Introduction: A phenomenon of decreasing antimicrobial resistance (AMR) among fecal bacteria as food animals age has been noted in multiple field studies. We conducted a scoping review to summarize the extent, range, and nature of research activity and the data for the following question: “does AMR among enteric/fecal bacteria predictably shift as animals get older?”.Methods: This review followed a scoping review methodology framework. Pertinent literature published up until November 2018 for all animals (except humans) was retrieved using keyword searches in two online databases, namely, PubMed® and the Web of Science™ Core Collection, without filtering publication date, geographic location, or language. Data were extracted from the included studies, summarized, and plotted. Study quality was also assessed using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) guidelines for all included papers.Results: The publications with detailed relevant data (n = 62) in food animals, poultry, and dogs were identified. These included longitudinal studies (n = 32), cross-sectional studies of different age groups within one food animal production system or small-animal catchment area (n = 16), and experimental or diet trials (n = 14). A decline in host-level prevalence and/or within-host abundance of AMR among fecal bacteria in production beef, dairy cattle, and swine was reported in nearly two-thirds (65%) of the identified studies in different geographic locations from the 1970's to 2018. Mixed results, with AMR abundance among fecal bacteria either increasing or decreasing with age, have been reported in poultry  and dogs.Conclusions: Quantitative synthesis of the data suggests that the age-dependent AMR phenomenon in cattle and swine is observed irrespective of geographic location and specific production practices. It is unclear whether the phenomenon predates or is related to antimicrobial drug use. However, almost 50% of the identified studies predate recent changes in antimicrobial drug use policy and regulations in food animals in the United States and elsewhere. Escherichia coli in cattle as animals age during early life. One of the studies conducted in the U.S. suggested that the decline in the abundance of multidrug-resistant (MDR) fecal E. coli in cattle during the first months of life may be independent of the transition from milk to solid diet  changes as the host ages. For example, studies in beef and dairy cattle production systems in the Pacific Northwestern and Southwestern U.S. –3, Greatal drugs . Others al drugs –10. Hencal drugs . Thus, AAssessing the available research data pertaining to age-related AMR in food animals enhances our understanding of how the prevalence of animals carrying AMR bacteria or the abundance of AMR (or AMR genes) within those animals will change according to host age; in turn, this will help to formulate a risk-based AMR mitigation program to lower the environmental and food safety risks. However, it is unclear what kind of research information is available in the literature about age-dependent AMR in animals in different geographic regions of the world and across different periods. Thus, the objectives of this review were to examine research reports and summarize the available data for the following question: “does AMR among enteric/fecal bacteria predictably shift as animals get older?.” A scoping review was chosen as the approach for the study, given that the goal was to examine the nature, extent, and range of research activity on this broad question , 13 as wHere, we explore, summarize, and present data on age-related AMR dynamics from the available literature that was systematically searched for all animals without filtering date, geographic location, or the language of the publication. Using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) guidelines , we summWe followed the scoping literature review methodology framework outlined by Arksey and O'Malley . For rigThe following outcomes were defined for “AMR among enteric/fecal bacteria” in a sampled animal population: the abundance of AMR bacteria, the relative fraction of AMR bacteria, the quantities of total or specific genes encoding AMR in feces of animals, and the proportion of animals carrying AMR bacteria or genes in their feces collected by individual fecal or rectal swabs or in a pooled sample from the pen/flock/barn. The study designs included any observational design employing a comparison group.Enterobacteriaceae OR Escherichia coli OR E. coli OR Salmonella OR Campylobacter OR Enterococcus OR Klebsiella OR Citrobacter OR microbial flora OR microbiome OR intestinal microorganisms) AND .Keyword-based search strings were developed, refined, and implemented in two online databases: PubMed® maintained by the U.S. National Center for Biotechnology Information (NCBI) and Web of Science™ Core Collection maintained by the Thomson Reuters Corporation. The string for each database was refined until the search returned all publications known to the study team on the study question. The following final algorithms were used in PubMed®:  AND  AND  NOT (human OR man OR human disease OR human feces OR human stool OR children OR women OR infants).Similarly, the following final algorithms were used in the Web of Science™ Core Collection:  AND . After deduplication, the citation list was imported into the web-based Rayyan platform for systematic reviews  without filtering the language, geographic location, or date of publication. The final searches were performed in November 2018. All citations identified by the searches in the two databases were imported, merged, and deduplicated in the web-based RefWorks reviews .n = 8,073) were subjected to a title-based screening. A citation was excluded if the title indicated that the study was conducted in humans, was performed on the resistance to disease of multicellular organisms, was on infectious agents other than enteric/fecal bacteria, or was on bacterial resistance to drugs other than antimicrobial drugs. The citations retained after the title screening (n = 383) were subjected to an abstract-based screening. A citation was excluded if the abstract met any of the title exclusion criteria. In addition, a citation was retained if the abstract identified that the study met these inclusion criteria: (a) performed in farm, shelter, or household animals; (b) longitudinal study of >3 weeks or a cohort study or a cross-sectional study of multiple age groups in one production system or local population ; (c) enteric/fecal culturable bacteria or microbiome studied; and (d) AMR (phenotype or genes) measured in the bacteria or microbiome. The citations retained after the abstract screening (n = 199) were subjected to full-text screening. The full text was excluded if any of the abstract exclusion criteria were met or if it was an in vitro study or a cross-sectional study of animals at one age point or if the animal age was not specified. The full text was included if it met the abstract inclusion criteria, if the publication contained age-specific data on enteric/fecal AMR in animals of a given species  at more than one age point, and either the fecal/enteric bacterial species was isolated and antimicrobial drugs to which the isolate susceptibility was tested were specified or the fecal/enteric bacterial antimicrobial genes tested were specified. The screening was performed on the Rayyan platform. These steps yielded 62 studies. The references for all included studies are provided in The identified citations (n = 383) retained after the title screening. The scoping review diagram was created following the PRISMA guidelines , were recorded. For studies based on phenotypic AMR assessment, bacterial species isolated for testing the phenotypic susceptibility to antimicrobial drugs, number of isolates of each of the bacterial species, identity and class of each antimicrobial drug tested, percentage of the isolates of each bacterial species resistant to each individual antimicrobial drug, animal-level prevalence of AMR to each individual drug, percentage of the isolates of each bacterial species concluded to be MDR (≥3 drug classes), and animal-level prevalence of multidrug AMR were used in the study. For studies based on AMR gene quantification via metagenomics of fecal samples, the quantities of total and specific genes encoding bacterial AMR, identity and number of antimicrobial drug classes for which resistance is encoded by the detected genes, animal-level prevalence of the detected genes being carried in feces, and the total number of isolates were extracted from the full-text citations. Similarly, for the purpose of data extraction, studies published in non-English language were translated using an online translation tool. The above-described categories were not established a priori but were developed iteratively by reviewers and characteristics based on individual studies.The characteristics of each full text, such as year of publication, geographic location of the study, study design , sample size for the fecal sampling, animal species, animal production system , animal production category , age or age group of the sampled animals, individual or pooled fecal sampling , sample type , and AMR assessment method , etc. Similarly, extracted data from studies were aggregated based on the outcomes of interests  and summarized by the age of animals. Age-dependent AMR dynamics  were further visualized by age animals . The plotted individual observations represent AMR to particular drugs. Some studies recorded the age of animals as the stage of production cycle, for instance, piglet, nursery, grower, and finisher in the age data for pigs. To make the data consistent, data from such studies were categorized based on production stages . We used R software with the ggplot2 package (V.3.3.4) , study location, study design, animal species, animal age, AMR analysis (phenotypic or genotypic), and fecal bacteria tested  (n = 62) were cattle , pigs , poultry (n = 14), and dogs (n = 2). The most common study type was observational  , Salmonella enterica subsp. enterica , and Enterococcus spp. . All the studies were published as journal articles. The general characteristics of the retained articles are presented in E. coli; 36% reported the abundance of AMR E. coli; 4% reported AMR S. enterica; 4% reported the relative abundance of AMR in bacterial taxa; 4% reported the presence of AMR genes in feces of animals; 4% reported the proportion of both the animals carrying both AMR E. coli and the abundance of AMR E. coli; and 4% reported the abundance of both AMR E. coli and AMR genes in feces of animals. Similarly, 24 pig studies (including one with both cattle and pig and another with both pig and poultry) generated 25 combined data points, where the outcome was reported as: 8% of the studies reported the proportion of animals carrying AMR E. coli; 50% reported the abundance or proportion of AMR E. coli; 16% reported the proportion of AMR Salmonella spp.; 4% reported the proportion of AMR Campylobacter spp.; 4% reported the proportion of AMR Enterococcus spp.; 12% reported the presence of AMR genes in feces of animals; and 8% reported both the abundance and the proportion of AMR E. coli and the presence of AMR genes in feces of animals. Similarly, from a total of 14 poultry studies and 1 study with both pigs and poultry, 15 data points were generated, where outcomes were reported as: 50% reported the abundance or proportion of AMR E. coli; 14% reported the proportion of AMR S. enterica subsp. enterica; 21% reported the proportion of AMR Enterococcus spp.; 14% reported the presence of specific genes encoding AMR in feces of animals; and 7% reported the abundance or proportion of both AMR E. coli and Enterococcus spp. We captured only two studies conducted in dogs, where outcomes were reported as: 50% reported the proportion of AMR Enterococcus spp.; and 50% reported the presence of specific genes encoding AMR in feces. Furthermore, we visualized the AMR dynamic data according to the age of animals. Based on the combined data, we observed that the overall age-related AMR dynamics (both phenotypic and genotypic) were especially high at a young age and thereafter declined with the age of animals among fecal E. coli in cattle   . Of the 48, 77%) . The mosn cattle  and pigsn cattle . However turkey)  and fecaE. coli or among the total genes is similar to the phenotypic AMR data, with especially high values at earlier ages or sampling points in cattle and pigs. The age-related AMR genes among fecal bacteria in pigs are presented in n = 46) of the included