Atomistic molecular dynamics simulation and COSMO-SAC approach for enhanced 1,3-propanediol extraction with imidazolium-based ionic liquids

CONTEXT

1,3-Propanediol (1,3-PDO) is a key chemical in various industries, including pharmaceuticals and material sciences, and is projected to see significant market growth. However, the current challenges in its downstream processing, particularly in terms of cost and efficiency, highlight the need for innovative solutions. Our study delves into using ionic liquids (ILs) as a potential alternative, aiming to address these critical separation challenges more sustainably and efficiently. In this study, we utilized molecular dynamics (MD) simulations and the COSMO-SAC to examine 1,3-propanediol (1,3-PDO) extraction using four imidazolium-based ionic liquids with 1-butyl-3-methylimidazolium [Bmim] cation and with different anions bis(pentafluoroethanesulfonyl)imide [NPF2]-, bis(trifluoromethylsulfonyl)imide [NTF2]-, thiocyanate [SCN]-, and trifluoromethanesulfonate [TFO]-. Molecular dynamics simulations, incorporating analysis of radial distribution functions (RDF) and spatial distribution functions (SDF), revealed that [Bmim][SCN] and [Bmim][TFO] exhibit enhanced interactions with 1,3-PDO. Notably, [Bmim][SCN] formed the most hydrogen bonds, averaging 1.639 per molecule, due to its coordinating [SCN]- anion. This was in contrast to the fewer hydrogen bonds formed by non-coordinating anions in [Bmim][NPF2] and [Bmim][NTF2]. In ternary systems, [Bmim][SCN] and [Bmim][TFO] demonstrated superior selectivity for 1,3-PDO extraction compared to the other ionic liquids, with selectivity values around 29. These findings, supported by COSMO-SAC predictive modeling, highlight the potential of [Bmim][SCN] as a promising candidate for 1,3-PDO extraction, emphasizing the importance of anion selection in optimizing ionic liquid properties for this application.

METHODS

In our study, we employed MD simulations, incorporating the OPLS-AA force field, and COSMO-SAC to investigate the extraction of 1,3-PDO using imidazolium-based ionic liquids: [Bmim][NTF2], [Bmim][NPF2], [Bmim][SCN], and [Bmim][TFO]. The MD simulations were conducted using LAMMPS software, focusing on elucidating the RDF, SDF, and hydrogen bonding. Analysis of the distribution coefficient (β) and selectivity (S) for the ternary mixture was also conducted. These aspects of the simulation were analyzed using TRAVIS and VMD software. Additionally, the COSMO-SAC model was employed to determine the activity coefficients of 1,3-PDO in the ionic liquids, with molecular optimization conducted using Gaussian16 and sigma profile calculations performed using COSMO-SAC.

North-south scientific collaborations on research datasets: a longitudinal analysis of the division of labor on genomic datasets (1992-2021)

Collaborations between scientists from the global north and global south (N-S collaborations) are a key driver of the "fourth paradigm of science" and have proven crucial to addressing global crises like COVID-19 and climate change. However, despite their critical role, N-S collaborations on datasets are not well understood. Science of science studies tend to rely on publications and patents to examine N-S collaboration patterns. To this end, the rise of global crises requiring N-S collaborations to produce and share data presents an urgent need to understand the prevalence, dynamics, and political economy of N-S collaborations on research datasets. In this paper, we employ a mixed methods case study research approach to analyze the frequency of and division of labor in N-S collaborations on datasets submitted to GenBank over 29 years (1992-2021). We find: (1) there is a low representation of N-S collaborations over the 29-year period. When they do occur, N-S collaborations display "burstiness" patterns, suggesting that N-S collaborations on datasets are formed and maintained reactively in the wake of global health crises such as infectious disease outbreaks; (2) The division of labor between datasets and publications is disproportionate to the global south in the early years, but becomes more overlapping after 2003. An exception in the case of countries with lower S&T capacity but high income, where these countries have a higher prevalence on datasets (e.g., United Arab Emirates). We qualitatively inspect a sample of N-S dataset collaborations to identify leadership patterns in dataset and publication authorship. The findings lead us to argue there is a need to include N-S dataset collaborations in measures of research outputs to nuance the current models and assessment tools of equity in N-S collaborations. The paper contributes to the SGDs objectives to develop data-driven metrics that can inform scientific collaborations on research datasets.

