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The number of scientific articles published each year is rapidly growing and so is the number of academic journals. This makes it impossible for an individual practitioner or researcher to keep track of all research published in their own field or sub-discipline. With the growing amount of publications, it is also becoming more difficult to distinguish between similar papers published on the same topic, in the same journal, or by the same researchers (or research team). This perspective paper could support students and novice researchers, outlines the difference between the unique identifier for: (1) you as the researcher, (2) a specific paper; and (3) a specific journal. This paper further outlines the various numerical identifiers associated with academic publishing to help demystify academic publishing.

A series of group 1 hydrocarbon-soluble donor free aluminates [AM( tBuDHP)(TMP)Al( iBu) 2] (AM=Li, Na, K, Rb) have been synthesised by combining an alkali metal dihydropyridyl unit [(2- tBuC 5H 5N)AM)] containing a surrogate hydride (sp 3 C−H) with [( iBu) 2Al(TMP)]. These aluminates have been characterised by X-ray crystallography and NMR spectroscopy. While the lithium aluminate forms a monomer, the heavier alkali metal aluminates exist as polymeric chains propagated by non-covalent interactions between the alkali metal cations and the alkyldihydropyridyl units. Solvates [(THF)Li( tBuDHP)(TMP)Al( iBu) 2] and [(TMEDA)Na( tBuDHP)(TMP)Al( iBu) 2] have also been crystallographically characterised. Theoretical calculations show how the dispersion forces tend to increase on moving from Li to Rb, as opposed to the electrostatic forces of stabilization, which are orders of magnitude more significant. Having unique structural features, these bimetallic compounds can be considered as starting points for exploring unique reactivity trends as alkali-metal-aluminium hydride surrog[ATES].

The growth in information technology and computer capacity has opened up opportunities to deal with much and much larger data sets than even a decade ago. There has been a technological revolution of big data and Artificial Intelligence (AI). Perhaps many readers would immediately think about robotic surgery or self-driving cars, but there is much more to AI. This Short Communication starts with an overview of the key terms, including AI, machine learning, deep learning and Big Data. This Short Communication highlights so developments of AI in health that could benefit a low-income country like Nepal and stresses the need for Nepal’s health and education systems to track such developments and apply them locally. Moreover, Nepal needs to start growing its own AI expertise to help develop national or South Asian solutions. This would require investing in local resources such as access to computer power/capacity as well as training young Nepali to work in AI.

pH dependence abounds in biochemical systems; however, many simulation methods used to investigate these systems do not consider this property. Using a modified version of the hybrid non-equilibrium molecular dynamics (MD)/Monte Carlo algorithm, we include a stochastic charge neutralization method, which is particularly suited to the MARTINI force field and enables artifact-free Ewald summation methods in electrostatic calculations. We demonstrate the efficacy of this method by reproducing pH-dependent self-assembly and self-organization behavior previously reported in experimental literature. In addition, we have carried out experimental oleic acid titrations where we report the results in a more relevant way for the comparison with computational methods than has previously been done.

Academic writing, especially in the health field, is usually an interdisciplinary team effort. This paper highlights some of the trials, tribulations, and benefits of working with co-authors. This includes collaborations and co-authorship between academics from different disciplines, academics of different level of careers, and authors from countries of varying economies i.e., high-income countries (HICs) and from low-and middle-income countries (LMICs). This paper also provides advice in the form of several useful tips to lead authors and co-authors to support collaborative working.

The absolute stereochemistry of the marine alkaloid (

Self-assembling peptide nanostructures have been shown to be of great importance in nature and have presented many promising applications, for example, in medicine as drug-delivery vehicles, biosensors, and antivirals. Being very promising candidates for the growing field of bottom-up manufacture of functional nanomaterials, previous work (Frederix, et al. 2011 and 2015) has screened all possible amino acid combinations for di- and tripeptides in search of such materials. However, the enormous complexity and variety of linear combinations of the 20 amino acids make exhaustive simulation of all combinations of tetrapeptides and above infeasible. Therefore, we have developed an active machine-learning method (also known as "iterative learning" and "evolutionary search method") which leverages a lower-resolution data set encompassing the whole search space and a just-in-time high-resolution data set which further analyzes those target peptides selected by the lower-resolution model. This model uses newly generated data upon each iteration to improve both lower- and higher-resolution models in the search for ideal candidates. Curation of the lower-resolution data set is explored as a method to control the selected candidates, based on criteria such as log P. A major aim of this method is to produce the best results in the least computationally demanding way. This model has been developed to be broadly applicable to other search spaces with minor changes to the algorithm, allowing its use in other areas of research.

Materials that combine the functionalities of both of proteins and graphene are of great interest for the engineering of biosensing, drug delivery, and regenerative devices. Graphene oxide (GO) offers an opportunity to design GO‐protein interactions but the need for harsh reduction processes to enable GO photoexcitation remains a limitation. A disinfector‐assisted low temperature method to reduce GO‐protein materials and fabricate surgical dressings with tuneable photothermal efficiency and bioactive properties for the postoperative treatment of melanoma is reported. The approach harnesses the capacity of 70% ethanol to penetrate the protein shell of microorganisms to infiltrate GO‐protein complexes and reduce GO at low temperature (85 °C) while maintaining the material structure and bioactivity. Both experiments and coarse‐grained simulations are used to describe the reduction process and assess the material properties. In vitro and in vivo validation revealed the capacity of the dressings to prevent tumor recurrence and promote healing after tumor resection.

Currently, there is a drive to develop the organoelement chemistry of sodium, the most abundant alkali metal on earth, as an alternative to that of rarer lithium, with the prime focus on sustainability. Organolithium compounds have been essential to the success of synthetic chemistry for more than a century, although their implementation has been essentially confined to stoichiometric synthesis. Here, we report on synthetic, structural, catalytic, mechanistic, and theoretical studies of a series of sodium diphenylphosphides, having unique structures defined by the Lewis base donor D solvating the Lewis acidic sodium cation. These donor complexes are explored as hydrophosphination catalysts on reacting Ph 2P–H with a range of alkynes and prove to be generally effective under ambient conditions, especially when n = 1 in [{Ph 2PNa(D) x} n]. Density functional theory (DFT) studies have shed light on the possible mechanisms of these catalytic cycles and how they relate to the E, Z, or α isomer formed.

We investigate the phase-transition behaviour of nickel nanoparticles (3 - 6 nm) via dynamic TEM. The nanoparticles were synthesized within a reverse microemulsion and then monitored via dynamic TEM simultaneously while undergoing controlled heating. The size-dependent melting point depression experimentally observed is compared with, and is in good agreement with existing thermodynamic and molecular dynamic predictions.