electron transfer from the TAA moiety to the corrole radical cation in TAA-AuCor competes with the undesirable charge recombination to generate long-lived charge separated state TAA⋅+-Cor/TiO2⋅- efficiently. Consequently, the introduction of the TAA moiety enhanced the η-value remarkably, demonstrating the usefulness of our new concept to manipulate charge-separated states toward highly efficient DSSCs.

Extracellular calcium functions as a molecular glue for transmembrane helices to activate the scramblase Xkr4.

The "eat me" signal, phosphatidylserine is exposed on the surface of dying cells by phospholipid scrambling. Previously, we showed that the Xkr family protein Xkr4 is activated by caspase-mediated cleavage and binding of the XRCC4 fragment. Here, we show that extracellular calcium is an additional factor needed to activate Xkr4. The constitutively active mutant of Xkr4 is found to induce phospholipid scrambling in an extracellular, but not intracellular, calcium-dependent manner. Importantly, other Xkr family members also require extracellular calcium for activation. Alanine scanning shows that D123 and D127 of TM1 and E310 of TM3 coordinate calcium binding. Moreover, lysine scanning demonstrates that the E310K mutation-mediated salt bridge between TM1 and TM3 bypasses the requirement of calcium. Cysteine scanning proves that disulfide bond formation between TM1 and TM3 also activates phospholipid scrambling without calcium. Collectively, this study shows that extracellular calcium functions as a molecular glue for TM1 and TM3 of Xkr proteins for activation, thus demonstrating a regulatory mechanism for multi-transmembrane region-containing proteins.

Exciton diffusion in amorphous organic semiconductors: Reducing simulation overheads with machine learning.

Simulations of exciton and charge hopping in amorphous organic materials involve numerous physical parameters. Each of these parameters must be computed from costly ab initio calculations before the simulation can commence, resulting in a significant computational overhead for studying exciton diffusion, especially in large and complex material datasets. While the idea of using machine learning to quickly predict these parameters has been explored previously, typical machine learning models require long training times, which ultimately contribute to simulation overheads. In this paper, we present a new machine learning architecture for building predictive models for intermolecular exciton coupling parameters. Our architecture is designed in such a way that the total training time is reduced compared to ordinary Gaussian process regression or kernel ridge regression models. Based on this architecture, we build a predictive model and use it to estimate the coupling parameters which enter into an exciton hopping simulation in amorphous pentacene. We show that this hopping simulation is able to achieve excellent predictions for exciton diffusion tensor elements and other properties as compared to a simulation using coupling parameters computed entirely from density functional theory. This result, along with the short training times afforded by our architecture, shows how machine learning can be used to reduce the high computational overheads associated with exciton and charge diffusion simulations in amorphous organic materials.

Discovery of a phase-separating small molecule that selectively sequesters tubulin in cells.

Phase-separated membraneless organelles or biomolecular condensates play diverse functions in cells, however recapturing their characteristics using small organic molecules has been a challenge. In the present study, cell-lysate-based screening of 843 self-assembling small molecules led to the discovery of a simple organic molecule, named huezole, that forms liquid droplets to selectively sequester tubulin. Remarkably, this small molecule enters cultured human cells and prevents cell mitosis by forming tubulin-concentrating condensates in cells. The present study demonstrates the feasibility of producing a synthetic condensate out of non-peptidic small molecules for exogenous control of cellular processes. The modular structure of huezole provides a framework for designing a class of organelle-emulating small molecules.

Intrinsic Hole Mobility in Luminescent Metal-Organic Frameworks and Its Application in Organic Light-Emitting Diodes.

Most metal-organic frameworks (MOFs) lack charge mobility, which is crucial for realizing their use in optoelectronic applications. This work proposes the design of a MOF using triarylamine-based ligands (Zr-NBP) as the lone pair electron spacer to enhance the hole mobility in the MOF while maintaining its luminescent properties. Zr-NBP has strong fluorescence with a good hole mobility of 1.05×10-6  cm2 V-1 s-1 , which is comparable to organic materials used in optoelectronic devices. We also employed a Zr-NBP nanofilm in the pure phase as both a non-doped emissive layer and a hole-transporting layer within organic light-emitting diodes (OLEDs). The obtained OLED device produced a bright green light with a low turn-on voltage of 3.9 V. This work presents an advance in developing the electronic properties of MOFs by modifying the chemical properties of its building blocks, and will likely inspire further design of MOF materials as active layers in optoelectronic devices.