studies from cattle and pigs showed a high prevalence and abundance of antimicrobial-resistant enteric/fecal bacteria early in life that subsequently declined with age. In contrast, half of the included studies in poultry showed an increase in the prevalence and abundance of AMR in fecal or cloacal bacteria with age. In dogs, mixed AMR dynamics with age were reported in the identified studies.In addition to phenotypic AMR, we also evaluated the combined data for AMR genes from cattle, pigs, poultry, and dogs from the included studies. The data showed that the overall abundance of genes encoding AMR to different drug classes among fecal n = 62) was performed by adapting the GRADE assessment of study quality and the risk-of-bias approach  clearly defined the study objectives and sampling procedures . However, the description of animal selection  was inadequate. In addition, very few studies  estimated the sample size. A majority of the studies  clearly described the experimental group, but there were very few studies  that performed randomization for treatment allocation. Nearly all the studies  clearly defined the method to measure the outcomes. Finally, more than 50% of the studies described the potential biases and/or confounders and adjusted or explained the results in the outcome and analysis section. Specific definitions used for quality assessment are provided in n = 51, 82%) reported the source of funding in their studies.To summarize the quality of research activity for the study question, an evaluation of the quality of evidence in the retained studies  since 2010. Additionally, most of the studies were from Europe and North America. We believe that this distribution likely reflects the geographic location in which the phenomenon is frequently investigated.E. coli shortly after birth and to shed MDR bacteria that are resistant to 9 and 10 antibiotics as early as 1 day of age -producing E. coli were high at a young age and decreased with age, followed later by an increase  compared with piglets and finishers from later birth cohorts. Another finding from the same study was that the prevalence of VRE was higher in broilers than in layers of the same age group; importantly, avoparcin had been used in the past in broilers but never in layer chicks  the studies clearly mention the research objectives and outcome and are from journal articles, the data were from different types of study designs, and different interpretative criteria for antimicrobial susceptibility testing may have affected the findings. Any citations that were not listed in one of the search databases were not captured by this study. Therefore, this is something that needs to be taken into consideration when interpreting the data of this review. Our scoping review has shown that the age-related dynamics in fecal/enteric AMR in food animals, including poultry and pet animal dogs, were consistent with other field study results. Although we do not fully understand the mechanism underlying the high AMR at early ages, it seems that the epidemiology of the age group of the animal population has been found to be an important factor in the quantification of AMR. The production of food animals may involve public health risks related to microbial exposure, and there are many opportunities for the bacteria carrying resistance determinants to enter the food chain, regardless whether the animal received antimicrobials or not. Age-dependent AMR study in food animals will improve our understanding of how the prevalence of AMR is within the commensal or host during their production phase. We believe that this age-dependent AMR data finding helps to stratify further individual risk based on the study area, allowing the potential targeting of surveillance  or any other intervention in specific animal age groups in the population . However, this review specifically aimed to summarize the research reports related to the age dependency of AMR, so many policy-related questions remain unanswered. The higher AMR observed at early ages is of concern, but there was no clear difference in animal age-specific trends between different antimicrobial agents, which could represent differences in antimicrobial use and, in turn, selection pressure. Well-researched areas of interest were identified in this review , and this finding could be extended to other food animals and to aquaculture, which will ultimately help with AMR risk categorization and planning for interventions to reduce environmental and foodborne risks to public health.The decline in the prevalence and abundance of AMR enteric/fecal bacteria with age in production pigs, beef, and dairy cattle has been reported since the 1970's in various geographic locations and in two-thirds of the included studies in our scoping review. In broiler chickens and meat turkeys, mixed AMR dynamics associated with age have been reported. We captured very few studies in dogs, where mixed AMR dynamics with age also were reported. We found that the age of animals could be one of the factors affecting both phenotypic and genotypic AMR; however, other management factors may influence the overall findings. Hence, identifying such risk factors associated with resistance in the different production phases of food animals and poultry is crucial, and such findings could guide judicious antimicrobial use. The scientific evidence from the existing studies in these areas is limited. Therefore, further longitudinal research into related AMR phenomena should be undertaken to better guide the interpretation of our findings.The datasets generated during and analyzed for this study are available from the corresponding author upon request.VV and HS conceived the study. TG, HS, and VV designed the study and its specific components. TG and LS performed the literature screening. TG and VV drafted the manuscript and developed the figures. HS, LS, and TN helped write the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This paper presents Contextual Fibre Growth (ConFiG), an approach to generate white matter numerical phantoms by mimicking natural fibre genesis. ConFiG grows fibres one-by-one, following simple rules motivated by real axonal guidance mechanisms. These simple rules enable ConFiG to generate phantoms with tuneable microstructural features by growing fibres while attempting to meet morphological targets such as user-specified density and orientation distribution. We compare ConFiG to the state-of-the-art approach based on packing fibres together by generating phantoms in a range of fibre configurations including crossing fibre bundles and orientation dispersion. Results demonstrate that ConFiG produces phantoms with up to 20% higher densities than the state-of-the-art, particularly in complex configurations with crossing fibres. We additionally show that the microstructural morphology of ConFiG phantoms is comparable to real tissue, producing diameter and orientation distributions close to electron microscopy estimates from real tissue as well as capturing complex fibre cross sections. Signals simulated from ConFiG phantoms match real diffusion MRI data well, showing that ConFiG phantoms can be used to generate realistic diffusion MRI data. This demonstrates the feasibility of ConFiG to generate realistic synthetic diffusion MRI data for developing and validating microstructure modelling approaches. •We present ConFiG, a biologically motivated numerical phantom generator for white matter.•ConFiG produces phantoms with state-of-the-art density and realistic microstructure.•Diffusion MRI simulations in ConFiG phantoms are comparable to real dMRI signals. In particular, numerical phantoms are often used when developing diffusion MRI (dMRI) microstructure imaging techniques where simulations of the dMRI signal in phantoms with known microstructural properties are used in lieu of an tructure . While rtructure , they hatructure . Some retructure . As welltructure . For insTypically, however, there is a mismatch between the complexity of true brain tissue microstructure and the models used in simulation, with simulations simplifying the microstructure. On one hand, ex vivo electron microscopy (EM) studies have revealed the high complexity of real axonal morphology . ReconstRecently, a number of groups have attempted the challenge of combining these features to generate phantoms approaching the morphological complexity and density of real tissue. The most common approach to this is the packing of fibres into densely packed configurations . The typTo this end, we propose Contextual Fibre Growth (ConFiG), an approach to generate WM numerical phantoms that emulates natural fibre growth. ConFiG generates WM numerical phantoms by growing fibres one-by-one, mimicking a set of key mechanisms which govern real axonal growth. A preliminary implementation of ConFiG was presented in . We asseThe rest of the paper is organized as follows: Section 2In this section we describe the ConFiG algorithm, beginning with an overview of the main components in the growth algorithm. We then describe the biological mechanisms motivating ConFiG and how each of these are implemented to give the final ConFiG algorithm.2.1•STEP 1: Generate initial growth configuration from user inputs•STEP 2: Grow the fibres using ConFiG growth algorithm•STEP 3: Generate 3D meshes for dMRI simulationGiven a set of morphological input parameters , ConFiG generates a densely packed set of fibres by growing each fibre following a set of biologically motivated rules. The generation of ConFiG numerical phantoms happens in three main steps:Each of these steps are discussed in detail below.First, Step 1 is broken down in to three substeps as outlined in STEP 1.1: Generate fibre starting points a–b. To gSTEP 1.2: Generate fibre target points c. To encSTEP 1.3: Generate growth nodes d. ConFiGSecond, Step 2, the main growth algorithm, is broken down into a series of substeps as outlined in STEP 2.1: Create growth network a&b. In oSTEP 2.2: Grow one fibre step  c-e. FibSTEP 2.3: Update the network  f. The gSTEP 2.4: Repeat steps 2.2 and 2.3 until fibre reaches target g. By defSTEP 2.5: Repeat steps 2.2–2.4 for remaining fibres h–i. As nFinally, Step 3, the meshing procedure, is briefly described below and in further detail in Section STEP 3: Generate 3D fibre meshes. After the growth process, each fibre will be represented by a series of connected 3D points and corresponding diameters at each point. In order to simulate diffusion MRI signals, these fibre skeleta need to be turned into 3D meshes. ConFiG uses a meshing procedure designed to eliminate overlap between fibres.The basic ConFiG growth algorithm described here is illustrated in https://vimeo.com/433661018 or https://doi.org/10.1016/j.neuroimage.2020.117107Supplementary video related to this article can be found at https://vimeo.com/433661018.Video 1 Illustration of the ConFiG growth algorithm overviewed in Section The following is the supplementary data related to this article:2.2•Chemoattraction – the process by which fibres are attracted to diffusible chemical cues in their environment .•Fibre collapse – a response to a chemorepulsive source whereby a fibre withdraws and regrows in a different direction .•Cell adhesion molecules – chemical signals on the surface of cells which guide axons that come into contact with them .