Fast Reaction Research Articles

Reaction Rate and Stereoselectivity Enhancement in Glycosidations with O-Glycosyl Trihaloacetimidate Donors due to Catalysis by a Lewis Acid-Nitrile Cooperative Effect.

Activation of O-glycosyl trihaloacetimidate glycosyl donors with AuCl3 as a catalyst and pivalonitrile (tBuCN) as a ligand led to excellent glycosidation results in terms of yield and anomeric selectivity. In this way, various β-d-gluco- and β-d-galactopyranosides were obtained conveniently and efficiently. Experimental studies and density functional theory (DFT) calculations, in order to elucidate the reaction course, support formation of the tBuCN-AuCl2-OR(H)+ AuCl4- complex as a decisive intermediate in the glycosidation event. Proton transfer from this acceptor complex to the imidate nitrogen leads to donor activation. In this way, guided by the C-2 configuration of the glycosyl donor, the alignment of the acceptor complex enforces the stereoselective β-glycoside formation in an intramolecular fashion, thus promoting also a fast reaction course. The high stereocontrol of this novel 'Lewis acid-nitrile cooperative effect' is independent of the glycosyl donor anomeric configuration and without the support of neighboring group or remote group participation. The power of the methodology is shown by a successful glycoalkaloid solamargine synthesis.

New SiS destruction and formation routes via neutral-neutral reactions and their fundamental role in interstellar clouds at low- and high-metallicity values

Among the silicon-bearing species discovered in the interstellar medium, SiS and SiO stand out as key tracers due to their distinct chemistry and variable abundances in interstellar and circumstellar environments. Nevertheless, while the origins of SiO are well documented, the SiS chemistry remains relatively unexplored. Our objective is to enhance the network of Si- and S-bearing chemical reactions for a gas-grain model in molecular clouds, encompassing both low and high metallicities. To achieve this, we calculated the energies and rate coefficients for six neutral atom-diatom reactions involved in the SiCS triatomic system, with a special focus on the C+SiS and S+SiC collisions. We employed the coupled-cluster method with single and double substitutions and a perturbative treatment of triple substitutions (CCSD(T)) refined at the explicitly correlated CCSD(T)-F12 level. With these computational results in conjunction with supplementary data from the literature, we construct an extended network of neutral-neutral chemical reactions involving Si- and S-bearing molecules. To assess the impact of these chemical reactions, we performed time-dependent models employing the Nautilus gas-grain code, setting the gas temperature to 10 K and the H$_2$ density to 2times 10$^4$ cm$^ $. The models considered two initial abundance scenarios, corresponding to low- and high-metallicity levels. Abundances were computed using both the default chemical network and the constrained network, enriched with newly calculated reactions. The temperature dependence for the reactions involving SiS were modelled to the $k(T)= T/300 beta gamma/T) $ expression, and the coefficients are provided for the first time. The high-metallicity models significantly boost the SiS production, resulting in abundances nearly four orders of magnitude higher compared to low-metallicity models. Higher initial abundances of C, S, and Si, roughly sim 2, 190, and 210 times higher, respectively, contribute to this. Around the age of 10$^3$ yr, destruction mechanisms become relevant, impacting the abundance of SiS. The proposed production reaction S + SiC longrightarrow C + SiS, mitigates these effects in later stages. By expanding the gas reaction network using a high-metallicity model, we derived estimates for the abundances of observed interstellar molecules, including SiO, SO, and SO$_2$. We demonstrate the significance of both SiC+S and C+SiS channels in the SiS chemistry. Notably, the inclusion of neutral-neutral mechanisms, particularly via Si+HS and S+SiC channels, played a pivotal role in determining SiS abundance. These mechanisms carry a significance level on a par with that of the well-known and fast ion-neutral reactions.

