Enhanced laser-induced damage performance of all-glass metasurfaces for energetic pulsed laser applications.

To fabricate optical components with surface layers compatible with high-power laser applications that may operate as antireflective coatings, polarization rotators, or harness physical anisotropy for other uses, metasurfaces are becoming an appealing candidate. In this study, large-beam (1.05 cm diameter) 351-nm laser-induced damage testing was performed on an all-glass metasurface structure composed of cone-like features with a subwavelength spacing of adjacent features. These structures were fabricated on untreated fused silica glass and damage tested, as were structures that were fabricated on fused silica glass that experienced a preliminary etching process to remove the surface Beilby layer that is characteristic of polished fused silica. The laser-induced damage onset for structures on untreated fused silica glass was 19.3J⋅c m -2, while the sample that saw an initial pretreatment etch exhibited an improved damage onset of 20.4J⋅c m -2, only 6% short of the reference pretreated glass damage onset of 21.7J⋅c m -2. For perspective, the National Ignition Facility operational average fluence at this wavelength and pulse length is about 10J/c m 2. At a fluence of 25.5J⋅c m -2, the reference (pretreated) fused silica initiated 5.2 damage sites per m m 2, while the antireflective metasurface sample with a preliminary etching process treatment initiated 9.8 damage sites per m m 2. These findings demonstrate that substrate-engraved metasurfaces are compatible with high energy and power laser applications, further broadening their application space.

The Influence of Comorbidities, General Health Status, and Self-Care Self-Efficacy on COVID-19 Symptoms During the Omicron Wave.

Background The emergence of the less virulent COVID-19 strains such as Omicron and its subvariants shifted the paradigm of COVID-19 treatment from inpatient treatment to regular outpatient care. The individual health determinants affecting COVID-19 disease severity among vulnerable adults treated in outpatient settings are an under-researched area. Methods This study conducted in an outpatient COVID-19 antibody infusion center employed a cross-sectional survey design to explore the impact of comorbidities, general health status, and self-care self-efficacy on COVID-19 symptom severity. We recruited 120 COVID-19-positive participants over 40 years of age, of which 117 completed the study with 87 providing complete data. After the screening and consenting process, the participants completed the following surveys in a secure REDCap survey software (Vanderbilt University, Nashville, USA) on an iPad (Apple Inc., Cupertino, USA): 1) sociodemographic questionnaire, 2) Charlson Comorbidity Index (CCI) to capture comorbidities, 3) Medical Outcomes Study Short-Form (SF-12) to assess general health including physical (PCS) and mental (MCS) health subscales, 4) Self-Care Self-Efficacy Scale (SCSES) to measure self-care self-efficacy, and 5) the COVID-19 Symptom rating scale (COVID-19 SRS). Statistical analysis used were Chi-square and Pearson correlations.  Results As evidenced by CCI, the top five comorbidities were hypertension (42%), diabetes mellitus (31%), pulmonary disease (19%), depression (14%), and solid tumors (11%). Age was statistically significantly correlated to comorbidity burden (p<0.0001). Severe COVID-19 symptoms reported were fatigue, myalgia, cough, runny nose, and sore throat. The general health status measure (SF-12) subscales showed that the patient's mental component summary (MCS) was more statistically significant to COVID-19 symptom severity than the physical component summary (PCS). The MCS demonstrated a statistically significant correlation with fatigue and myalgia (p<0.0001), headache and breathing difficulties (p<0.001), nausea/vomiting (p<0.01), and abdominal pain/diarrhea (p<0.05). The PCS showed a lesser statistically significant correlation with fatigue, myalgia, headaches (p<0.01), fever/chills, cough, congestion/runny nose, night sweats, breathing difficulties, nausea/vomiting, and abdominal pain/diarrhea (p<0.05). Interestingly, the 'loss of smell' which is the hallmark symptom of COVID-19 was the only symptom that showed a statically significant correlation with the Charlson Comorbidity Index (p<0.05), and it did not show any association with either mental (SF-12 MCS) or physical (SF-12 PCS) health status. The SF-12 MCS also showed a statistically significant correlation with a diagnosis of depression (p< 0.01), validating it as a true measure of mental health among vulnerable adults. The SCSES was not correlated with any of the COVID-19 symptoms. Conclusions The patient's general health status, especially mental health was more statistically significant to COVID-19 symptoms. The COVID-19 hallmark symptom of 'loss of smell' was the only symptom that showed statistical significance with comorbidities. Within the limitations of a cross-sectional survey design and convenient sampling methods, this study calls to tailor general health status, especially mental health, and cumulative comorbidity burden to risk assessment/risk stratification of COVID-19 care.

