Selective photooxidation of aromatic alcohols to corresponding aldehydes is a widely used model reaction for evaluation of performance of heterogeneous photocatalysts. A chief example is the photocatalytic production of hydrogen peroxide via reduction of dioxygen with concomitant photooxidation of benzyl alcohol to benzaldehyde. Although it has long been known that photoexcitation of benzaldehyde under UV light yields reactive benzaldehyde radicals capable of oxidizing substrates such as benzyl alcohol, it was assumed that such autocatalytic processes cannot be initiated under visible light irradiation. Herein we demonstrate the ability of benzaldehyde to promote auto-photocatalytic oxidation of benzyl alcohol and produce large quantities of H2O2 in solvent-free (no water) or biphasic (with water) systems even under nominally solar-simulated visible light (>420 nm cutoff filter) irradiation. While these results open up broader prospects for the use of benzaldehyde in visible light-driven photocatalysis as exemplified by the ability of benzaldehyde to photocatalyze H2O2 production even in the presence of alternative electron donors (e.g., ethanol), they also shed some critical light on the plethora of research reports on photocatalytic H2O2 production in which benzyl alcohol was employed as electron donor. Since the autocatalytic pathway based on the photocatalytic activity of benzaldehyde formed during photocatalysis under such conditions cannot be neglected, the interpretations of photocatalytic performance are likely contentious and distorted in such reports. We conclude that the use of benzyl alcohol as a model electron donor in photocatalytic studies should be definitely discouraged, and highlight the importance of carrying out simple check protocols for excluding similar issues when using alternative substrates.

Pandemics create survival uncertainty through infection possibilities, food scarcity, and unemployment. Being the largest democracy in the world, we have explored the response of Indian citizens on the COVID-19's lockdown and defined an anxiety response model using PLS based Structural Equation Modeling(SEM). For a comprehensive understanding, we have measured the response at two levels of individual and government. Though the types of anxieties are related, we observed that a specific response is linked with a specific type of anxiety and all responses are not anxiety-driven. We have found that the response mechanism of Health and Food anxieties follow very different paths and that the role of information is not significant in all anxieties. Our results will help policymakers in understanding how to respond to a crisis and optimize policy implementation accordingly. It will further help the scholars understand the difference in the anxieties caused by the pandemic and the layers of responses individuals take in such situations.

Investments in new ventures are risky due to lack of conventional form of quantitative information and untested products. Venture capitalists (VCs) are seen to target such new ventures for high-risk premium but with little success. Existing research has investigated and identified a variety of qualitative factors that impact VCs’ investment decisions; however, many research gaps still exist. Works published in the last two decades show the evolution in the preference of factors with the focus shifting from venture’s team and product to factors such as intellectual property rights, economic crisis and social capital. It was found that the factor’s role was limited to the binary scale (positive and negative), which undermines its effect. The purpose of this review is to provide a comprehensive framework of factors that influence VCs’ investment decisions and show theoretical research gaps. Accordingly, we have segmented factors into two macro-categories: ‘internal’ and ‘external environment’, and presented a detailed framework of the factors that influence VCs’ investment decisions. Further, we argue to consider the subjectivity of qualitative factors and to explore the role of a factor in the decision-making.

This study measures an individual's evaluation of the situation of COVID‐19 and the result of such an evaluation on their business venturing decision. We have considered a three‐step model of exposure–evaluation–action using partial least squares (PLS)‐based structural equation modeling with a sample of 497 working‐class members and small business owners. Unlike previous researches on “economic uncertainty,” our results show that the systemic economic uncertainty during COVID‐19 inhibited business venturing. This was caused by the negative opportunity cost due to higher sustenance costs during the pandemic. We further found that “entrepreneurial intent” independently did not lead to business venturing, but the act of venturing depended on the recognition of opportunity.

Light-driven production of hydrogen peroxide via selective dioxygen reduction is an attractive “green” alternative to the conventionally used anthraquinone process. One of the most promising classes of photocatalytic materials for this conversion that excels by high selectivity, chemical stability and low cost is represented by polymeric carbon nitrides, and particularly by various types of poly(heptazine imide) (PHI), i.e., ionic variants of carbon nitride. A crucial challenge highlighted by recent studies is the problem of separation of formed H2O2 from the reaction medium and especially from the suspended photocatalyst particles since photocatalytically generated H2O2 can undergo light-driven decomposition, as well as disproportionation on the surface of the photocatalyst in the dark. Herein, we report an elegant solution to this problem by implementing a biphasic reaction system in which the hydrophobic photocatalyst oxidizes a lipophilic electron donor in the organic phase, while the produced H2O2 is instantaneously extracted into the aqueous layer. To this end, we have achieved an effective hydrophobization of ionic carbon nitride (PHI) nanoparticles in the form of a composite with alkylated silica. The hydrophobized composite effectively photocatalyzes the reduction of dioxygen to H2O2 with concurrent oxidation of a model fatty alcohol (1-octanol) in the organic phase under visible light irradiation (406 nm LED), and enables, at the same time, facile separation of the high-value H2O2/water mixture from the reaction medium at H2O2 concentrations (~0.12 M) that are unprecedentedly high for light-driven systems reported in the literature. Notably, fatty alcohols are readily available from vegetable waxes and as pulping sub-products, and the products of their partial oxidation represent a valuable feedstock for the synthesis of pharmaceuticals and cosmetic products. This work thus showcases a rational design of a high-performance photocatalytic system for H2O2 production that enables easy separation of the product from electron donors and its recovery at high concentrations, and paves the way for sustainable and economically viable light-driven H2O2 production from easily available feedstock.

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