Change blindness, reward bias, negative affective priming: Exploring individual‐level associations between depression/anxiety symptoms and cognition

AbstractCognitive biases are thought to contribute to depression/anxiety. In addition to self‐reported measures, cognitive tasks could potentially be integrated with clinical practice as more precise measures of cognitive biases. In a large online study we explored the individual‐level association between depression/anxiety symptoms and performance on (1) reward bias, (2) negative affective priming, and (3) change blindness tasks. Participants completed tasks alongside depression/anxiety symptom questionnaires. We used regression analyses to test for associations between task performance and questionnaire scores. We conducted a replication study of the change blindness task, and performed a mega‐analysis of the two studies. Faster reaction time in the change blindness task was associated with higher depression score (B = −27, p = 0.034) in the first study (N = 545) and higher depression and anxiety scores (depression: B = −15, p = 0.045; anxiety: B = −17, p = 0.022) in the replication study (N = 616). These effects were significant in the mega‐analysis but did not withstand adjusting for age in either the original and replication studies or the mega‐analysis. We found no association between depression/anxiety and reward bias (N = 504) and negative affective priming (N = 539). Our results provide preliminary evidence that individuals with more severe depressive/anxious symptoms may be faster at identifying changes in the change blindness task. Contrary to previous findings, neither reward bias nor negative affective priming was associated with depression/anxiety.

The impact of music training on temporal order processing in Mandarin Chinese sentence reading: Evidence from event-related potentials (ERPs).

The objective of this study was to investigate the impact of music training on the processing of temporal order in Mandarin sentence reading using event-related potentials (ERPs). Two-clause sentences with temporal connectives ("before" or "after") were presented to both musicians and non-musicians. Additionally, a verbal N-back task was utilized to evaluate the participants' working memory capacities. The findings revealed that musicians, but not nonmusicians, demonstrated a more negative amplitude in the second clauses of "before" sentences compared with "after" sentences. In the N-back task, musicians exhibited faster reaction times than nonmusicians in the two-back condition. Furthermore, a correlation was observed between the ERP amplitude differences (before vs. after) and reaction time differences in the N-back task (0-back vs. 2-back) among musicians. These findings suggested that music training enhances the depth of temporal order processing, potentially mediated by improvements in working memory capacity.

A comprehensive understanding of the role of sodium sulfate in calcium looping via in-situ experiments and DFT studies: Performance and mechanism

Adding alkali metal salt promoters to calcium-based materials can influence the cycling performance of CaO-based sorbents. So far, most research on alkali metal salts focus on carbonate and chloride salts, while little attention is paid to sulfates. In this paper, we present an in-depth study of the role of Na2SO4 in calcium looping via in-situ experiments and DFT simulations. The results show that the effective conversion rate of Na2SO4-CaO after one cycle is 0.779 with the energy storage density of 2476.1 kJ/kg, while the effective conversion rate of CaO is 0.562 with the energy storage density of 1786.4 kJ/kg. After 80 cycles, the effective conversion and energy storage density of Na2SO4-CaO are lower than CaO, which is attributed to Na+ reducing the surface energy and accelerating the sintering. Moreover, an optimization strategy based on coordination effect among Na2SO4, CaO and inert oxides is proposed to slow down the sintering problems. Among them, Na2SO4-(CaO + ZnO) has the best adsorption performance and energy storage performance and ZnO is cheap, which can be considered a cost-effective sorbent. This work provides a new approach for developing efficient, simple and cost-effective calcium-based materials by simultaneously achieving fast reaction rates and good cycling stability of CaL.

Evaluation of cross sections for fast ion reactions with beryllium in helium and hydrogen fusion plasmas

Abstract To computationally support hydrogen and helium plasma discharges in the early stages of tokamak operation and to support the commissioning of the neutron detectors during these operational phases, creation of a realistic neutron and gamma ray particle source for Monte Carlo simulations will be needed. One of the most important parts of creating the particle source is calculating the reaction rates of the particle-emitting reactions to determine the emission profile in the plasma and the energy spectra of the emitted particles. In this paper the analysis and evaluation of cross sections for important neutron-emitting reactions, namely, 9Be(p,nγ)9B, 9Be(3He,nγ) 11C and charged-particle emission reactions 9Be(p,d)2α and 9Be(p,α)6Li that cause neutron emission in the next step of interactions are presented. The reaction cross sections were evaluated based on experimental measurements and empirical models describing the interaction of two charged particles. Evaluation of the associated uncertainties was also performed. The main goal of the work is to propose the newly evaluated cross sections for inclusion in the FENDL nuclear data library, thus making the cross section available to other researchers studying the above listed reactions.

Effect of Condensed Water at an Alumina/Epoxy Resin Interface on Curing Reaction.

The adhesion of epoxy adhesives to aluminum materials is an important issue in assembling parts for lightweight mobility. Aluminum surfaces typically possess an oxide layer, which readily adsorbs water. In this study, the aggregation states of water and its effect on the curing reaction were examined by placing a water layer between an amorphous alumina surface and a mixture of epoxy and amine components. This study used molecular dynamics simulations and density functional theory calculations. Before the reaction, water molecules strongly adsorbed onto the alumina surface, aggregating excess water. Some water diffused into the epoxy/amine mixture, accelerating the diffusion of unreacted substances. This led to faster reaction kinetics, particularly in proximity to the alumina surface. The adsorption of water molecules onto the alumina surface and the aggregation of excess water were similarly observed even after the curing process. Subsequently, the interaction between the alumina surface and various functional groups of the epoxy/amine mixture was evaluated before and after the reaction. Epoxy monomers had little interaction with the alumina surface before the reaction, whereas hydroxy groups formed by the ring-opening reaction of epoxy groups exhibited notable interaction. Conversely, sulfonyl and amino groups in amine compounds formed hydrogen bonds with OH groups on the alumina surface before the reaction. However, after the reaction, amino groups weakened their interaction with the alumina OH groups as they transformed from primary to tertiary during the curing reaction. Both epoxy and amine monomers/fragments similarly interacted with water molecules, both before and after the reaction. The insights gained from this study are expected to contribute to a better understanding of the impact of moisture absorption on the application of epoxy resins.

Intelligent near-infrared light-activatable DNA machine with DNA wire nano-scaffold-integrated fast domino-like driving amplification for high-performance imaging in live biological samples

While there is significant potential for DNA machine-built enzyme-free fluorescence biosensors in the imaging analysis of live biological samples, they persist certain shortcomings. These encompass a deficiency of signal enrichment within a singular interface, uncontrolled premature activation during bio-delivery, and a slow reaction rate due to free nucleic acid collisions. In this contribution, we are committed to resolving the above challenges. Firstly, a single-interface-integrated domino-like driving amplification is constructed. In this conception, a specific target acts as the domino promotor (namely the energy source), initiating a cascading chain reaction that grafts onto a singular interface. Next, an 808 nm near-infrared (NIR) light-excited up-converting luminescence-induced light-activatable biosensing technique is introduced. By locking the target-specific identification segment with a photo-cleavage connector, the up-converted ultraviolet emission can activate target binding in a completely controlled manner. Moreover, a fast reaction rate is achieved by confining nucleic acid collisions within the surface of a DNA wire nano-scaffold, leading to a substantial enhancement in local contact concentration (30.8-fold increase, alongside a 15 times elevation in rate). When a non-coding microRNA (miRNA-221) is positioned as the model low-abundance target for proof-of-concept validation, our intelligent DNA machine demonstrates ultra-high sensitivity (with a limit of detection down to 62.65 fM) and good specificity for this hepatic malignant tumor-associated biomarker in solution detection. Going further, it is worth highlighting that the biosensing system can be employed to carry out high-performance imaging analysis in live bio-samples (ranging from the cellular level to the nude mouse body), thereby propelling the field of DNA machines in disease diagnosis.