Birefringent Glass-Engraved Tilted Pillar Metasurfaces for High Power Laser Applications.

Birefringent materials-which are highly needed in high power laser systems-may be limited in usage due to the laser-induced damage threshold of traditional birefringent materials. This work reports here on all-glass metasurfaces, fabricated by angled etching through sacrificial metal nanoparticle (NP) etching masks, for generation of effective birefringence in the formed layer. As a result, a fused silica metasurface, monolithic to the underlying substrate, is demonstrated to exhibit a birefringence of 6.57° under 375 nm illumination. Full-wave analysis shows a good agreement with the measurement and presents potential paths forward to increasing the effective metasurface birefringence. This is the first demonstration, to the best of knowledge, of an etching technique to obtain the resulting tilted pillar-like nanofeatures. The anisotropy of the metasurface nanoelements along the two window in-plane major axes presents different effective paths for the two polarizations and thus generates birefringence in a nonbirefringent material. Additionally, the imparted anisotropy lends itself to manipulation of physical properties of the surface as well, with metasurface feature orientation suppressing water flow along one principal axis and giving rise to water flow steering capabilities.

Femtosecond damage experiments and modeling of broadband mid-infrared dielectric diffraction gratings.

High peak and average power lasers with high wall-plug efficiency, like the Big Aperture Thulium (BAT) laser, have garnered tremendous attention in laser technology. To meet the requirements of the BAT laser, we have developed low-dispersion reflection multilayer dielectric (MLD) gratings suitable for compression of high-energy pulses for operations at 2 micron wavelength. We carried out 10000-on-1 damage tests to investigate the fluence damage thresholds of the designed MLD gratings and mirrors, which were found between 100-230 mJ/cm2. An ultrashort pulsed laser (FWHM = 53 fs, λ = 1.9 µm) operating at 500 Hz was used in the serpentine raster scans. The atomic force microscope images of the damage sites show blister formation of the underlying layers at lower fluences but ablation of the grating pillars at higher fluences. We simulated the dynamic electronic excitation in the MLD optics with a finite-difference in the time domain approach in 2D. The simulation results agree well with the LIDT measurements and the observed blister formation. This model is able to evaluate the absolute LIDT of MLD gratings.

Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy.

The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects.

Coupling buried etalon layers to an engraved metasurface for durable and large-aperture meta-optics.

Many optical applications that could potentially benefit from the design flexibility provided by the metasurface approach are being prohibited by the limited scalability of the fabrication and the robustness of the end-result structures when using a resonant meta-elements-based approach. An alternative demonstrated approach with superior scalability and robustness is substrate-engraved metasurfaces, based on medium mixing homogenization, yet it suffers from very limited optical response. Here we propose advancing this approach by coupling the metasurface with buried etalon layers, leading to enhancement in the optical response. A transfer matrix analysis is used to study the parameter space, predicting that the patterned reflectance values range of a beam shaper could be raised from only 4% to 30% when the metasurface is engraved in silica, and even up to 66% when engraved into higher-index oxides. Using the method proposed here, the phase difference range across the metasurface could be increased by 0.4 radians beyond the range achievable by a metasurface engraved in silica and could reach even higher values when embedded in higher-index materials. Full-wave numerical simulations are used to demonstrate a cylindrical metareflector and a metalens, further validating the analysis.

Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts.

To reveal post-traumatic stress disorder (PTSD) genetic risk influences on tissue-specific gene expression, we use brain and non-brain transcriptomic imputation. We impute genetically regulated gene expression (GReX) in 29,539 PTSD cases and 166,145 controls from 70 ancestry-specific cohorts and identify 18 significant GReX-PTSD associations corresponding to specific tissue-gene pairs. The results suggest substantial genetic heterogeneity based on ancestry, cohort type (military versus civilian), and sex. Two study-wide significant PTSD associations are identified in European and military European cohorts; ZNF140 is predicted to be upregulated in whole blood, and SNRNP35 is predicted to be downregulated in dorsolateral prefrontal cortex, respectively. In peripheral leukocytes from 175 marines, the observed PTSD differential gene expression correlates with the predicted differences for these individuals, and deployment stress produces glucocorticoid-regulated expression changes that include downregulation of both ZNF140 and SNRNP35. SNRNP35 knockdown in cells validates its functional role in U12-intron splicing. Finally, exogenous glucocorticoids in mice downregulate prefrontal Snrnp35 expression.

Scalable Light-Printing of Substrate-Engraved Free-Form Metasurfaces.

A key challenge for metasurface research is locally controlling at will the nanoscale geometric features on meter-scale apertures. Such a technology is expected to enable large aperture meta-optics and revolutionize fields such as long-range imaging, lasers, laser detection and ranging (LADAR), and optical communications. Furthermore, these applications are often more sensitive to light-induced and environmental degradation, which constrains the possible materials and fabrication process. Here, we present a relatively simple and scalable method to fabricate a substrate-engraved metasurface with locally printed index determined by induced illumination, which, therefore, addresses both the challenges of scalability and durability. In this process, a thin metal film is deposited onto a substrate and transformed into a mask via local laser-induced dewetting into nanoparticles. The substrate is then dry-etched through this mask, and selective mask removal finally reveals the metasurface. We show that masking by the local nanoparticle distribution, and, therefore, the local index, is dependent on the local light-induced dewetting temperature. We demonstrate printing of a free-form pattern engraved into a fused silica glass substrate using a laser raster scan. Large-scale spatially controlled engraving of metasurfaces has implications on other technological fields beyond optics, such as surface fluidics, acoustics, and thermomechanics.

The Role of Water in Mediating Interfacial Adhesion and Shear Strength in Graphene Oxide.

Graphene oxide (GO), whose highly tunable surface chemistry enables the formation of strong interfacial hydrogen-bond networks, has garnered increasing interest in the design of devices that operate in the presence of water. For instance, previous studies have suggested that controlling GO's surface chemistry leads to enhancements in interfacial shear strength, allowing engineers to manage deformation pathways and control failure mechanisms. However, these previous reports have not explored the role of ambient humidity and only offer extensive chemical modifications to GO's surface as the main pathway to control GO's interfacial properties. Herein, through atomic force microscopy experiments on GO-GO interfaces, the adhesion energy and interfacial shear strength of GO were measured as a function of ambient humidity. Experimental evidence shows that adhesion energy and interfacial shear strength can be improved by a factor of 2-3 when GO is exposed to moderate (∼30% water weight) water content. Furthermore, complementary molecular dynamics simulations uncovered the mechanisms by which these nanomaterial interfaces achieve their properties. They reveal that the strengthening mechanism arises from the formation of strongly interacting hydrogen-bond networks, driven by the chemistry of the GO basal plane and intercalated water molecules between two GO surfaces. In summary, the methodology and findings here reported provide pathways to simultaneously optimize GO's interfacial and in-plane mechanical properties, by tailoring the chemistry of GO and accounting for water content, in engineering applications such as sensors, filtration membranes, wearable electronics, and structural materials.

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders.

BACKGROUND: Integrating rare variation from trio family and case-control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified. METHODS: We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls). RESULTS: For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ>0.55), but low between SCZ and the NDDs (ρ<0.3). An in-depth analysis of 288 NDD genes shows there is highly significant protein-protein interaction (PPI) network connectivity, and functionally distinct PPI subnetworks based on pathway enrichment, single-cell RNA-seq cell types, and multi-region developmental brain RNA-seq. CONCLUSIONS: We have extended a pipeline used in ASD studies and applied it to infer rare genetic parameters for SCZ and four NDDs ( https://github.com/hoangtn/extTADA ). We find many new DD risk genes, supported by gene set enrichment and PPI network connectivity analyses. We find greater similarity among NDDs than between NDDs and SCZ. NDD gene subnetworks are implicated in postnatally expressed presynaptic and postsynaptic genes, and for transcriptional and post-transcriptional gene regulation in prenatal neural progenitor and stem cells.

Optically Assisted Surface Functionalization for Protein Arraying in Aqueous Media.

Protein surface patterning is employed in a broad spectrum of applications ranging from protein microarray analysis to 2D cell organization. However, limitations arise because of the highly sensitive nature of proteins requiring careful handling to ensure their structural and functional integrity during the grafting process. Here, we describe a patterning protocol that keeps proteins in an aqueous environment during their immobilization, avoiding the loss of their biological activity. The procedure is based on the UV-mediated removal of polyethylene glycol self-assembled monolayers in a transparent microfluidic chamber, giving access to micrometric motifs of predefined geometries. Afterward, modified proteins can be grafted on the photopatterned domains. We also studied the influence of reactive oxygen species for a better understanding of the chemical mechanism involved in this process. Finally, as a proof of concept, a protein microarray was created with this process using cell-capturing antibodies to immobilize human blood cells, confirming the functionality of the arrayed proteins.

SRBreak: A Read-Depth and Split-Read Framework to Identify Breakpoints of Different Events Inside Simple Copy-Number Variable Regions.

Copy-number variation (CNV) has been associated with increased risk of complex diseases. High-throughput sequencing (HTS) technologies facilitate the detection of copy-number variable regions (CNVRs) and their breakpoints. This helps in understanding genome structure as well as their evolution process. Various approaches have been proposed for detecting CNV breakpoints, but currently it is still challenging for tools based on a single analysis method to identify breakpoints of CNVs. It has been shown, however, that pipelines which integrate multiple approaches are able to report more reliable breakpoints. Here, based on HTS data, we have developed a pipeline to identify approximate breakpoints (±10 bp) relating to different ancestral events within a specific CNVR. The pipeline combines read-depth and split-read information to infer breakpoints, using information from multiple samples to allow an imputation approach to be taken. The main steps involve using a normal mixture model to cluster samples into different groups, followed by simple kernel-based approaches to maximize information obtained from read-depth and split-read approaches, after which common breakpoints of groups are inferred. The pipeline uses split-read information directly from CIGAR strings of BAM files, without using a re-alignment step. On simulated data sets, it was able to report breakpoints for very low-coverage samples including those for which only single-end reads were available. When applied to three loci from existing human resequencing data sets (NEGR1, LCE3, IRGM) the pipeline obtained good concordance with results from the 1000 Genomes Project (92, 100, and 82%, respectively). The package is available at https://github.com/hoangtn/SRBreak, and also as a docker-based application at https://registry.hub.docker.com/u/hoangtn/srbreak/.

Health Disparities Influence Childhood Melanoma Stage at Diagnosis and Outcome.

OBJECTIVE: To identify health disparities in pediatric patients with melanoma that affect disease presentation and outcome. STUDY DESIGN: This was a retrospective cohort study of all persons aged ≤18 years diagnosed with melanoma and enrolled in the Texas Cancer Registry between 1995 and 2009. Socioeconomic status (SES) and driving distance to the nearest pediatric cancer treatment center were calculated for each patient. Logistic regression was used to determine factors associated with advanced-stage disease. Life table methods and Cox regression were used to estimate survival probability and hazard ratios. RESULTS: A total of 185 adolescents (age >10 years) and 50 young children (age ≤10 years) were identified. Hispanics (n = 27; 12%) were 3 times more likely than non-Hispanic whites (n = 177; 75%) to present with advanced disease (OR, 3.8; 95% CI, 1.7-8.8). Young children were twice as likely as adolescents to present with advanced disease (OR, 2.2; 95% CI, 1.1-4.3). Distance to treatment center and SES did not affect stage of disease at presentation. Hispanics and those in the lowest SES quartile had a significantly higher mortality risk (hazard ratios, 3.0 [95% CI, 1.2-7.8] and 4.3 [95% CI, 1.4-13.9], respectively). In the adjusted survival model, only advanced disease was predictive of mortality (P < .001). CONCLUSION: Hispanics and young children with melanoma are more likely to present with advanced disease, and advanced disease is the single most important predictor of survival. Heightened awareness among physicians is needed to facilitate early detection of melanoma within these groups.

The Impact of Socioeconomic Status on Appendiceal Perforation in Pediatric Appendicitis.

OBJECTIVE: To assess the impact of socioeconomic status (SES) on pediatric appendicitis outcomes using the validated Agency for Healthcare Research and Quality (AHRQ) SES Index and incorporating block-group data. STUDY DESIGN: We reviewed all patients <18 years old who underwent appendectomy for acute appendicitis from 2009-2013 at our institution. Patient addresses were geocoded and linked to 2010 US Census SES block-group data to determine composite AHRQ SES Index scores based on 7 publically reported SES variables. The primary outcome was appendiceal perforation, and the impact of SES scores, age, race, and insurance status on perforation rates were assessed through regression analyses. RESULTS: Of 1501 patients, 510 (34%) had perforated appendicitis. On bivariate analysis, components of the SES Index associated with an increased perforation rate included lower household income, lower percentage of adults with college education, and higher percentage of adults with <12th grade education (all P < .05). On multivariate analysis, age ≤ 10 years (OR 1.7, 95% CI 1.4-2.2) and public insurance (OR 1.5, 95% CI 1.2-2.0) were associated with increased odds of perforation. CONCLUSIONS: This study used the AHRQ SES scoring system to evaluate SES and its influence on appendiceal perforation. Among our cohort of pediatric patients, the risk of perforation was multifactorial, and younger age and public insurance were stronger predictors of perforation than SES.

Active cooling of pulse compression diffraction gratings for high energy, high average power ultrafast lasers.

Laser energy absorption and subsequent heat removal from diffraction gratings in chirped pulse compressors poses a significant challenge in high repetition rate, high peak power laser development. In order to understand the average power limitations, we have modeled the time-resolved thermo-mechanical properties of current and advanced diffraction gratings. We have also developed and demonstrated a technique of actively cooling Petawatt scale, gold compressor gratings to operate at 600W of average power - a 15x increase over the highest average power petawatt laser currently in operation. Combining this technique with low absorption multilayer dielectric gratings developed in our group would enable pulse compressors for petawatt peak power lasers operating at average powers well above 40kW.

Self-reported physical activity among middle-aged cancer survivors in the United States: Behavioral Risk Factor Surveillance System Survey, 2009.

INTRODUCTION: Regular physical activity (PA) can improve health outcomes in cancer survivors, but the rate of adherence to PA recommendations among middle-aged survivors is unclear. We examined adherence to PA recommendations among cancer survivors and controls. We sought to identify correlates of adherence to PA and to determine whether PA adherence is associated with health-related quality of life (HRQOL) among cancer survivors. METHODS: We examined PA adherence among 8,655 cancer survivors and 144,213 control subjects aged 45-64 years who were respondents to the 2009 Behavior Risk Factor Surveillance System survey. We used multinomial logistic regression to assess associations between PA adherence and demographic, psychosocial, and clinical factors, and multivariable linear regression to assess the relationship between PA adherence and HRQOL of cancer survivors. RESULTS: Cancer survivors and control subjects had similar rates of PA adherence. Of the survivors, 47% met the recommendations of 150 minutes of moderate-intensity PA or 120 minutes of vigorous-intensity PA per week, 41% were somewhat active, and 12% were sedentary. Compared with cancer survivors who were sedentary, survivors who were somewhat active were less likely to be obese (odds ratio [OR], 0.65; P < .007), and those who met PA recommendations were less likely to be overweight (OR, 0.61; P < .002) or obese (OR, 0.33, P < .001). Regression analysis indicated that PA adherence was positively correlated with HRQOL (P < .001). CONCLUSION: Most cancer survivors did not meet PA recommendations, but those who are active seem to have improved HRQOL. Therefore, targeted interventions to improve adherence to PA among cancer survivors are needed.

A bioinformatics workflow for detecting signatures of selection in genomic data.