•Fasciculation – the process by which multiple axons come together to form bundles .In nature, axons grow following chemical cues in their environment through various mechanisms which either attract or repel fibres to guide their growth . In an aThe following sections detail how mechanisms motivated by these biological processes are implemented in ConFiG while 2.3As mentioned in Section To approximate this chemoattractive mechanism, each fibre is encouraged to grow towards its target point (i.e. the target point acts like a chemoattractive source). From any node in the growth network, the fibre will move along an edge that takes it towards its target while avoiding existing fibres according to a cost function . The cheFrom a starting node, t, t, is (1)l=lt+fThe next node for a fibre will be the candidate node which has the lowest cost according to Equation Growing fibres along the network using just this chemoattractive mechanism is the minimal implementation of ConFiG that will generate substrates to try and meet the morphological inputs. There are some limitations to this minimal approach however; the greedy growth and the sparse sampling of the space means that fibres can grow into regions from which they cannot grow further and become stuck. Additionally, in this approach, fibres grow independently of one another, whereas real fibres grow forming bundles in the process known as fasciculation.Sections 2.4As mentioned in Section In ConFiG fibre collapse, the fibre will move back by an initial distance, 2.5In the preliminary implementation of ConFiG , the netA dynamic growth network was implemented to ameliorate these effects. Now, once a fibre has reached the target, a number of nodes, This is also loosely motivated by the contact guidance mechanism in which axons are attracted to or repelled by chemical cues on the surface of other cells, known as cell adhesion molecules (CAMs). Here, the added points act like CAMs meaning that a future fibre which grows can use these points near to the fibre to grow around or along it as if it were following contact guidance cues. 2.6One particular role CAMs play is in axon fasciculation, the process in which axons follow a so-called pioneer axon closely, forming a bundle . To mimiEquation , was altA fibre, This new form of the cost function encourages fibres of the same bundle to stick together while still avoiding fibres of different bundles, inspired by the labelled pathway hypothesis, which states that axons join different fascicles based on different CAMs expressed on the fibres . In this2.7Since the growth of fibres in ConFiG takes place on a discrete network of points, the final positions of fibre nodes may be suboptimal for achieving the maximum density. In other words, certain fibres’ nodes may be closer to other fibres than they would ideally be in order to reach their target diameter (i.e. the fibre has had to shrink its diameter at that node).To mitigate against this, a global optimisation step was added at the end of the growth in a procedure similar to MEDUSA . For eacThere is some biological evidence that this kind of interaction between fibres is important in the fasciculation process. The fasciculation process described in Section 2.8https://blender.org) and is built on the SWC mesher addon (https://github.com/mcellteam/swc_mesher).As mentioned in Section ConFiG meshes are constructed using Blender metaballs, an implicit surface representation which is the isosurface of a function; typically a function analogous to the electric potential from a point charge. When two metaballs come close to one another, the fields combine and the surfaces will merge to form a smooth surface. By placing a series of metaballs along the skeleton of each fibre, a smooth surface is formed for each fibre one-by-one as shown in When fibres are densely packed, the surfaces from neighbouring fibres may overlap. To account for this, a meshing procedure was developed in which fibres can deform around nearby fibres to avoid overlap. The metaball surface for one fibre is created as described above. This surface is then turned into a triangulated mesh, however the metaballs are retained. The metaball potential is then turned negative, meaning that rather than merging with any future nearby metaball surfaces, it will repel them, as shown in 2.93In order to assess the performance of ConFiG, a range of experiments were performed. The first set of experiments were performed in order to explore the impact of each of the biologically inspired growth mechanisms. Another set of experiments aimed to show that ConFiG is able to generate substrates with realistic microstructure by comparing generated substrates with real tissue. Additionally, the relationship between the user-specified target morphology and the final output morphology was investigated by comparing resulting phantoms to their inputs (target density and orientation distribution). Finally, a simulation experiment was performed to assess how well ConFiG phantoms can be used to generate realistic diffusion MRI data. The rest of this section outlines these experiments.3.1•one bundle of parallel fibres, target density 75%•one bundle with Watson distributed fibres  had a high target density whilst ensuring that each bundle had a reasonable number of fibres to begin with (>50).The ConFiG variants were tested by generating phantoms for each of the scenarios starting with the same initial conditions. Each phantom was generated 5 times with a different random seed and results averaged across the seeds.To investigate the impact of the biological mechanisms on dMRI simulation, a comparison was made between real dMRI signals and simulations from ConFiG phantoms. The NODDI model  was fittThe dMRI signal was simulated in the phantoms using Camino  with ideAll dMRI simulations in this work used a bulk diffusivity ulations  with 105ere used , with dMere used .3.2In order to test how realistic the microstructure generated using ConFiG is, microstructural measurements of diameter distribution and orientation distribution were calculated using methods to be comparable with previous studies on ex-vivo tissue .A centre line is generated from each of the fibre meshes by aligning the ends of each fibre with the z-axis and connecting the centre of mass of 100 equidistant slices through each fibre, following the approach taken by Each segment in this centre line could then be used to assess the microstructure of the phantom. The direction of each segment was used to assess the orientation distribution of the phantom, illustrated in A second approach was devised to better visualise orientation distributions in 3D to aid differentiation of crossing bundles and antipodal symmetry. In this approach each vertex was raised above the surface of the sphere proportionally to the number of segments pointing in its direction as illustrated in To measure the diameter profile along fibres, the direction of each segment gave the normal to a plane used to cut the fibre using Boolean intersection to give a cross section of each fibre at each segment. The diameter profile along the axon was generated by calculating the equivalent diameter of a circle with the same area as the fibre cross section. This process is illustrated in 3.3https://blender.org). A myelin sheath was added to the fibres when generating virtual histology for visualisation purposes. Virtual histological images were rendered with a resolution of 5 nm × 5 nm x 100 nm, chosen to be comparable to real histological white matter measurements  was fit in each voxel using constrained spherical deconvolution in MRTrix , 2007. VIn each voxel, the diffusion tensor was fit to the signal and the principal eigenvector used to define a major direction of diffusion in the voxel, To attempt to generate representative microstructure for each voxel using ConFiG, the NODDI model  was fittribution  estimateConFiG phantoms were grown using these initial conditions and the diffusion MRI signal simulated using the Camino Monte Carlo diffusion MRI simulator . For eac44.1Each of the proposed biological mechanisms enabled ConFiG to generate phantoms with increased density over the minimal case of chemoattraction only, as is shown in When combining all of the proposed mechanisms together, the achievable density is higher than any of the improvements individually. This improved performance is comparable to the state of the art, MEDUSA , with paThis improvement in density can be appreciated visually in The improvement in the density of phantoms leads to a much more realistic simulated diffusion MRI signal as demonstrated in 4.2The microstructural morphology generated using ConFiG is comparable to results from real data as demonstrated in Video 2 shows a series of sequential slices through a ConFiG substrate containing two crossing bundles of fibres, demonstrating the non-circular cross-sections generated by ConFiG. These complex cross-sections are not explicitly imposed during growth but arise as a result of the close packing of axons and the meshing procedure used in ConFiG.https://vimeo.com/402472645 or https://doi.org/10.1016/j.neuroimage.2020.117107Supplementary video related to this article can be found at https://vimeo.com/402472645.Video 2 Sequential virtual histology slices of a ConFiG phantom containing two crossing fibre bundles alongside the phantom in 3D with cutting plane indicated. Each fibre is given a unique colour to aid in differentiation and tracking of individual fibre. See also The following is the supplementary data related to this article:ConFiG morphological metrics calculated slice-wise on the virtual histology correspond much more closely to real axons that the same metrics calculated for parallel cylinders, as shown in The diameter distribution of a ConFiG substrate is compared to a reconstruction from real EM data  in Fig. ConFiG is also able to generate orientation distributions comparable to real tissue as shown in 4.3The morphology of ConFiG phantoms matches the input morphology well, as shown in These phantoms took an average of 6 h to grow plus an average of 20 min for the meshing and microstructural measurement procedure, using 9.4 GB of RAM on average. These values give an estimate of the time taken to generate a typical ConFiG phantom, though it is strongly dependent on user inputs (number of nodes in the network etc.).4.42 signal in the internal capsule and corpus callosum is lower in simulation than in real data. This is to be expected however because as Simulated data from ConFiG substrates match real dMRI data well, as shown in 5ConFiG is shown to produce substrates with microstructural properties comparable to real white matter, both in terms of measures derived from histology  and in terms of the diffusion MRI signal.ConFiG is shown to produce WM numerical phantoms with state-of-the-art performance. The amount of real data containing 3D microstructural morphology information available to compare to is limited, so we have only compared to one sample in this study. Whilst limited, this shows that ConFiG is able to produce realistic microstructure by following simple biologically inspired growth rules.Whilst the input morphological priors do not necessarily correspond to the morphology of the resulting ConFiG phantom, A related property of ConFiG is that the growth algorithm strongly depends on the growth network, meaning that the resulting phantom for the same input fibre configuration will be different for different network choices. This is alleviated to an extent by using the dynamic network introduced here, however the phantom will still be dependent on the initialisation of the network. The dependence appears to be relatively minor as is demonstrated by the small standard errors on the mean density shown in 2 signal from the internal capsule is higher at low |n.G| in the simulated versus the real data  to the Additionally, to further add to the realism of ConFiG phantoms, realistic myelin may be modelled, creating spiral layers wrapped around the axons . FurtherA planned future application will be to use ConFiG to generate a wide range of phantoms with different microstructural features. These can then be used to create a computational model to estimate microstructural features directly from the diffusion MRI signal in an approach similar to previous works .5.2As mentioned in the introduction, axonal configuration impacts MR signals beyond dMRI. One potential avenue of exploration would be to investigate the impact of realistic axonal configurations on magnetic susceptibility in a similar way to The virtual histology presented in https://mcell/.org) (http://lammps.sandia.gov)   or LAMMPdia.gov) .6ConFiG enables the generation of realistic white matter numerical phantoms achieving state of the art fibre density whilst ensuring realistic microstructural morphology by following biologically motivated rules. This realistic microstructure is shown to generate realistic simulated diffusion MRI signals, opening up the possibility to use ConFiG to create a realistic computational model of WM microstructure.ConFiG outputs fibre meshes which can be used for realistic diffusion MRI simulations or can be processed to produce virtual histological slices, allowing for further potential applications outside of diffusion MRI.https://rcallagh.github.io.ConFiG code will be made available at Ross Callaghan: Conceptualization, Methodology, Software, Investigation, Visualization, Writing - original draft. Daniel C. Alexander: Conceptualization, Writing - review & editing, Supervision, Resources, Funding acquisition. Marco Palombo: Conceptualization, Methodology, Writing - review & editing, Supervision. Hui Zhang: Conceptualization, Methodology, Writing - review & editing, Supervision, Resources, Funding acquisition.The authors confirm that there are no conflicts commercial or financial conflicts of interest affecting this work.


Collectiverotations of the polyhedral units in oxide ceramics are another commonlyexploited distortion, driving anomalous behavior such as negativethermal expansion—the counterintuitive phenomenon of volumecontraction on heating. An exciting development in the field has beento take advantage of the interplay between different distortion types:generating polarization by combining two different polyhedral rotations,for example. In this way, degrees of freedom act as geometric “elements”that can themselves be combined to engineer materials with new andinteresting properties. Just as the discovery of new chemical elementsquite obviously diversified chemical space, we might expect that identifyingnew and different types of structural degrees of freedom to be animportant strategy for developing new kinds of functional materials.In this context, the broad family of molecular frameworks is emergingas an extraordinarily fertile source of new and unanticipated distortiontypes, the vast majority of which have no parallel in the establishedfamilies of conventional solid-state chemistry.The structural degrees of freedom of a solidmaterial are the variousdistortions most straightforwardly activated by external stimuli suchas temperature, pressure, or adsorption. One of the most successfuldesign strategies in materials chemistry involves controlling theseindividual distortions to produce useful collective functional responses.In a ferroelectric such as lead titanate, for example, the key degreeof freedom involves asymmetric displacements of Pbmolecular frameworks,at least one of these components is a molecule.Framework materialsare solids whose structures are assembled fromtwo fundamental components: nodes and linkers. Quite simply, linkersjoin the nodes together to form scaffolding-like networks that extendfrom the atomic to the macroscopic scale. These structures usuallycontain cavities, which can also accommodate additional ions for chargebalance. In the well-established systems—such as lead titanate—node,linker, and extra-framework ions are all individual atoms . But in In this Account,we survey the unconventional degrees of freedomintroduced through the simple act of replacing atoms by molecules.Our motivation is to understand the role these new distortions play(or might be expected to play) in different materials properties.The various degrees of freedom themselves—unconventional rotational,translational, orientational, and conformational states—aresummarized and described in the context of relevant experimental examples.The much-improved prospect for generating emergent functionalitiesby combining these new distortion types is then discussed. We highlighta number of directions for future research—including the designand application of hierarchically structured phases of matter intermediateto solids and liquid crystals—which serve to highlight theextraordinary possibilities for this nascent field. Nat. Commun.2018, 9, 2380.1 Our demonstration that the many degrees of freedom in molecularperovskites vastly increase the opportunities to generate hybrid improperferroelectricity relative to conventional inorganic systems.• Boström, H. L. B.; Senn, M. S.; Goodwin, A. L.Recipes for Improper Ferroelectricity in Molecular Perovskites. Phys. Rev. Lett.2017, 119, 115501.2 Discovery that the interplay between molecularconformational interconversion and framework shear can drive a newtype of symmetry breaking in molecular frameworks.• Hill, J. A.; Christensen, K. E.; Goodwin, A. L. IncommensurateChirality Density Wave Transition in a Hybrid Molecular Framework. 2)3]CuxCdx1–(HCOO)3 Metal–Organic Frameworks. J. Am. Chem. Soc.2016, 138, 9393–9396.3 Characterization of the dependence of collectiveJahn–Teller and molecular orientational order on compositionin a series of hybrid perovskites.•Evans, N. L.; Thygesen, P. M. M.; Boström, H. L.B.; Reynolds, E. M.; Collings, I. E.; Phillips, A. E.; Goodwin, A.L. Control of Multipolar and Orbital Order in Perovskite-like Fe2/3□1/3(HCOO)3 (□ = vacancy) framework togethereven when one-third of the B-sites is absent.25 Another important distinction between monatomic and molecular cationsis that of accessible charge states. Molecular cations are predominantlyunivalent—dabconium, [H–N(C2H4)3N–H]2+, being a notable exception16—whereas inorganic ions can often accesshigher charges.26 Thus, molecular A-sitespecies offer a larger diversity in terms of interactions and shapesbut a smaller range of available charge states, relative to monatomicA-site species.A topical example of molecular substitutionon the A-site is thatof the organic halide perovskites such as MAPbI9 This is in contrast to oxideperovskites, which may feature cations with oxidation states as highas 6+.26 However, molecular B-site cationshave been incorporated in hybrid perovskite frameworks: a high-profileexample is the metal-free ferroelectric perovskite [MDABCO]NH4I3 (MDABCO = [H–N(C2H4)3N–CH3]2+), assembled byH–I interactions.16 The conceptof molecular nodes is well-established in MOF chemistry, with manycanonical systems based on such architectures: the [OZn4]6+ and [Zr6O4(OH)4]12+ B-site clusters in MOF-5 and UiO-66, respectively, areobvious examples.17 One advantage of incorporatingoxometallate clusters is that it allows highly charged metal cations(up to 4+) to be incorporated, which often correlates with good thermaland chemical stability.17The scope for compositional variation of theB-site is normallysystem dependent. By way of example, molecular perovskites generallycomprise univalent A and X species, which thus requires B to be adivalent octahedral species. As a result, molecular perovskites arefrequently based on first-row transition metals—rather thanmolecular ions—as these satisfy both the charge and geometryrequirements.8 Organic anions are the predominant type of molecular X-site linkers,but metal-containing species may also be used, as in the dicyanometallate27 and metalloporphyrin28 frameworks. Even simple inorganic molecules and molecular ions canoccupy the X-site: examples include BH4–, SiF62–, I2, and CN–.31 Quite obviously the scope forvariation on this site is essentially without limit and includes linkerfunctionalization—an important tool for property optimization.32 The linker shape may also guide the topologyof the system and the propensity for distortions.33 Hence, of the three site types in molecular frameworks,it is the X-site that offers the richest playground for tuning structureand function.Molecularsubstitution on the X-site leads to the rich familiesof MOFs and CPs.19 and more generally,they are the rigid-unit modes (RUMs) relevant to, e.g., the silicateminerals and zeolites.34 Their ubiquityarises from the contrast in energy scales between the cost of deformingthe tightly bound BXn2 coordination polyhedraand flexing the underconstrained B–X–B linkages. Asa consequence, a common structural distortion involves correlatedrotations of corner-sharing coordination polyhedra, themselves behavingeffectively as rigid bodies. By way of example, the famous tilt instabilityin SrTiO3 involves counter-rotation of corner-sharing TiO6 octahedra around a common axis—the Ti coordinationgeometry is preserved in the process, but the Ti–O–Tiangle flexes to reduce the system volume at low temperatures.35 In general, many different tilt distortionsare possible for a given framework, with each one breaking crystalsymmetry in its own particular way. This symmetry breaking can beexploited in the design of hybrid improper ferroelectrics, which hasled to the development of so-called “tilt engineering”approaches,22 whereby framework compositionis cleverly manipulated to introduce tilt distortions of a specificuseful symmetry.Arguably the best studied type of structural degree of freedomin conventional framework materials is that of tilt distortions. Inperovskites, these are the “octahedral tilts” famouslycategorized by Glazer,n2] polyhedra to rotate in opposite directions,but the latter lifts any such constraint.36 In particular, it is possible in molecular frameworks for neighboringpolyhedra to rotate in the same sense as one another—a so-called“forbidden” tilt distortion that has no analogue inconventional frameworks.37 It turns outthat forbidden tilts are a relatively common phenomenon in many molecularperovskites, with a particular predominance in azide-bridged systems[33 In the Prussian-blue-like framework [NH4]2SrFe(CN)6, it is even possible toswitch between conventional and forbidden tilt distortions throughreversible guest binding at the B-site ) are shifted relativeto one another as a consequence of the step-like NDC geometry.43 Whereas in hybrid perovskites the shifts areusually well-ordered, in DUT-8(Ni), they exhibit a strongly correlateddisorder governed by strict local rules: each square pore is boundedby two NDC steps-up and two steps-down.44 The particular type of disordered arrangement can even be controlledreversibly by guest (de)sorption, which imparts the system with anunusual type of structural flexibility.45The asymmetric 2,6-naphthalenedicarboxylate (NDC) linker inducesa similar effect in the MOF known as DUT-8(Ni). Here, neighboringcolumns of DABCO-bridged nickel-carboxylate paddlewheels 6].14In the long-wavelength limit, shift modes correspond to asheardistortion of the framework structure. Hence, the propensity for molecularframeworks with cubic or square topologies to exhibit shift-type instabilitiesis reflected also in their low shear moduli—as in MOF-5 (ref )—and, e.4] units rotate such that eachtetrahedron translates along a loop tangent 2, where a pressure-induced phase transition isaccompanied by a coupled translation of the [ZnN4] tetrahedra.52 The extension from these select few examplesto a general understanding of translational degrees of freedom inmolecular frameworks of arbitrary topology, however, remains verymuch an open question and work-in-progress.Whereas translational degreesof freedom in cubic and square networktopologies are understood well, the case is much less clear for othersystems. For molecular frameworks with diamondoid topologies, a verydifferent type of collective translation occurs: hexagonal loops ofconnected tetrahedral , where A is an organic cation—typicallydisplay phase transitions upon cooling, driven by progressive freezingof the motion of the A-site cation. This can be exploited in the developmentof materials with switchable dielectric constants.54 The metal-free ferroelectric [MDABCO][NH4]I3 develops a polarization competitive with that in BaTiO3 through orientational order of the polar [MDABCO]2+ cations  corresponds to a loss of dipolar order, whereas—asthe normal of the imidazolium plane is unchanged—the quadrupolarorder is retained.54 The type of multipolarorder is dictated by the symmetry relationship between the point symmetryof the A-site cation and its site in the ideal undistorted parent.57 Some control over the order of the multipolemoments may be achieved by considering the packing efficiency andsize of the cavity.3 As a result, designrules based on multipole moments may be within reach. An interestingparallel to these examples is the phenomenology of so-called “hidden-ordertransitions” in strongly correlated electronic materials, e.g.,the magnetocaloric Gd3Ga5O12, whichalso involve the emergence of multipolar order on lattices of varioustopologies.59Phase transitions relatingto orientational order can often bedescribed in terms of multipole moments and map onto relatively simplephysical models.18 Relateddegrees of freedom exist in molecular frameworks. For example, thehexagonal Zr-MOF PCN-223 features a Zr oxyhydroxide cluster with threefoldorientational disorder at the nodes of the hexagonal lattice.60 Such disorder can complicate the structure determination,as recently noted for PCN-221—a polymorph of PCN-223.61 The unusual cubic Zr oxyhydroxide cluster initiallyreported in PCN-221 appears to be the result of a superposition ofstatically disordered octahedral clusters.61If the symmetry ofthe B-site species is lower than the point symmetryof its crystallographic site, then orientational B-site order canemerge. A well-known example in conventional frameworks is that ofcollective Jahn–Teller order—crucial to the physicsof many strongly correlated oxides.62 It readily absorbs moleculeslarger than the size of the pore window, which can be attributed toa rotation of the surrounding imidazolate linker edges  Mn[N(CN)2]3 (Pr = C3H7).66 Part of the interest in these systems arisesfrom the possibility of controlling order via the application of externalelectric fields.Turning to the X-site, the use of cylindrically asymmetricanionsleads to potential symmetry breaking by rotation around the B–X–Blinkage. This is of particular currency for ZIFs and has been extensivelystudied in the specific case of ZIF-8, a porous material with theSOD topology.3.67 More complex is the case of bis(trisphenylphosphine)iminium (PPN),which acts as the A-site cation in dicyanometallate frameworks andwhich can adopt multiple conformations in the solid state.27 When enclosed in the layered [PPN]0.5Cd[Ag(CN)2]2.5(EtOH), for example, the phenylgroups are oriented so as to maximize the π–π interactionbetween the aromatic rings and the framework. By contrast, in theperovskite [PPN]Cd[Au(CN)2]3, inter- and intramolecularinteractions are favored.27As the structuralcomplexity of molecular components increases,so too does their capacity for internal degrees of freedom. Variationsin molecular conformation—e.g., torsion angles—are distinctfrom the whole-body rotations or translations associated with displaciveand orientational degrees of freedom. A simple example is the H–N–C–Hdihedral angle of the methylammonium cation, which may influence excitonrecombination rates in MAPbIcis/trans isomerism of the linkers.68 This structuralchange tightens the pore size, which effectively switches on and offthe material’s ability to transport molecules beyond a certaincritical size [69 In the dicyanometallate-linked diamondoid framework[NEt4]Ag[Ag(CN)2]2 (Et = C2H5), the normally achiral NEt4+ A-site cation adopts a chiral conformationthrough its interaction with the dicyanometallate network.2 At low temperatures, this chirality is coupledin a complex fashion throughout the crystal to give an incommensuratelymodulated “chirality density wave” of potential interestin advanced photonics Mn[N(CN)2]3.70 On heating above a criticaltemperature of 331 K, the tetrapropylammonium A-site cationsswitch from being conformationally ordered to a disordered state.A significant entropy change of ∼42.5 J kg–1 K–1 accompanies the transition.Because the disordered state has a larger molar volume, the transitioncan be suppressed by applying a very modest hydrostatic pressure Cu(HCOO)3 as a resultof combined Jahn–Teller and multipolar order as an excellentexample.75 Solid-solution chemistry—termed “multivariate”synthesis in the MOF field—offers a surprisingly underexploredadditional dimension for exploration in molecular framework materialsdesign.76 Here the scope is especiallybroad, since substitution of molecular components can involve varyingnot only size or charge but also shape, conformation, rigidity, orfunctionality.Just as the manganites have assumed a specialrole in device physicsbecause they combine many interacting degrees of freedom—charge,spin, lattice, and orbital—so is it the case that we expectthe 77 and unconventional78 magnetism can be found among this broader familyof materials, one expects that conventional inorganic or intermetallicsystems will always have the upper hand in this regard. Nevertheless,the orientational degrees of freedom of, e.g., A-site cations canbehave as pseudospins that, in favorable cases, interact in a manneranalogous to various types of magnetic exchange with strengths of∼100 K.57 Hence, there isenormous scope to exploit the way in which molecular frameworks bothorganize pseudospin degrees of freedom and control their interactionsto access structural analogues of exotic magnetic phases.58A necessary consequence of the larger physicalseparation betweentransition-metal centers in magnetic molecular frameworks is a reducedenergy scale associated with collective magnetic order. And whileexamples of strong79 In such systems, the director field associatedwith A-site orientations exhibits the same topological features asin nematic liquid crystals, now driven by the Dzyalonshinskii-Moriyaphysics of skyrmionic magnets.80 Giventhe extraordinary diversity of structural degrees of freedom foundin molecular frameworks and the varied types of interaction that existbetween those degrees of freedom, one anticipates the discovery ofall sorts of emergent states (like skyrmions) in molecular frameworks,well beyond those found in the conventional playgrounds of unconventionalphysics.One target, for example, is the realizationof skyrmionic phasesof the potential application in information storage and manipulation.


The sound absorption of granular silica-aluminate molecular sieve pellets was investigated in this paper. The absorption coefficients of molecular sieve pellets with different pore sizes, pellet sizes, and layer thicknesses were measured through impedance tubes under room temperature and pressure conditions. The effects of pore size, pellet size, layer thickness were compared and explained. The comparisons show that at room temperature and pressure, the sound absorption of molecular sieve pellets is not a result of the crystalline structure, but rather it mainly changes with the pellet size and layer thickness. In addition, the five non-acoustical parameters of molecular sieve pellets were obtained by an inverse characterization method based on impedance tube measurements. The measurement by impedance tubes is in good agreement with the calculation of Johnson-Champoux-Allard (JCA) model, proving that the JCA model can be effectively used to predict the sound absorption of molecular sieve pellets. Porous materials are the most widely used sound absorbing materials in engineering. The obvious sound absorption of porous materials lies in the fact that their internal structure has numerous tiny pores that are interlinked with each other and connected to the outside on their surfaces. During the process of sound wave propagation, friction occurs between the moving air in the pores and the solid skeleton of the pore wall, and viscous loss is caused by the viscosity of airflow within the materials. Due to the viscosity and heat conduction effect of the air, sound energy is converted into internal energy and then dissipated, thus achieving sound absorption .Porous sound absorbing materials may be classified into fibrous, cellular and granular ,3. Granu4 and SiO4, which are the basic components of different zeolites. The crystalline structure of molecular sieves is a three-dimensional porous system that precisely adjusts the pore size to allow molecules smaller than this pore size to be adsorbed and to exclude larger molecules [2/Al2O3 = 2) and NaX (SiO2/Al2O3 = 2.5) is approximately 660 °C. Molecular sieves with different crystal structures are usually classified by the pore diameter, such as 3Å, 4Å and 5Å, where 1Å = 0.1 nm. 3Å molecular sieves have effective adsorption selectivity and are suitable for the insulating glass desiccant and refrigerant desiccant applications; 5Å molecular sieves have high adsorption and fast adsorption speed, and are suitable for various gas pressure swing adsorption devices for oxygen, hydrogen and carbon dioxide production. The appearance of molecular sieves is usually as a powder, strips or granular. The size range of molecular sieve pellets is generally 0.4–0.8, 1.6–2.5 or 3–5 mm. For convenience, we will uniformly refer to them as micro, small and large pellets in this paper.Molecular sieves, also known as zeolites, belong to the aluminosilicate compounds, a sort of crystalline porous material. The corresponding crystallographic structure is formed by tetrahedrons of AlOolecules ,12, hencThe acoustic properties of porous materials are mainly focused on the propagation of sound waves through their interior. Zwikker and Kosten  pointed The paper is organized as follows: In The purpose of this paper is to investigate the sound absorption characteristics of molecular sieves at room temperature and pressure. 3Å and 5Å molecular sieve pellets were chosen for the measurements carried out in SW impedance tubes according to ISO 10534-2 . Based oA perforated cylindrical box is designed to fill with loose molecular sieve pellets. The sound absorption of the perforated cylinder is very low and can be ignored here. For example, a perforated cylinder with an aperture of 1.5 mm and a perforation ratio of 39.6% is used, and its measurement of sound absorption coefficient with cylinder depths of 20, 30 and 50mm is shown on the right of In order to find out the effect of pore size on the sound absorption of molecular sieve pellets under room temperature and pressure, two types of samples with pore sizes of 3Å and 5Å are selected for sound absorption comparison. The characteristics of the molecular sieve pellet samples used are listed in The sound absorption curves of 3Å and 5Å are similar in shape and almost identical. The slight differences in some frequency bands may be caused by installation or measurement errors. Under room temperature and pressure, “sieve molecules” does not appear due to its own strengthening stability. That is to say, the pore size has no obvious effect on the sound absorption of molecular sieve pellets. The sound absorption of molecular sieve pellets is mainly related to the macroscopic size of pellets and is less related to the pore size. Therefore, molecular sieve pellets are regarded as rigid porous materials, and sound energy is mainly consumed by the air viscosity between pellets and heat transfer between air and pellets surface. In addition, a low sound absorption coefficient valley appears on each sound absorption curve, which obviously affects the wide-band sound absorption of molecular sieve pellets. This is because the sound absorption of molecular sieve pellets is related to flow resistance, porosity and structure factor, and finally attributed to the pellets gap. When the gap between pellets is too large or too small, the air between the pellets cannot be sufficiently frictional and heat transfer during the propagation of sound waves.To illustrate the effect of layer thickness on the sound absorption of molecular sieve pellets, the measured sound absorption coefficient for the eight samples given in Three different pellet size molecular sieve pellets selected for sound absorption comparison are illustrated in 0P is the ambient atmospheric pressure, JCA model is a generalized model for sound propagation in porous materials over a wide range of frequencies, which includes five non-acoustic parameters of porous materials: the static flow resistance essed as :(1)ρe(ω)Based on the equivalent fluid theory, the characteristic acoustic impedance Therefore, according to Zwicker and Kosten theory, the surface acoustic impedance Then, the normal incidence sound absorption coefficient can be calculated as:Simulated annealing is an optimization algorithm based on Monte Carlo iteration. Because of its global optimization and strong robustness, it is widely used in the optimization of multi-objective parameters in acoustic materials and structures ,32,33,34Meanwhile, according to the analysis of five non-acoustic parameters in literature , the optUsing the above inversion strategy, the calculated non-acoustic parameters of samples are listed in New samples with different thickness listed in Under the conditions of room temperature and pressure, the sound absorption performance of molecular sieve pellets was measured for comparisons. It is found that the sound absorption coefficients are very sensitive to the pellet size and the thickness of the molecular sieve pellets, but not sensitive to the pore size of the molecular sieve pellets, implying that the sound absorption is not caused by the crystalline structure. Molecular sieve pellets with optimized pellet size may result in satisfactory absorption in the broad band frequency range. Increasing the thickness of the molecular sieve pellets moves the sound absorption peaks to a lower frequency range. Moreover, it has been demonstrated that the JCA model is appropriate to describe the sound absorption performance of molecular sieve pellets. The five non-acoustic parameters obtained with one sample by the inverse method are reliable and can be used for the prediction of the sound absorption coefficient of molecular sieve pellets with different thicknesses. When the temperature and pressure are higher than those of room conditions, or under the condition of high sound intensity, the effect of the crystalline structure on the sound absorption has not been verified and is worth being investigated in the future.