Heterostructure Engineering Enables MoSe2 with Superior Alkali-Ion Storage

Molybdenum diselenide (MoSe2) is a promising anode for alkali-ion storage due to its intrinsic advantages. However, MoSe2 still encounters the issues of structural instability and poor rate performance caused by drastic volume change and sluggish reaction kinetics. Reasonable design of electrode structure is crucial for achieving superior electrochemical performance. Herein, a novel hierarchical structure coupled with 1D/1D subunits is elaborately designed and constructed, in which the MoSe2/CoSe2 heterostructure is the “trunk” and the N-doped carbon nanotubes are the “branches” (MoSe2/CoSe2/NCNTs). Benefiting from the properties endowed by unique configurations, MoSe2/CoSe2/NCNTs electrodes manifest faster reaction kinetics and better structure durability. Evaluated as an anode for LIBs and SIBs, MoSe2/CoSe2/NCNTs deliver high reversible capacity, superior rate capability (452 at 10 A g−1 in LIBs and 296 at 10 A g−1 in SIBs), and prominent cycle life (553 after 2000 cycles at 5 A g−1 in LIBs and 310 after 2000 cycles at 5 A g−1 in SIBs). Such design conception can also provide guidance for the development of other high-performance electrodes.

Data-Driven SiC MOSFET Active Gate Driving for 380V/3A LVDC System Protection Employing Recurrent Deep Neural Network

This article proposed a Gated-Recurrent Learning Deep Neural Network (GRL-DNN) to predict the gate driving sequence of SiC-MOSFET in a 380 V/3A Low Voltage DC microgrid (LVDC). It is devised that the proposed intelligent fuse Active Gate Driving (AGD) requires a current limitation of 3 A to avoid fault and excess power loss. During over-current conditions in microgrid the proposed data-driven Intelligent Fuse (iFuse) acts as a circuit breaker with current limitation. The proposed GRL-DNN switching model training dataset is obtained for various operating condition in MATLAB. Training features like gate triggering, temperature, over-current magnitude, and tripping time are obtained by the proposed circuitry sequence predictor model in LTspice. By obtaining large solution space, without any delay automatic AGD can cutoff over-current in LVDC microgrid system. By comparing with conventional gate driving solid state fuse by Angelov model, the proposed iFuse integrated merits like fast reaction, accurate tripping, and high reliability to any system for improving fault protection. Online data analysis was carried to validate the outcome of the proposed iFuse AGD in hardware-in-loop simulation. The conducted real-time scaled-down experiment under over-current conditions on 380 V/3A LVDC system shows the proposed GRL-DNN based iFuse as a valuable active gate driving component for protection.

Network-targeted transcranial direct current stimulation of the hypothalamus appetite-control network: a feasibility study.

The hypothalamus is the key regulator for energy homeostasis and is functionally connected to striatal and cortical regions vital for the inhibitory control of appetite. Hence, the ability to non-invasively modulate the hypothalamus network could open new ways for the treatment of metabolic diseases. Here, we tested a novel method for network-targeted transcranial direct current stimulation (net-tDCS) to influence the excitability of brain regions involved in the control of appetite. Based on the resting-state functional connectivity map of the hypothalamus, a 12-channel net-tDCS protocol was generated (Neuroelectrics Starstim system), which included anodal, cathodal and sham stimulation. Ten participants with overweight or obesity were enrolled in a sham-controlled, crossover study. During stimulation or sham control, participants completed a stop-signal task to measure inhibitory control. Overall, stimulation was well tolerated. Anodal net-tDCS resulted in faster stop signal reaction time (SSRT) compared to sham (p = 0.039) and cathodal net-tDCS (p = 0.042). Baseline functional connectivity of the target network correlated with SSRT after anodal compared to sham stimulation (p = 0.016). These preliminary data indicate that modulating hypothalamus functional network connectivity via net-tDCS may result in improved inhibitory control. Further studies need to evaluate the effects on eating behavior and metabolism.

Graphdiyne Enabled Nitrogen Vacancy Formation in Copper Nitride for Efficient Ammonia Synthesis.