Measuring the Concept of PID Literacy: User Perceptions and Understanding of PIDs in Support of Open Scholarly Infrastructure

The increasing centrality of persistent identifiers (PIDs) to scholarly ecosystems and the contribution they can make to the burgeoning “PID graph” has the potential to transform scholarship. Despite their importance as originators of PID data, little is known about researchers’ awareness and understanding of PIDs, or their efficacy in using them. In this article, we report on the results of an online interactive test designed to elicit exploratory data about researcher awareness and understanding of PIDs. This instrument was designed to explore recognition of PIDs (e.g. Digital Object Identifiers [DOIs], Open Researcher and Contributor IDs [ORCIDs], etc.) and the extent to which researchers correctly apply PIDs within digital scholarly ecosystems, as well as measure researchers’ perceptions of PIDs. Our results reveal irregular patterns of PID understanding and certainty across all participants, though statistically significant disciplinary and academic job role differences were observed in some instances. Uncertainty and confusion were found to exist in relation to dominant schemes such as ORCID and DOIs, even when contextualized within real-world examples. We also show researchers’ perceptions of PIDs to be generally positive but that disciplinary differences can be noted, as well as higher levels of aversion to PIDs in specific use cases and negative perceptions where PIDs are measured on an “activity” semantic dimension. This work therefore contributes to our understanding of scholars’ “PID literacy” and should inform those designing PID-centric scholarly infrastructures that a significant need for training and outreach to active researchers remains necessary.

The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central

Science across all disciplines has become increasingly data-driven, leading to additional needs with respect to software for collecting, processing and analysing data. Thus, transparency about software used as part of the scientific process is crucial to understand provenance of individual research data and insights, is a prerequisite for reproducibility and can enable macro-analysis of the evolution of scientific methods over time. However, missing rigor in software citation practices renders the automated detection and disambiguation of software mentions a challenging problem. In this work, we provide a large-scale analysis of software usage and citation practices facilitated through an unprecedented knowledge graph of software mentions and affiliated metadata generated through supervised information extraction models trained on a unique gold standard corpus and applied to more than 3 million scientific articles. Our information extraction approach distinguishes different types of software and mentions, disambiguates mentions and outperforms the state-of-the-art significantly, leading to the most comprehensive corpus of 11.8 M software mentions that are described through a knowledge graph consisting of more than 300 M triples. Our analysis provides insights into the evolution of software usage and citation patterns across various fields, ranks of journals, and impact of publications. Whereas, to the best of our knowledge, this is the most comprehensive analysis of software use and citation at the time, all data and models are shared publicly to facilitate further research into scientific use and citation of software.

Nonvolatile taste compounds of Shanghai smoked fish: A novel three stages control techniques

In this work, the effect of processing stages including first soaking (FS), frying after first soaking (FFS), and second soaking (SS) on nonvolatile taste compounds of Shanghai smoked fish was investigated using high-performance liquid chromatography (HPLC) and automatic amino acid analyzer. Results showed that the contents of free amino acids (FAAs) ranged from 396.94 to 585.79 mg/100 g and 5'-inosine monophosphate (IMP, as main umami nucleotide) from 215.91 to 284.56 mg/100 g in Shanghai smoked fish, respectively. Moreover, the contents of Glu and Gly as main umami amino acids ranged from 1.64 to 107.32 mg/100 g and 61.61 to 108.88 mg/100 g, respectively. TAV values of IMP, Asp, and Glu in Shanghai smoked fish reached 11.38, 2.73, and 21.46, respectively. The obvious difference could be observed using principal component analysis (PCA) in three processing stages of Shanghai smoked fish. Therefore, probing into the nonvolatile flavor of Shanghai smoked fish could not only enrich the theoretical basis of flavor chemistry in freshwater fish fields, but probe into the formation mechanisms of taste compounds in further study.

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin.

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin.