Highly Porous Renewable Carbons for Enhanced Storage of Energy-Related Gases (H2 and CO2) at High Pressures

Hydrochar, i.e., hydrothermally carbonized biomass, is generating great interest as a precursor for the synthesis of advanced carbon materials owing to economical, sustainability, and availability issues. Hereby, its versatility to produce adsorbents with a porosity adjusted to the targeted application, i.e., low or high pressure gas adsorption applications, is shown. Such tailoring of the porosity is achieved through the addition of melamine to the mixture hydrochar/KOH used in the activation process. Thereby, high surface area carbons (>3200 m2 g–1) with a bimodal porosity in the micromesopore range are obtained, whereas conventional KOH chemical activation leads to microporous materials (surface area <3100 m2 g–1). The micromesoporous materials thus synthesized show enhanced ability to store both H2 and CO2 at high pressure (≥20 bar). Indeed, the uptake capacities recorded at 20 bar, ca. 7 wt % H2 (−196 °C) and 19–21 mmol CO2 g–1 (25 °C) are among the highest ever reported for porous materials. Furthermore, the micromesoporous sorbents are far from saturation at 20 bar and achieve much higher CO2 uptake at 40 bar (up to 31 mmol of CO2 g–1; 25 °C) compared to 23 mmol of CO2 g–1 for the microporous materials. In addition, the micromesoporous materials show enhanced working capacities since the abundant mesoporosity ensures higher capture at high uptake pressure and the retention of lower amounts of adsorbed gas at the regeneration pressure used in PSA systems.This research work was supported by Spanish Ministerio de Economía y Competitividad, MINECO (MAT2012-31651), and by Fondo Europeo de Desarrollo Regional (FEDER). M. S. thanks the Ministerio de Ciencia e Innovación for her Ramón y Cajal contract. We thank the Rajamangala University of Technology Srivijaya (RMUTSV), Thailand for funding and a studentship for WS, and the Kingdom of Saudi Arabia for funding a PhD studentship for NB.Peer reviewe

Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning

Deep reinforcement learning methods have been shown to be potentially powerful tools for de novo design. Recurrent-neural-network-based techniques are the most widely used methods in this space. In this work we examine the behaviour of recurrent-neural-network-based methods when there are few (or no) examples of molecules with the desired properties in the training data. We find that targeted molecular generation is usually possible, but the diversity of generated molecules is often reduced and it is not possible to control the composition of generated molecular sets. To help overcome these issues, we propose a new curriculum-learning-inspired recurrent iterative optimization procedure that enables the optimization of generated molecules for seen and unseen molecular profiles, and allows the user to control whether a molecular profile is explored or exploited. Using our method, we generate specific and diverse sets of molecules with up to 18 times more scaffolds than standard methods for the same sample size; however, our results also point to substantial limitations of one-dimensional molecular representations, as used in this space. We find that the success or failure of a given molecular optimization problem depends on the choice of simplified molecular-input line-entry system (SMILES)

Immune responses to malaria pre-erythrocytic stages: Implications for vaccine development.

Radiation-attenuated sporozoites induce sterilizing immunity and remain the 'gold standard' for malaria vaccine development. Despite practical challenges in translating these whole sporozoite vaccines to large-scale intervention programmes, they have provided an excellent platform to dissect the immune responses to malaria pre-erythrocytic (PE) stages, comprising both sporozoites and exoerythrocytic forms. Investigations in rodent models have provided insights that led to the clinical translation of various vaccine candidates-including RTS,S/AS01, the most advanced candidate currently in a trial implementation programme in three African countries. With advances in immunology, transcriptomics and proteomics, and application of lessons from past failures, an effective, long-lasting and wide-scale malaria PE vaccine remains feasible. This review underscores the progress in PE vaccine development, focusing on our understanding of host-parasite immunological crosstalk in the tissue environments of the skin and the liver. We highlight possible gaps in the current knowledge of PE immunity that can impact future malaria vaccine development efforts

Hepatitis B virus seroepidemiology data for Africa:Modelling intervention strategies based on a systematic review and meta-analysis