The electrocatalytic reduction of nitrate is promising for sustainable ammonia synthesis but suffers from slow reduction kinetics and multiple competing reactions. Here, we report a catalyst featuring copper nitride (Cu3N) anchored on a novel graphdiyne support (termed Cu3N/GDY), which is used for electrocatalytic reduction of nitrate to produce ammonia. The GDY absorbed hydrogen and enabled nitrogen (N) vacancy formation in Cu3N for the fast nitrate reduction reaction (NO3RR). Further, the distinct absorption sites formed by GDY and N vacancy enabled the excellent selectivity and stability of NO3RR. Notably, the Cu3N/GDY catalyst achieved a high ammonia yield (YNH3) up to 35280 μg h-1 mgcat.-1 and a high Faradaic efficiency (FE) of 98.1% using 0.1 M NO3- at -0.9 V versus a reversible hydrogen electrode (RHE). Using electron paramagnetic resonance (EPR) technology and in situ X-ray absorption fine structure (XAFS) spectroscopy measurement, we visualized the N vacancy formation in Cu3N and electrocatalytic NO3RR enabled by GDY. These findings show the promise of GDY in sustainable ammonia synthesis and highlight the efficacy of Cu3N/GDY as a catalyst.

An Improved Fire Detection Approach Based On Yolo-v8 for Smart Cities

Systems for detecting fires are essential for preventing property damage and saving lives. defending people and property. Conventional techniques frequently depend on sensor-based strategies, which have limitations in intricate settings. In order to improve accuracy and efficiency, this study suggests an intelligent fire detection system that makes use of machine learning and computer vision techniques. The technology analyzes video streams in real time using deep learning algorithms to identify fire incidents based on visual patterns and attributes. Future research on fire detection systems will benefit from the information this study will provide for smoker and fire detection issues in both indoor and outdoor situations. The improved fire detection technique for smart cities that is based on the YOLOv8 algorithm is the smart fire detection system (SFDS), which uses deep learning to identify fire-specific properties in real-time. The SFDS strategy may be more cost-effective, reduce false alarms, and improve fire detection accuracy when compared to traditional methods. It can also be extended to find other intriguing aspects of smart cities, such as gas leakage or flooding. The proposed smart city framework consists of four primary levels: the application layer (i), cloud layer (iii), fog layer (ii), and internet of things layer (iv). The recommended technique uses fog, cloud computing, and the Internet of Things layer to collect and understand data in real time. This reduces the chance of damage to persons or property and enables faster reaction times. The SFDS demonstrated state- of-the-art performance in terms of precision and recall, with a high precision rate of 97.1% across all classes. Among the potential applications are intelligent security systems, forest fire monitoring, and public space fire safety management.

Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs

The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. However, current optimizers show limitations in maintaining sufficient exploration/exploitation balance for problems dealing with multiple conflicting objectives and complex constraints. Here, we devise an Evolution-Guided Bayesian Optimization (EGBO) algorithm that integrates selection pressure in parallel with a q-Noisy Expected Hypervolume Improvement (qNEHVI) optimizer; this not only solves for the Pareto Front (PF) efficiently but also achieves better coverage of the PF while limiting sampling in the infeasible space. The algorithm is developed together with a custom self-driving lab for seed-mediated silver nanoparticle synthesis, targeting 3 objectives (1) optical properties, (2) fast reaction, and (3) minimal seed usage alongside complex constraints. We demonstrate that, with appropriate constraint handling, EGBO performance improves upon state-of-the-art qNEHVI. Furthermore, across various synthetic multi-objective problems, EGBO shows significative hypervolume improvement, revealing the synergy between selection pressure and the qNEHVI optimizer. We also demonstrate EGBO’s good coverage of the PF as well as comparatively better ability to propose feasible solutions. We thus propose EGBO as a general framework for efficiently solving constrained multi-objective problems in high-throughput experimentation platforms.

Travelling waves for a fast reaction limit of a discrete coagulation-fragmentation model with diffusion and proliferation.