One-Pot, Room-Temperature Conversion of CO2 into Porous Metal-Organic Frameworks.

The conversion of CO2 into functional materials under ambient conditions is a major challenge to realize a carbon-neutral society. Metal-organic frameworks (MOFs) have been extensively studied as designable porous materials. Despite the fact that CO2 is an attractive renewable resource, the synthesis of MOFs from CO2 remains unexplored. Chemical inertness of CO2 has hampered its conversion into typical MOF linkers such as carboxylates without high energy reactants and/or harsh conditions. Here, we present a one-pot conversion of CO2 into highly porous crystalline MOFs at ambient temperature and pressure. Cubic [Zn4O(piperazine dicarbamate)3] is synthesized via in situ formation of bridging dicarbamate linkers from piperazines and CO2 and shows high surface areas (∼2366 m2 g-1) and CO2 contents (>30 wt %). Whereas the dicarbamate linkers are thermodynamically unstable by themselves and readily release CO2, the formation of an extended coordination network in the MOF lattices stabilizes the linker enough to demonstrate stable permanent porosity.

Caspase cleavage releases a nuclear protein fragment that stimulates phospholipid scrambling at the plasma membrane.

Phospholipid scrambling in dying cells promotes phosphatidylserine exposure, a critical process for efferocytosis. We previously identified the Xkr family protein Xkr4 as a phospholipid-scrambling protein, but its activation mechanisms remain unknown. Here we show that Xkr4 is activated in two steps: dimer formation by caspase-mediated cleavage and structural change caused by activating factors. To identify the factors, we developed a new screening system, "revival screening," using a CRISPR sgRNA library. Applying this system, we identified the nuclear protein XRCC4 as the single candidate for the Xkr4 activator. Upon apoptotic stimuli, XRCC4, contained in the DNA repair complex, is cleaved by caspases, and its C-terminal fragment with an intrinsically disordered region is released into the cytoplasm. Protein interaction screening showed that the fragment interacts directly with the Xkr4 dimer to activate it. This study demonstrates that caspase-mediated cleavage releases a nuclear protein fragment for direct regulation of lipid dynamics on the plasma membrane.

Discovery of Self-Assembling Small Molecules as Vaccine Adjuvants.

Immune potentiators, termed adjuvants, trigger early innate immune responses to ensure the generation of robust and long-lasting adaptive immune responses of vaccines. Presented here is a study that takes advantage of a self-assembling small-molecule library for the development of a novel vaccine adjuvant. Cell-based screening of the library and subsequent structural optimization led to the discovery of a simple, chemically tractable deoxycholate derivative (molecule 6, also named cholicamide) whose well-defined nanoassembly potently elicits innate immune responses in macrophages and dendritic cells. Functional and mechanistic analyses indicate that the virus-like assembly enters the cells and stimulates the innate immune response through Toll-like receptor 7 (TLR7), an endosomal TLR that detects single-stranded viral RNA. As an influenza vaccine adjuvant in mice, molecule 6 was as potent as Alum, a clinically used adjuvant. The studies described here pave the way for a new approach to discovering and designing self-assembling small-molecule adjuvants against pathogens, including emerging viruses.

Exploring the configuration spaces of surface materials using time-dependent diffraction patterns and unsupervised learning.

Computational methods for exploring the atomic configuration spaces of surface materials will lead to breakthroughs in nanotechnology and beyond. In order to develop such methods, especially ones utilizing machine learning approaches, descriptors which encode the structural features of the candidate configurations are required. In this paper, we propose the use of time-dependent electron diffraction simulations to create descriptors for the configurations of surface materials. Our proposal utilizes the fact that the sub-femtosecond time-dependence of electron diffraction patterns are highly sensitive to the arrangement of atoms in the surface region of the material, allowing one to distinguish configurations which possess identical symmetry but differ in the locations of the atoms in the unit cell. We demonstrate the effectiveness of this approach by considering the simple cases of copper(111) and an organic self-assembled monolayer system, and use it to search for metastable configurations of these materials.

Disorder-robust bands from anisotropic orbitals in a coordination polymer semiconductor.