The detection of "signatures of selection" is now possible on a genome-wide scale in many plant and animal species, and can be performed in a population-specific manner due to the wealth of per-population genome-wide genotype data that is available. With genomic regions that exhibit evidence of having been under selection shown to also be enriched for genes associated with biologically important traits, detection of evidence of selective pressure is emerging as an additional approach for identifying novel gene-trait associations. While high-density genotype data is now relatively easy to obtain, for many researchers it is not immediately obvious how to go about identifying signatures of selection in these data sets. Here we describe a basic workflow, constructed from open source tools, for detecting and examining evidence of selection in genomic data. Code to install and implement the pipeline components, and instructions to run a basic analysis using the workflow described here, can be downloaded from our public GitHub repository: http://www.github.com/smilefreak/selectionTools/

The CNVrd2 package: measurement of copy number at complex loci using high-throughput sequencing data.

Recent advances in high-throughout sequencing technologies have made it possible to accurately assign copy number (CN) at CN variable loci. However, current analytic methods often perform poorly in regions in which complex CN variation is observed. Here we report the development of a read depth-based approach, CNVrd2, for investigation of CN variation using high-throughput sequencing data. This methodology was developed using data from the 1000 Genomes Project from the CCL3L1 locus, and tested using data from the DEFB103A locus. In both cases, samples were selected for which paralog ratio test data were also available for comparison. The CNVrd2 method first uses observed read-count ratios to refine segmentation results in one population. Then a linear regression model is applied to adjust the results across multiple populations, in combination with a Bayesian normal mixture model to cluster segmentation scores into groups for individual CN counts. The performance of CNVrd2 was compared to that of two other read depth-based methods (CNVnator, cn.mops) at the CCL3L1 and DEFB103A loci. The highest concordance with the paralog ratio test method was observed for CNVrd2 (77.8/90.4% for CNVrd2, 36.7/4.8% for cn.mops and 7.2/1% for CNVnator at CCL3L1 and DEF103A). CNVrd2 is available as an R package as part of the Bioconductor project: http://www.bioconductor.org/packages/release/bioc/html/CNVrd2.html.

Evaluation of the PAH and water-extractable phenols content in used cross ties from the French rail network.

Recycling used railway sleepers is a major economic and environmental issue since nearly 50000 tons of those are incinerated every year in France. Therefore, it appeared essential to determine the real toxicity of sleepers and particularly for very old one. They are treated with creosote, which contains toxic and carcinogen compounds such as polycyclic aromatic hydrocarbons (PAHs). This study aims at measuring the amount of 16 priority PAHs and water extractable phenols in 12 sleepers implemented between 1936 and 1978. Results showed that the creosote content was systematically far above 1000mgkg(-1), even after 76years ageing. Crossties should then be considered as a hazardous waste according to European regulations. Less creosote and PAHs were detected in the sleepers centers. Moreover, the fraction of volatile PAHs was lower in the surface part, due to their evaporation. It appeared that a long ageing process was not sufficient to remove the major part of volatile PAHs and that they could be yet released in the atmospheric environment. Moreover, most of the treated crossties contained huge amount of the highly toxic benzo[a]pyrene, between 179mgkg(-1) and up to 853mgkg(-1) in wood. In contrast, the study revealed that concentrations of water extractable phenols were well below European regulations (3% by mass of creosote).

Selective capture of carbon dioxide under humid conditions by hydrophobic chabazite-type zeolitic imidazolate frameworks.

Hydrophobic zeolitic imidazolate frameworks (ZIFs) with the chabazite (CHA) topology are synthesized by incorporating two distinct imidazolate links. Zn(2-mIm)0.86 (bbIm)1.14 (ZIF-300), Zn(2-mIm)0.94 (cbIm)1.06 (ZIF-301), and Zn(2-mIm)0.67 (mbIm)1.33 (ZIF-302), where 2-mIm = 2-methylimidazolate, bbIm = 5(6)-bromobenzimidazolate, cbIm = 5(6)-chlorobenzimidazolate, and mbIm = 5(6)-methylbenzimidazolate, were prepared by reacting zinc nitrate tetrahydrate and 2-mIm with the respective bIm link in a mixture of N,N-dimethylformamide (DMF) and water. Their structures were determined by single-crystal X-ray diffraction and their permanent porosity shown. All of these structures are hydrophobic as confirmed by water adsorption isotherms. All three ZIFs are equally effective at the dynamic separation of CO2 from N2 under both dry and humid conditions without any loss of performance over three cycles and can be regenerated simply by using a N2 flow at ambient temperature.