We study traveling wave solutions for a reaction-diffusion model, introduced in the article Calvez et al. (Regime switching on the propagation speed of travelling waves of some size-structured myxobacteriapopulation models, 2023), describing the spread of the social bacterium Myxococcus xanthus. This model describes the spatial dynamics of two different cluster sizes: isolated bacteria and paired bacteria. Two isolated bacteria can coagulate to form a cluster of two bacteria and conversely, a pair of bacteria can fragment into two isolated bacteria. Coagulation and fragmentation are assumed to occur at a certain rate denoted by k. In this article we study theoretically the limit of fast coagulation fragmentation corresponding mathematically to the limit when the value of the parameter k tends to . For this regime, we demonstrate the existence and uniqueness of a transition between pulled and pushed fronts for a certain critical ratio between the diffusion coefficient of isolated bacteria and the diffusion coefficient of paired bacteria. When the ratio is below , the critical front speed is constant and corresponds to the linear speed. Conversely, when the ratio is above the critical threshold, the critical spreading speed becomes strictly greater than the linear speed.

Order-disorder structural engineering of vanadium oxide anode: Balancing ionic and electronic dynamic for fast-charging aqueous Li-ion battery

Fast-charging aqueous lithium-ion batteries (ALIBs) are considered as promising energy storage devices because of their non-flammability and environmentally friendly characteristics. However, how to balance the ionic and electronic dynamics for fast charging reactions remains a significant challenge under the current research status. Here, the order-disorder structural engineering strategy is adopted to resolve this issue, considering the difference between ion and electron transportation in the crystalline and amorphous phases, respectively. Vanadium oxide anodes were developed with optimized ionic and electronic dynamics by using an organic-inorganic hybrid material as a precursor along with refined regulation on the calcination temperature and time. This facile and large-scale extendable approach harnesses the benefits of the order-disorder structure to optimize Li+ storage efficiency and facilitate the high reversibility of Li-ion during fast charging. Consequently, the order-disorder V2O5-based full cell with LiMn2O4 as a cathode exhibits high specific capacity (262.71 mAh g−1, 89.35 % of the theoretical capacity of V2O5), high energy density (166.04 Wh kg−1), fast Li-ion diffusion coefficient (7.34×10−5 cm2 s−1) and fast-charging performance (only 6 min achieves 82.84 % of initial state-of-charge capacity). This work explores the ionic and electronic dynamic of ordered-disorder structure and offers new insights into the development of fast-charging metal ion batteries.

Facile and efficient in-situ end-functionalization of neodymium-based polybutadiene by isocyanate via a coordinative chain transfer polymerization strategy

Tapping facile and efficient strategies for in-situ end-functionalization of polydiene elastomers has been pursued for scientists for decades. This has been especially prominent for Ziegler-Natta type catalytic systems, because they hold great potential for future large-scale industrializations. In this report, through using a newly emerged method of coordinative chain transfer polymerization (CCTP), we introduce a simple and convenient method to efficiently end-functionalize neodymium-based polybutadienes by in-situ addition of isocyanate or isothiocyanate compounds. These two types of substrates performed high reactivities with η1-allyl-Al capped polybutadienyl chain-ends, that were generated from fast and reversible chain transfer reactions, giving high functionalization efficiencies (up to 97.1 %). The high functionalization efficiencies were also applicable to isocyanate or isothiocyanate substrates bearing different functionalities, showing a broad scope capability. Moreover, such a functionalization process was not influenced by the viscosities of the reaction system, as revealed from the kinetic studies that linear relationship was obtained between Mns and various [BD]/[Nd] ratios, implying again the high reactivities of the isocyanate or isothiocyanate compounds. Due to the incorporation of amide or thioamide functional group into the chain-ends, the corresponding polybutadienes showed much improved surface properties and performed higher mechanical properties than unfunctionalized counterparts for raw rubber matrix. Regarding the vulcanizate, chain-end functional groups could also result in much improved filler dispersion and stronger interaction between rubber and filler particles, which eventually gave rise to better mechanical properties, inducing higher tensile strength, more toughness, and greater tear strength.