While the effects of structural disorder on the electronic properties of solids are poorly understood, it is widely accepted that spatially isotropic orbitals lead to robustness against disorder. In this paper, we use first-principles calculations to show that a cluster of occupied bands in the coordination polymer semiconductor ß-copper(I) thiocyanate undergo relatively little fluctuation in the presence of thermal disorder-a surprising finding given that these bands are composed of spatially anisotropic d-orbitals. Analysis with the tight-binding method and a stochastic network model suggests that the robustness of these bands to the thermal disorder can be traced to the way in which these orbitals are aligned with respect to each other. This special alignment causes strong inverse statistical correlations between orbital-orbital distances, making these bands robust to random fluctuations of these distances. As well as proving that disorder-robust electronic properties can be achieved even with anisotropic orbitals, our results provide a concrete example of when simple 'averaging' methods can be used to treat thermal disorder in electronic structure calculations.

Materials informatics for self-assembly of functionalized organic precursors on metal surfaces.

Bottom-up fabrication via on-surface molecular self-assembly is a way to create defect-free, low-dimensional nanomaterials. For bottom-up fabrication to succeed, precursor molecules which correctly assemble into the target structure must be first identified. Here we present an informatics technique which connects self-assembled structures with particular chemical properties of the precursor molecules. Application of this method produces a visual output (a dendrogram) that functions much like the periodic table, but whereas the periodic table puts atoms into categories according to the way in which they bond to each other, the dendrogram put molecules into categories according to the way in which they arrange in a self-assembled structure. By applying this method to the case of functionalized bianthracene precursors adsorbed to copper(111), we identify the functional groups needed to assemble one-dimensional chains, two-dimensional tilings, and other shapes. This methodology can therefore help to identify appropriate precursor molecules for forming target nanomaterials via bottom-up fabrication.

Construction of a Hierarchical Architecture of Covalent Organic Frameworks via a Postsynthetic Approach.

Covalent organic frameworks (COFs) represent an emerging class of crystalline porous materials that are constructed by the assembly of organic building blocks linked via covalent bonds. Several strategies have been developed for the construction of new COF structures; however, a facile approach to fabricate hierarchical COF architectures with controlled domain structures remains a significant challenge, and has not yet been achieved. In this study, a dynamic covalent chemistry (DCC)-based postsynthetic approach was employed at the solid-liquid interface to construct such structures. Two-dimensional imine-bonded COFs having different aromatic groups were prepared, and a homogeneously mixed-linker structure and a heterogeneously core-shell hollow structure were fabricated by controlling the reactivity of the postsynthetic reactions. Solid-state nuclear magnetic resonance (NMR) spectroscopy and transmission electron microscopy (TEM) confirmed the structures. COFs prepared by a postsynthetic approach exhibit several functional advantages compared with their parent phases. Their Brunauer-Emmett-Teller (BET) surface areas are 2-fold greater than those of their parent phases because of the higher crystallinity. In addition, the hydrophilicity of the material and the stepwise adsorption isotherms of H2O vapor in the hierarchical frameworks were precisely controlled, which was feasible because of the distribution of various domains of the two COFs by controlling the postsynthetic reaction. The approach opens new routes for constructing COF architectures with functionalities that are not possible in a single phase.

A Hydroxamic Acid Anchoring Group for Durable Dye-Sensitized Solar Cells Incorporating a Cobalt Redox Shuttle.

A hydroxamic acid group has been employed for the first time as an anchoring group for cobalt-based dye-sensitized solar cells (DSSCs). The porphyrin dye YD2-o-C8HA including a hydroxamic acid anchoring group exhibited a power conversion efficiency (η) of 6.4 %, which is close to that of YD2-o-C8, a representative porphyrin dye incorporating a conventional carboxylic acid. More importantly, YD2-o-C8HA was found to be superior to YD2-o-C8 in terms of both binding ability to TiO2 and durability of cobalt-based DSSCs. Notably, YD2-o-C8HA photocells revealed a higher η-value (4.1 %) than YD2-o-C8 (2.8 %) after 500 h illumination. These results suggest that the hydroxamic acid can be used for DSSCs with other transition-metal-based redox shuttle to ensure high cell durability as well as excellent photovoltaic performance.

Chemical and entropic control on the molecular self-assembly process.