BACKGROUND: International Sustainable Development Goals (SDGs) for elimination of hepatitis B virus (HBV) infection set ambitious targets for 2030. In African populations, infant immunisation has been fundamental to reducing incident infections in children, but overall population prevalence of chronic hepatitis B (CHB) infection remains high. In high-prevalence populations, adult catch-up vaccination has sometimes been deployed, but an alternative Test and Treat (T&T) approach could be used as an intervention to interrupt transmission. Universal T&T has not been previously evaluated as a population intervention for HBV infection, despite high-profile data supporting its success with human immunodeficiency virus (HIV). METHODS AND FINDINGS: We set out to investigate the relationship between prevalence of HBV infection and exposure in Africa, undertaking a systematic literature review in November 2019. We identified published seroepidemiology data representing the period 1995-2019 from PubMed and Web of Science, including studies of adults that reported prevalence of both hepatitis B surface antigen (HBsAg; prevalence of HBV infection) and antibody to hepatitis B core antigen (anti-HBc; prevalence of HBV exposure). We identified 96 studies representing 39 African countries, with a median cohort size of 370 participants and a median participant age of 34 years. Using weighted linear regression analysis, we found a strong relationship between the prevalence of infection (HBsAg) and exposure (anti-HBc) (R2 = 0.45, p < 0.001). Region-specific differences were present, with estimated CHB prevalence in Northern Africa typically 30% to 40% lower (p = 0.007) than in Southern Africa for statistically similar exposure rates, demonstrating the need for intervention strategies to be tailored to individual settings. We applied a previously published mathematical model to investigate the effect of interventions in a high-prevalence setting. The most marked and sustained impact was projected with a T&T strategy, with a predicted reduction of 33% prevalence by 20 years (95% CI 30%-37%) and 62% at 50 years (95% CI 57%-68%), followed by routine neonatal vaccination and prevention of mother to child transmission (PMTCT; at 100% coverage). In contrast, the impact of catch-up vaccination in adults had a negligible and transient effect on population prevalence. The study is constrained by gaps in the published data, such that we could not model the impact of antiviral therapy based on stratification by specific clinical criteria and our model framework does not include explicit age-specific or risk-group assumptions regarding force of transmission. CONCLUSIONS: The unique data set collected in this study highlights how regional epidemiology data for HBV can provide insights into patterns of transmission, and it provides an evidence base for future quantitative research into the most effective local interventions. In combination with robust neonatal immunisation programmes, ongoing PMTCT efforts, and the vaccination of high-risk groups, diagnosing and treating HBV infection is likely to be of most impact in driving advances towards elimination targets at a population level

First Results from The GlueX Experiment

The GlueX experiment at Jefferson Lab ran with its first commissioning beam in late 2014 and the spring of 2015. Data were collected on both plastic and liquid hydrogen targets, and much of the detector has been commissioned. All of the detector systems are now performing at or near design specifications and events are being fully reconstructed, including exclusive production of $\pi^{0}$, $\eta$ and $\omega$ mesons. Linearly-polarized photons were successfully produced through coherent bremsstrahlung and polarization transfer to the $\rho$ has been observed.Comment: 8 pages, 6 figures, Invited contribution to the Hadron 2015 Conference, Newport News VA, September 201

A hygrothermal modelling approach to water vapour sorption isotherm design for mesoporous humidity buffers

This paper describes the development of a design technique using hygrothermal numerical modelling for top-down predictive design and optimisation of water vapour sorption isotherms to match any humidity buffering application. This was used to inform the design and synthesis of two new mesoporous silica (MS) materials suitable for specific applications. To validate the technique, the new materials were experimentally assessed using gravimetric dynamic vapour sorption (DVS). The experimental isotherms closely matched the optimised isotherm predictions from the design stage, and a positive correlation was observed between the rate of change in adsorbed water content, Δw and the time taken to exceed the permissible upper limit of humidity, φi,U in a closed environment. A positive non-linear correlation was determined between the interior volumetric moisture load, ωml and the mass of adsorbent required to fully achieve humidity buffering between specified lower/ upper limits (φi,L and φi,U). The kinetics of water vapour sorption/ desorption were found to have general agreement when using the current hygrothermal numerical model. Current hygrothermal models appear to significantly underestimate the rate of adsorption/ desorption in rapid-response mesoporous silica type materials. This is perhaps largely due to the current lack of consideration for scanning curve prediction within hysteresis loops and so is a priority for future research