Bimetallic Ni and Pt single atoms anchored on nitrogen–phosphorus doped porous carbon fibers to achieve significant electrocatalytic hydrogen evolution

The commercial application of water electrolysis for hydrogen production requires the development of low precious metal catalysts with a high crustal abundance. One feasible strategy is to utilize bimetallic catalysts composed of both transition and precious metals. In this study, a novel N/P-doped Ni/Pt bimetallic catalyst is developed (NiPt@C-NP, 3.68 % Ni, 0.2 % Pt) using polyacrylonitrile fibers as an inexpensive carbon source for catalyst support. Due to strong anchoring from the N and P heteroatoms, the nickel and platinum species are mono-atomically dispersed throughout the catalyst. Under acidic conditions, NiPt@C-NP exhibits a hydrogen evolution overpotential of 89 mV (10 mA cm−2), whereas an unsupported platinum catalyst gives an overpotential of 302 mV. The mass activity of Pt in NiPt@C-NP reaches 36.17 A mgPt−1, which is 33 times higher than 20 % Pt/C (1.07 A mgPt−1). Density functional theory (DFT) calculations reveal that synergistic interactions between Ni and Pt significantly increase the density of state near the Fermi level of NiPt@C-NP, resulting in a reduced bandgap and an enhanced charge transfer capability. Furthermore, the Gibbs free energy at the Pt and Ni sites is − 0.25 and − 0.63 eV, respectively, indicating fast reaction kinetics.

Functionalization of Supramolecular Polymers by Dynamic Covalent Boroxine Chemistry.

Molecular scaffolds that enable the combinatorial synthesis of new supramolecular building blocks are promising targets for the construction of functional molecular systems. Here, we report a supramolecular scaffold based on boroxine that enables the formation of chiral and ordered 1D supramolecular polymers, which can be easily functionalized for circularly polarized luminescence. The boroxine monomers are quantitatively synthesized in situ, both in bulk and in solution, from boronic acid precursors and cooperatively polymerize into 1D helical aggregates stabilized by threefold hydrogen-bonding and π-π stacking. We then demonstrate amplification of asymmetry in the co-assembly of chiral/achiral monomers and the co-condensation of chiral/achiral precursors in classical and in situ sergeant-and-soldiers experiments, respectively, showing fast boronic acid exchange reactions occurring in the system. Remarkably, co-condensation of pyrene boronic acid with a hydrogen-bonding chiral boronic acid results in chiral pyrene aggregation with circularly polarized excimer emission and g-values in the order of 10-3. Yet, the electron deficiency of boron in boroxine makes them chemically addressable by nucleophiles, but also sensitive to hydrolysis. With this sensitivity in mind, we provide first insights into the prospects offered by boroxine-based supramolecular polymers to make chemically addressable, functional, and adaptive systems.

Simultaneous measurements for fast neutron flux and tritium production rate using pulse shape discrimination and single crystal CVD diamond detector

This paper presents the development of a simultaneous measurement method for fast neutron energy spectra and tritium production rates within mixed radiation fields using a single crystal chemical vapour deposition diamond detector combined with a lithium fluoride (LiF) foil. The method involves the separation of pulses with rectangular shapes and the determination of the depth position within the single crystal diamond (SCD) struck by fast neutrons or nuclear reaction products including recoil tritons from the LiF foil based on pulse width, extracting pulse events occurred at the specific bulk region and the surface region of the SCD. Subsequently, unfolding techniques were employed to analyse the energy deposition spectrum of pulses at the specific bulk region which are induced only by fast neutrons, allowing the deduction of the fast neutron energy spectrum. To evaluate the tritium production rate, the energy deposition spectrum of pulses from events occurring at the SCD surface facing the LiF foil was analysed. By estimating the energy deposition spectrum solely induced by fast neutrons striking the SCD surface and subtracting it from the energy deposition spectrum of events at the SCD surface, the contribution of energetic ions, such as recoil tritons generated by the 6Li(n,α)3H reaction in the LiF foil, was determined. The fast neutron flux and tritium production rate obtained through this study were consistent with particle transport calculations, demonstrating the successful development of a method suitable for performance testing of fusion reactor blankets.