In recent decades, molecular simulation has developed into an industry. Since its beginnings in the 1950s, the field has grown continuously with the tremendous increase of computational power but, even more, by the successful efforts of many researchers devoted to finding ways of computing the properties of aggregates of molecular systems at atomistic resolution. Molecular simulations developed from basic theoretical techniques  to compute all kinds of properties of condensed phases for the simplest molecular models. For a long time, these calculations could be done only for simple systems, but computing power and algorithms began catching up with the theory to enable the application of calculations to large, practically relevant molecules like proteins, drugs and materials. In 1998 the Nobel Prize in chemistry was awarded to Walter Kohn and John A. Pople for the development of advanced computational methods in quantum chemistry while in 2013 it was awarded to Martin Karplus, Michael Levitt and Arieh Warshel for the development of models for complex chemical systems, so confirming that the field has reached a “nobility status”. If you ask a professional in the field: “Where is MD heading next?”, the answer is generally “larger, faster, more complex”: The field seems obsessed with gearing up the machinery for advancing to more complex, and more relevant molecular systems. This may be an appropriate target but, as a general answer, it is also a treacherous one. It reveals that MD as a scientific field has changed scope and purpose. MD started as an auxiliary tool of the theory that made possible calculations that scientists could not even dream of doing by hand before. It started as a simple prolongation of the human mind. Then, step by step, the machinery was scaled up and simulations started to allow realistic insight into the molecular basis of the cosmos and also into the molecular micro-cosmos itself. These simulations seem to create a virtual reality that scientists just have to visit in order to find out “what is going on”. Furthermore, today, at the onset of the era of exascale computing, the dream of inspecting the processes of life on the level of molecular resolution seems to be coming true. However, there are pitfalls. For example, even in the exascale era, clock speed and bandwidth will no longer substantially increase. That is, the more complex molecular systems that come into reach will be larger but the timescale accessible by brute-force MD simulations will no longer grow. This means that the timescale challenge will not be solved by the next generation of supercomputers but only by theory. Since the beginning, research regarding algorithms to overcome the challenges associated to the limitations of the atomistic approach have been at the heart of the development of the field. However, in recent years, the pace of the phenomenon, specially focused on the timescale challenge, has witnessed a dramatic acceleration. Ideas from statistical physics, rare event simulations, and related fields, generally led by stochastic modelling, have been utilized for new algorithms like milestoning, interface sampling, Markov state modelling, enhanced sampling or accelerated MD that allow for obtaining reliable statistics on timescales far beyond the ones accessible by the longest MD trajectories computable by brute force. At the same time, the gap between simulation and understanding in molecular dynamics is widening. One reason for this gap is that massive simulations produce massive data and tools for understanding it have not developed and are not developing at the same rate as the rate of increase in simulation size. Simultaneously, fields like machine learning and big data analytics are experiencing explosive growth. The idea of using the progress in the data sciences for the extraction of information from long MD trajectories is not new; however, recently, many research groups have taken the lead and developed completely new techniques, e.g., for data-based identification of reaction coordinates or kinetic fingerprinting, that are simultaneously based on simulation as well as on experimental (spectroscopic) data. However, again, theory is needed to provide understanding of what is actually computed and with which accuracy. In this promising but complex situation, the standard trial and error way in which the field has progressed in the past, led by chemists and physicists not particularly mathematically  trained, seems to have reached some kind of saturation and more attention to the tools of applied mathematics appears to be needed. In particular, if we aim beyond standard statistical mechanics and equilibrium expectation values at dynamical phenomena. Developing the right probabilistic framework for the study of dynamical phenomena, such as rare events or transition pathways of non-equilibrium processes, is a formidable challenge. This part of Statistical Mechanics is still much less developed and requires more sophisticated tools from Stochastic Processes Theory; one has to deal with a stochastic process rather than with random variables. As a result, the probability distributions relevant to dynamical phenomena are more complicated objects in path space, and their theoretical characterization and efficient computation are in their infancy. However, establishing what these distributions are and how to use MD or modifications of it as a tool to sample them efficiently is the right way to go. Given the growing importance of advanced statistical techniques and stochastic modeling to understand and develop a more solid basis for computational statistical mechanics and, in particular, MD simulation, we need a novel effort to overcome the traditional way of approaching this problem. The present Special Issue is a first attempt to collect some of these new theory-related research efforts in the framework of MD, specially addressing algorithms , theoret


The maximum loss peak (tanδmax) improved in all PBMA/PR blends compared with the pure PBMA. However, tanδmax reduced as the molecular weight increased. This is because PR with higher molecular weight is more rigid in the glass transition zone of blends. The hydrogen bonding between PBMA and PR was characterized by Fourier transform infrared spectroscopy (FTIR). Lower molecular weight PR formed more hydrogen bonds with the matrix and it had weaker temperature dependence. Combined with the results from DMA, we studied how molecular weight affected hydrogen bonding and thus further affected tanδmax.Poly (butyl methacrylate) (PBMA) was blended with a series of phenolic resins (PR) to study the effect of PR molecular weight on dynamic mechanical properties of PBMA/PR composites. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) found a similar variation of glass transition temperature (T However, in practical application, polymer damping materials are usually required to play a high damping capacity in a specific temperature range. In order to achieve this goal, some methods like blends, interpenetrating networks, and copolymerization were adopted [In order to reduce the harm caused by vibration in people’s daily life and industrial production, the development of damping materials is becoming more and more important . Polymer adopted ,5,6,7,8.g. On the contrary, weak interaction may reduce Tg [Some scholars have tried to combine polymers with organic or inorganic fillers in order to obtain high performance polymer damping materials. Yin et al. blended petroleum resin with chlorinated butyl rubber (CIIR), thus improving its damping temperature range. The contact angle experiments revealed that van der Waals interactions play an important role in improving the damping properties . Wu et aeduce Tg .g, tanδmax is the focus of this paper. Tanδmax is influenced by molecular motions on different length scales and it is difficult to improve on the high temperature side. Wu [max. This provides a new idea for the preparation of high performance damping materials. In recent years, some reports about the effect of hydrogen bonding on the damping properties of polymer/small molecule hybrids have been reported [max [Compared to Tside. Wu  found threported ,15. Somereported ,17 have ted [max ,19. Thisg of the fillers can reflect its motion ability and it increases with the increase of molecular weight for polymer oligomers. Therefore, it is theoretically possible to adjust the motion ability of fillers by changing its molecular weight.Hydrogen bonding is a kind of reversible dynamic physical bonding. The energy dissipation from it should be affected by the motion ability of filler molecules. Tg close to room temperature, about 20 °C. This characteristic makes it have better application prospect in higher temperature range. PR is formed by condensation of some simple low molecular weight compounds and is widely used in molding powders, laminating resins, adhesives, binders, surface coatings due to its lower manufacturing cost, dimensional stability, chemical resistance, and thermal stability [Poly (butyl methacrylate) (PBMA) is a homologue of acrylate polymers, which is widely used as pressure-sensitive adhesives, paints, coatings, seals, and damping elements . Howevertability ,22. PR ctability . It was max was discovered. FTIR was used to analyze the interaction between PR and PBMA. Finally, we put forward explanation to interpret the phenomenon observed in our case.In this paper, five kinds of PR with different molecular weights were blended with PBMA by solvent blending. The dynamic mechanical behavior and segment dynamics were measured by DSC and DMA. An interesting variation about tanδPBMA was synthesized by emulsion polymerization in our laboratory. A series of linear phenolic resins  were provided by Chengdu Keyi Polymer Technology Co., Ltd. . The chemical structures of PBMA and PR are shown in BMA was passed through neutral alumina columns before use to remove the polymerization inhibitor. In the first step, 160 mL deionized water, 100 mL BMA monomer, 4 g emulsifier were added into a 500-mL three-necked flask. Nitrogen was stirred in at room temperature for 20 min and then heated to 72 °C. At the same time, 0.3 g initiator was dissolved in 40 mL deionized water and dripped into the emulsion through a constant pressure drip funnel. When the liquid surfance appears light blue, the reaction was continued for 4 h. The product was precipitated with anhydrous ethanol. Then filtered with a vacuum pump until the liquid in the lower layer is clarified. The product is then placed on a evaporation dish and dried in a vacuum oven.Ethyl acetate was selected as the co-solvent for PBMA and PR. First, PBMA (3 g) and PR (3 g) were dispersed in 50 mL of ethyl acetate at room temperature for 8 h to form an even solution. Then 250 mL of deionized water was added to precipitate the sediment. The sediment was collected by watch glass and then dried in a vacuum oven at 80 °C for 24 h.2 windows. After the solvent is completely volatilized, the sample was fixed and tested. For the temperature scans, the samples were placed in a heating cell connected to a temperature controller. The temperature range was from 30 °C to 170 °C. The carbonyl stretching region was fitted by two Gaussian bands, corresponding to free and hydrogen bonded carbonyl band near 1728 cm−1 and 1704 cm−1, respectively.FTIR was carried out on Nicolet 6700 . Total of 0.2 g blends was dissolved in 2 mL tetrahydrofuran (THF) and smeared on the CaFe . The sample was first heated from −20 °C to 120 °C at a rate of 15 °C/min and then cooled toward −20 °C at the same rate. Finally, a heating process at a heating rate of 3 °C/min to 120 °C was performed to measure the Tg. For PR, we are going to approximate its softening point as Tg because its molecular weight is so small that there is no rubber platform.DSC test was performed on DSC-822DMA was carried out on Q800  by using a dual cantilever clamp and a testing method of temperature step-frequency sweep under a heating rate of 5 °C/min within a temperature range of −20 °C to 200 °C and a frequency of 1 Hz.−1 can be attributed to the stretching vibrations of carbonyl. B01 shows the characteristic absorption peaks at 1500 cm−1 and 1600 cm−1 which can assign to the stretching vibrations of conjugate double bonds in aromatic ring framework. The characteristic absorption peak of hydroxyl appeared at 3485 cm−1 and the peak of carbonyl splits into two peaks located at 1704 cm−1 and 1728 cm−1 respectively for B01. These phenomena indicate the formation of hydrogen bonding between PR and PBMA.The FTIR spectra were used to characterize the structures of PBMA and B01. As shown in g of PBMA in g. With the increase of molecular weight, it increases rapidly at first and then rises slightly. In order to further understand this phenomenon. The Tg measured by DSC is compared with the Tg calculated by Fox equation. As shown in g than that predicted by the Fox equation. This is mostly caused by the strong intermolecular interaction between fillers and matrix.Glass transition is the cooperative motion of local segments, it is sensitive to the environment. Except for A01, the softening point of all phenolic resins is higher than Tmax and tanδ peak area (TA) were used to evaluate the damping properties and other damping parameters of blends are listed in max improves from 1.481 to 2.352, TA increases from 40.4 to 71.64. On the other hand, the molecular weight has a great influence on the damping property. Higher molecular weight leads to smaller improvement of damping properties. By adjusting the molecular weight properly, PR can improve the damping capacity of the polymer more effectively.Dynamic mechanical analysis (DMA) is widely used to detect dynamic mechanical properties and segmental dynamics of polymer composites. Tanδ is an important parameter to evaluate damping properties. Some studies on molecular dynamics have found that tanδ consists of three molecular motions  and the area of tanδ is influenced by them together ,25,26. Gmax increases. Hydrogen bonding plays a role in limiting molecular motion and increasing energy consumption at the same time. max than pure PBMA and the variation of tanδ peak position is consistent with those measured by DSC. It is worth noting that tanδmax can be easily suppressed by a larger molecular weight. We think this is because that the PR with higher molecular weight has weaker motion ability that can reduce the energy consumption from hydrogen bonds.The temperature dependence of tanδ of PBMA/A04 composites is shown in -tanδ-Tg-dsc) is used to evaluate the motion ability of PR in the glass transition region of PBMA/PR composites . As shown in In order to test our ideas, ∆T′ (TgInspection of N) of rubber platform is directly related to entanglements, as follow:e represents entanglement molecular weight, ρ is the polymer density, R is the gas constant, and T is the temperature. That means the PBMA blended with larger molecular weight PR produce more entanglements and have less free volume. However, different scales of molecular motion have different responses to the space limited. The reduction in free volume can mainly confine the molecule motion with long scale and has little effect on small motion units such as segments corresponding to Tg [max.On the other hand, the storage modulus of the composites improves with the increase of PR molecular weight in the rubbery state in ng to Tg ,31. This−1 comes from the free carbonyl groups, another centered at around 1704 cm−1 corresponds to the hydrogen bonded carbonyl [carbonyl . With inT) of the carbonyl region can be expressed by the following formula [B and AF are the area of bonded and free carbonyl groups, respectively. The fraction of hydrogen-bonded carbonyl is given by:As shown in  formula ,34,35:ATB with temperature for B01 and B04. B01 forms more hydrogen bonds and has a weak dependence on temperature than B04, especially above 130 °C. This is consistent with our prediction. Combined with previous tests, we can draw a preliminary conclusion that lower molecular weight phenolic resin is more likely to form hydrogen bonds with PBMA because of its greater motion ability, which can effectively improve tanδmax.g. PR with higher molecular weight had weaker motion ability in the glass transition zone for PBMA/PR composites, which can weaken the energy dissipation from hydrogen bonding and reduce tanδmax. The variable temperature IR spectra found that PR with smaller molecular weight can form more hydrogen bonds with matrix and shows weaker temperature dependence. By analyzing the results, we found that increasing tanδmax by hydrogen bonding energy requires a premise, the fillers need to have sufficient motion ability in the glass transition zone. The conclusion can be used as a guide for the preparation of high performance polymer damping materials.The influence of PR molecular weight on the dynamic mechanical properties of PBMA/PR composites was investigated in this work. We used poly (butyl methacrylate) (PBMA) as matrix and a series of PR with different molecular weights as fillers for investigation. Solvent blending was used as a blending method. DSC and DMA found similar variation in T


Resveratrol is a naturally occurring polyphenol compound which has been shown to possess antioxidant and anti-inflammatory properties. However, its pharmaceutical applications are limited by its poor water solubility. In this study, we used electrospinning technology to synthesize nanofibers of polyvinylpyrrolidone (PVP) and hydroxypropyl-β-cyclodextrin (HPBCD) loaded with resveratrol. We used X-ray diffractometry to analyze crystalline structure, Fourier transform infrared spectroscopy to determine intermolecular hydrogen bonding, antioxidant assays to measure antioxidant activity, and Franz diffusion cells to evaluate skin penetration. Our results showed that the aqueous solubility of resveratrol nanofibers was greatly improved  compared to the pure compound. Analysis of physicochemical properties demonstrated that following nanofiber formation, resveratrol was converted from a crystalline to amorphous structure, and resveratrol formed new intermolecular bonds with PVP and HPBCD. Moreover, resveratrol nanofibers showed good antioxidant activity. In addition, the skin penetration ability of resveratrol in the nanofiber formulation was greater than that of pure resveratrol. Furthermore, resveratrol nanofibers suppressed particulate matter (PM)-induced expression of inflammatory proteins (COX-2 and MMP-9) in HaCaT keratinocytes. Therefore, resveratrol-loaded nanofibers can effectively improve the solubility and physicochemical properties of resveratrol, and may have potential applications as an antioxidant and anti-inflammatory formulation for topical skin application. Resveratrol (Res) is a naturally occurring non-flavonoid polyphenol compound and is characterized by a stilbene chemical structure  1]. It . It 1]. A major drawback of resveratrol is that it is poorly soluble in water, and can only dissolve in organic solvents such as methanol and ethanol ,19. ThisCyclodextrins are generated from the enzymatic degradation of starch. They have a truncated cone structure with a lipophilic inner cavity and hydrophilic outer surface, leading to high aqueous solubility. They can therefore act as nanoparticle sized carriers to improve the water solubility of lipophilic drugs, and enable controlled drug release ,29,30. NElectrospinning technology uses electrostatic forces to generate nanofibers with very fine diameters ,35. TherIn this study, we used electrospinning technology to synthesize resveratrol-loaded nanofibers containing different ratios of polyvinylpyrrolidone (PVP) and hydroxypropyl-β-cyclodextrin (HPBCD). We determined whether resveratrol nanofibers can effectively improve the aqueous solubility of resveratrol, analyzed their surface morphology and physicochemical properties, determined their skin penetration ability, and investigated their antioxidant and anti-inflammatory activities.Resveratrol was obtained from Acetar Bio-Tech Inc. . The purity of resveratrol was greater than 97% as determined by high-performance liquid chromatography (HPLC). PVP  was acquired from Sigma-Aldrich . HPBCD was purchased from Zibo Qianhui Biological Technology Co., Ltd . PM (1649b) was purchased from the National Institute of Standards and Technology .The electrospinning procedure was performed using FES-COS Electro-spinning equipment . The amount of resveratrol, PVP and HPBCD used to prepare different ratio formulations of resveratrol nanofibers during the electrospinning procedure is presented in 2PO4 . The flow rate was 1 ml/min. The eluted resveratrol was detected by an ultraviolet detector (wavelength 290 nm). The absorption peak for resveratrol appeared at 6.57 min.High-performance liquid chromatography (HPLC) was performed using a pump with an ultraviolet detector system . The Mightysil RP-18 GP column  was used for HPLC . The mobile phase was composed of acetonitrile : KHTo obtain the standard calibration curve for HPLC, 1 mg of resveratrol was dissolved in 1 ml methanol, and filtered through a 0.45-μm membrane. The resveratrol solution was serially diluted to 100, 50, 10, 5, 1, 0.5, 0.1, 0.05, and 0.01 μg/mL, and analyzed by HPLC. A standard curve for resveratrol was then constructed.Firstly, 10 mg of different ratio formulations of resveratrol nanofibers was dissolved in 1 ml methanol, filtered through a 0.45-μm membrane , and diluted 25-fold. The diluted solutions were analyzed by HPLC, and the standard curve was used to calculate the resveratrol amount. The following equation was used to calculate entrapment efficiency : Resveratrol entrapment efficiency (%) =  × 100%.Measurement of water solubility was performed at 25 °C temperature and 50 ± 5% humidity. Pure resveratrol (1 mg) and different ratio formulations of resveratrol nanofibers  were dissolved in 1 ml deionized water, shaken for 1 h , filtered through a 0.45-μm membrane , and diluted 10-fold. The diluted solutions were analyzed by HPLC, and the standard curve was employed to determine the resveratrol amount.The surface morphology of the nanofiber formulations was visualized using scanning electron microscopy. The nanofibers were sputter coated with gold–palladium and then visualized by a scanning electron microscope . X-ray diffractometry  was used to determine the crystalline versus amorphous structure of pure resveratrol and resveratrol nanofiber formulations. The analysis was conducted using nickel-filtered Cu-Kα radiation, using a voltage of 40 kV and current of 25 mA. The range of the angles scanned was from 5° to 50°.The samples  were mixed with potassium bromide using a mortar, and compressed to form thin sheets. The samples were then analyzed by a FTIR spectrophotometer .2,2-diphenyl-1-picrylhydrazyl (DPPH) is a lipophilic free radical, and is soluble in ethanol. It has a purple color, and absorbs light strongly at a wavelength of 517 nm. When DPPH undergoes a redox reaction with an antioxidant, the color of DPPH turns to yellow, and the absorption at 517 nm is decreased .The experimental groups were pure resveratrol in water, pure resveratrol in methanol, resveratrol nanofibers, and vitamin C (as a reference antioxidant). The samples were filtered and serially diluted. To perform the DPPH free radical scavenging assay, 100 μL of different concentrations of the test samples was mixed with 100 μL DPPH (200 μM) in a 96-well plate, and incubated in the dark for 30 min. The absorption was then measured using a spectrometer at a wavelength of 517 nm.4[Fe(CN)6]3) is used to assess reducing power. For this assay, the Fe3+ in [K3Fe(CN)6] is first reduced by the test sample to Fe2+ in [K4Fe(CN)6], and then the solution is reacted with Fe3+ in FeCl3 to form Prussian blue. The absorption at 700 nm is measured to determine the concentration of Prussian Blue [The production of Prussian blue (Feian Blue .3Fe(CN)6 (1%) were mixed in a 1.5-ml microtube at 50 °C for 20 min, and placed in a cool water bath for 2 min. Then, 250 μL of trichloroacetic acid solution (10%) was added and the solution was centrifuged at 3000 rpm at 4 °C for 10 min. After centrifugation, 100 μL of supernatant was mixed with 140 μL deionized water and 10 μL FeCl3·6H2O (0.1%) in a 96-well plate and incubated in the dark for 10 min. The absorption was then measured using a spectrometer at a wavelength of 700 nm.The reducing power of pure resveratrol and resveratrol nanofibers was evaluated against vitamin C as a reference antioxidant. To perform this assay, 250 μL of the test sample, 250 μL of phosphate buffer (0.2 M), and 250 μL of KWhen ABTS ) is oxidized, it forms a blue-green colored cation free radical ABTS+. When an antioxidant test sample is added, ABTS+ is reduced back to ABTS, and the solution becomes colorless . 2S2O8 (2.45 mM) in a 1:1 ratio, and incubated for 12~16 h. The ABTS solution (170 μL) was then mixed with the test sample (30 μL) in a 96-well plate. The absorption was measured using a spectrometer at a wavelength of 734 nm.The ABTS radical scavenging activity of pure resveratrol and resveratrol nanofibers was evaluated against vitamin C as a reference antioxidant. To perform this assay, ABTS (7 mM) was mixed with KThis experiment was performed according to the European Cosmetic Toiletry and Perfumery Association (COLIPA) guideline . The FraHaCaT cells were cultured in 6-well plates, and treated with pure resveratrol or resveratrol nanofibers. Cells were then harvested, treated with lysis buffer, and proteins were extracted. The proteins were separated by sodium dodecylsulfate–polyacrylamide gel electrophoresis (SDS-PAGE), and then blotted onto polyvinylidene difluoride (PVDF) membranes. The membranes were incubated with antibodies against cyclooxygenase-2 (COX-2)  and matrix metalloproteinase-9 (MMP-9)  overnight at 4 °C. Secondary antibodies were then added for 1 h at room temperature, and the immunoreactive bands were visualized with the enhanced chemiluminescence (ECL) system. Antibodies against GAPDH and α-tubulin were used as internal controls. Data are shown as mean ± standard error of the mean (SEM). Comparisons between multiple groups were performed using analysis of variance (ANOVA) with post-hoc Tukey’s test. P value < 0.05 was considered to be statistically significant.Different ratio formulations of resveratrol nanofibers were subjected to HPLC analysis, and the amount of resveratrol was determined from the standard curve. It was found that ratios of 1:4:20, 1:4:40, 1:8:40 and 1:16:40 (Res:PVP:HPBCD) all had greater than 90% entrapment efficiency . In partScanning electron microscopy of resveratrol nanofibers showed that a Res:PVP:HPBCD ratio of 1:4:20 produced the thinnest nanofibers (437.96 ± 41.92 nm) . As the The X-ray diffractometry results showed that pure resveratrol exhibited multiple diffraction peaks at 5°~30°, indicating that resveratrol had a crystalline structure . On the -1  . When resveratrol was complexed with PVP and HPBCD to form resveratrol nanofibers, the absorption band at 3200~3500 cm-1 was broadened (indicating formation of new hydrogen bonds with nanocarriers), and there was an absorption band at 1600~1700 cm-1 . These results indicate that resveratrol had formed new intermolecular bonds, and had been encapsulated by its nanocarriers. The intermolecular interactions between resveratrol, HPBCD and PVP were analyzed using FTIR. The FTIR spectra showed that pure resveratrol had an absorption band at 3200~3500 cm groups) . PVP shoThe in vitro antioxidant assays were performed using a ratio of 1:4:20 for resveratrol nanofibers. The results from the DPPH assay showed that the free radical scavenging activity of resveratrol nanofibers was greater than that of pure resveratrol in methanol, and equivalent to that of vitamin C . This inThe results from the reducing power assay (production of Prussian blue) showed that the reducing power of pure resveratrol in methanol and resveratrol nanofibers was similar and equivalent to that of vitamin C . TherefoThe ABTS free radical scavenging activity of pure resveratrol in methanol and resveratrol nanofibers was similar and equivalent to that of vitamin C . This inWe next investigated whether the skin penetration ability of resveratrol is increased after nanofiber formation. Pig skin was exposed to pure resveratrol or resveratrol nanofibers, and different layers of the skin  were collected at 1, 2 and 4 and 8 h to determine drug concentration. The results demonstrated that resveratrol in the nanofiber formulation showed greater penetration into the epidermis and dermis compared with pure resveratrol, and this occurred in a time-dependent manner . Therefo2) led to increased protein expression of inflammatory proteins COX-2 and MMP-9  produced the thinnest nanofibers. On the other hand, resveratrol nanofibers with high proportions of PVP and HPBCD (in particular 1:16:40) produced thicker fibers which became fragmented. A possible explanation is that when the proportions of PVP and HPBCD increase, the viscosity of the nanofibers also increases ,55, whicThe improvement in water solubility of resveratrol may be a result of changes in physicochemical properties. An analysis of the physicochemical properties by X-ray diffractometry demonstrated that following nanofiber formation, resveratrol was converted from a crystalline to amorphous structure. In addition, FTIR showed that new intermolecular bonds (including hydrogen bonds) were formed between resveratrol and HPBCD/PVP. These results indicate that resveratrol had been encapsulated by the nanocarriers, and the formation of nanofibers improved the physicochemical properties of resveratrol. Previous reports have also demonstrated that when a drug is loaded into PVP/HPBCD nanofibers, it is converted from crystalline to amorphous form, and new intermolecular bonds are formed between the drug and nanocarriers ,51.Moreover, we demonstrated that resveratrol nanofibers possess good DPPH free radical scavenging activity, reducing power, and ABTS radical scavenging activity, indicating that resveratrol may show improved antioxidant activity following nanofiber formation . FurtherIn order to exert biological effects on the skin, cutaneous drug formulations need to penetrate the different layers of skin. The stratum corneum has been shown to be a rate-limiting factor for the skin penetration of drugs . In thisPreviously, it has been shown that particulate matter (PM) in air pollution may exert inflammatory effects on the skin ,60,61,62Based on the results of this study, we propose that resveratrol nanofibers may be a suitable cosmetic or drug formulation for topical skin application. The nanofibers may be applied to the skin as a thin film with local actions on the skin, for example as a facial mask product. The high surface area to volume ratio of the nanofiber facial mask may facilitate drug delivery to facial skin, leading to antioxidant and anti-inflammatory actions. Previously, facial masks formed from electrospun fiber mats have been developed to exert an anti-wrinkle effect on facial skin . Since oIn conclusion, resveratrol-loaded nanofibers can effectively improve the aqueous solubility and physicochemical properties of resveratrol, show enhanced skin penetration, and exhibit antioxidant and anti-inflammatory properties. Therefore, resveratrol nanofibers may have potential applications as an antioxidant and anti-inflammatory formulation for topical skin application in the future.