Molecular self-assembly refers to the spontaneous assembly of molecules into larger structures. In order to exploit molecular self-assembly for the bottom-up synthesis of nanomaterials, the effects of chemical control (strength of the directionality in the intermolecular interaction) and entropic control (temperature) on the self-assembly process should be clarified. Here we present a theoretical methodology that unambiguously distinguishes the effects of chemical and entropic control on the self-assembly of molecules adsorbed to metal surfaces. While chemical control simply increases the formation probability of ordered structures, entropic control induces a variety of effects. These effects range from fine structure modulation of ordered structures, through to degrading large, amorphous structures into short, chain-shaped structures. Counterintuitively, the latter effect shows that entropic control can improve molecular ordering. By identifying appropriate levels of chemical and entropic control, our methodology can, therefore, identify strategies for optimizing the yield of desired nanostructures from the molecular self-assembly process.

State-space reduction and equivalence class sampling for a molecular self-assembly model.

Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.

Charge transport in organic crystals: critical role of correlated fluctuations unveiled by analysis of Feynman diagrams.

Organic crystals have unique charge transport properties that lie somewhere between delocalised band-type transport and localised hopping transport. In this paper, we use a stochastic tight-binding model to explore how dynamical disorder in organic crystals affects charge transport. By analysing the model in terms of Feynman diagrams (virtual processes), we expose the crucial role of correlated dynamical disorder to the charge transport dynamics in the model at short times in the order of a few hundred femtoseconds. Under correlated dynamical disorder, the random motions of molecules in the crystal allow for low-energy "bonding"-type interactions between neighboring molecular orbitals can persist over long periods of time. On the other hand, the dependence of charge transport on correlated dynamical disorder also tends to localize the charge, as correlated disorder cannot persist far in space. This concept of correlation may be the "missing link" for describing the intermediate regime between band transport and hopping transport that occurs in organic crystals.

Effects of atomic collisions on the stoichiometry of thin films prepared by pulsed laser deposition.

We present an analytical model to quantitatively study the effect of collisions between the atoms of a plume and the molecules of a surrounding gas on the nonstoichiometry of lithium-containing oxide thin films deposited using pulsed laser deposition. A comparison of the experimental data and the model ascertain the inevitable loss of the lighter cation, leading to a nonstoichiometric reduction in the content of lighter cations in the films. Our model is the first analytic model of collision-induced plume expansion that can explain the partial oxygen pressure dependence of the Li content of a thin film. These studies have important implications for collision effects that affect the growth of thin films containing both light and heavy elements.

Dephasing by a continuous-time random walk process.

Stochastic treatments of magnetic resonance spectroscopy and optical spectroscopy require evaluations of functions such as (exp(i ∫(0)(t) Q(s)ds)), where t is time, Q(s) is the value of a stochastic process at time s, and the angular brackets denote ensemble averaging. This paper gives an exact evaluation of these functions for the case where Q is a continuous-time random walk process. The continuous-time random walk describes an environment that undergoes slow steplike changes in time. It also has a well-defined Gaussian limit and so allows for non-Gaussian and Gaussian stochastic dynamics to be studied within a single framework. We apply the results to extract qubit-lattice interaction parameters from dephasing data of P-doped Si semiconductors (data collected elsewhere) and to calculate the two-dimensional spectrum of a three-level harmonic oscillator undergoing random frequency modulations.

Non-Gaussian stochastic dynamics of spins and oscillators: a continuous-time random walk approach.

We consider separately a spin and an oscillator that are coupled to their environment. After a finite interval of random length, the state of the environment changes, and each change causes a random change in the resonance frequency of the spin or vibrational frequency of the oscillator. Mathematically, the evolution of these frequencies is described by a continuous-time random walk. Physically, the stochastic dynamics can be understood as non-Gaussian because the frequency of the system and state of the environment change on comparable time scales. These dynamics are also nonstationary, and so might apply to a nonequilibrium environment. The resonance and vibrational spectra of the spin and oscillator, as well as the ensemble-averaged displacement of the oscillator, are investigated in detail. We observe some distinct non-Gaussian features of the dynamics, such as the narrow, leptokurtic shape of the resonance spectrum of the spin and beating of the average oscillator displacement. The convergence to Gaussian dynamics as changes in the environment occur with increasing frequency is also considered. Among other results, we observe narrowing of the resonance and vibrational lines in the Gaussian limit due to a weakening of the system-environment interaction.