### Recent Submissions

• #### ITO Top-Electrodes via Industrial-Scale PLD for Efficient Buffer-Layer-Free Semitransparent Perovskite Solar Cells

(Advanced Materials Technologies, Wiley, 2022-05-12) [Article]
The deposition of transparent conductive oxides (TCO) usually employs harsh conditions that are frequently harmful to soft/organic underlayers. Herein, successful use of an industrial pulsed laser deposition (PLD) tool to directly deposit indium tin oxide (ITO) films on semitransparent vacuum-deposited perovskite solar cells without damage to the device stack is demonstrated. The morphological, electronic, and optical properties of the PLD deposited ITO films are optimized. A direct relation between the PLD chamber pressure and the solar cell performance is obtained. The semitransparent perovskite solar cells prepared exclusively by vacuum-assisted techniques had fill factors of 78% and exceeded 18% in power conversion efficiencies. This demonstrates that the direct deposition of TCO-based top electrodes without protective buffer layers is possible and leads to efficient devices.
• #### The effect of trip wire on transition of boundary layer on a cylinder

(Physics of Fluids, AIP Publishing, 2022-05-05) [Article]
The effect of height of a trip and its location on the transition of boundary layer on a cylinder is studied using large eddy simulations for 2×103≤𝑅𝑒≤5×105. The Reynolds number, Re, is based on the free stream speed and diameter of the cylinder (D). Two modes of transition are observed: (a) natural, for a relatively small trip of height 𝑑𝑇/𝐷=0.25%, via formation of a laminar separation bubble (LSB) and (b) direct, for a large trip of height 𝑑𝑇/𝐷=1.0%, wherein the formation of LSB is bypassed and the trip disturbs the flow enough to cause separation of the boundary layer and its subsequent turbulent reattachment. Transition delays the final separation leading to a very significant reduction in drag, often referred to as drag crisis. The delay is more for natural as compared to direct transition. Consequently, the drag at the end of crisis is lower for natural transition. The 1.0% trip at 78° leads to a more delayed flow separation than one at 55° from the front stagnation point. The drag crisis takes place in two stages for a cylinder with trip. During each of the two stages, asymmetric transition on the two sides results in generation of circulation and lift force. The effect of trip is felt even by the non-trip side. The cylinder experiences a relatively large “reverse lift” during the second stage of drag crisis. While natural transition is accompanied by intermittency of LSB, direct transition is associated with intermittency in laminar vs turbulent attachment of the flow following its separation at the trip.
• #### Investigation of traffic accidents involving seated pedestrians using a finite element simulation-based approach

(Computer Methods in Biomechanics and Biomedical Engineering, Informa UK Limited, 2022-05-04) [Article]
Pedestrians who use wheelchairs (seated pedestrians) report 36% - 75% higher mortality rates than standing pedestrians in car-to-pedestrian collisions but the cause of this mortality is unknown. This is the first study to investigate the cause of seated pedestrian mortality in vehicle impacts using finite element simulations. In this study a manual wheelchair model was developed using geometry taken from publicly available CAD data, and was tested to meet ISO standards. The GHBMC 50th percentile male simplified occupant model was used as the seated pedestrian and the EuroNCAP family car and sports utility vehicle models were used as the impacting vehicles. The seated pedestrian was impacted by the two vehicles at three different locations on the vehicle and at 30 and 40 km/h. In 75% of the impacts the pedestrian was ejected from the wheelchair. In the rest of the impacts, the pedestrian and wheelchair were pinned to the vehicle and the pedestrian was not ejected. The underlying causes of seated pedestrian mortality in these impacts were head and brain injury. Life-threatening head injury risks (0.0% - 100%) were caused by the ground-pedestrian contact, and life-threatening brain injury risks (0.0 - 97.9%) were caused by the initial vehicle-wheelchair contact and ground-pedestrian contact. Thoracic and abdominal compression reported no risks of life-threatening injuries, but may do so in faster impacts or with different wheelchair designs. Protective equipment such as the wheelchair seatbelt or personal airbag may be useful in reducing injury risks but future research is required to investigate their efficacy.
• #### Insighting the optoelectronic, charge transfer and biological potential of benzo-thiadiazole and its derivatives

(Zeitschrift für Naturforschung C, Walter de Gruyter GmbH, 2022-04-20) [Article]
The current investigation applies the dual approach containing quantum chemical and molecular docking techniques to explore the potential of benzothiadiazole (BTz) and its derivatives as efficient electronic and bioactive materials. The charge transport, electronic and optical properties of BTz derivatives are explored by quantum chemical techniques. The density functional theory (DFT) and time dependent DFT (TD-DFT) at B3LYP/6-31G** level of theory utilized to optimize BTz and newly designed ligands at the ground and first excited states, respectively. The heteroatoms substitution effects on different properties of 4,7-bis(4-methylthiophene-2yl) benzo[c] [1,2,5]thiadiazole (BTz2T) as initial compound are studied at molecular level. Additionally, we also study the possible inhibition potential of COVID-19 from benzothiadiazole (BTz) containing derivatives by implementing the grid based molecular docking methods. All the newly designed ligands docked with the main protease (MPRO:PDB ID 6LU7) protein of COVID-19 through molecular docking methods. The studied compounds showed strong binding affinities with the binding site of MPRO ranging from −6.9 to −7.4 kcal/mol. Furthermore, the pharmacokinetic properties of the ligands are also studied. The analysis of these results indicates that the studied ligands might be promising drug candidates as well as suitable for photovoltaic applications
• #### Genomic and metabolic adaptations of biofilms to ecological windows of opportunity in glacier-fed streams

(Nature communications, Springer Science and Business Media LLC, 2022-04-20) [Article]
In glacier-fed streams, ecological windows of opportunity allow complex microbial biofilms to develop and transiently form the basis of the food web, thereby controlling key ecosystem processes. Using metagenome-assembled genomes, we unravel strategies that allow biofilms to seize this opportunity in an ecosystem otherwise characterized by harsh environmental conditions. We observe a diverse microbiome spanning the entire tree of life including a rich virome. Various co-existing energy acquisition pathways point to diverse niches and the exploitation of available resources, likely fostering the establishment of complex biofilms during windows of opportunity. The wide occurrence of rhodopsins, besides chlorophyll, highlights the role of solar energy capture in these biofilms while internal carbon and nutrient cycling between photoautotrophs and heterotrophs may help overcome constraints imposed by oligotrophy in these habitats. Mechanisms potentially protecting bacteria against low temperatures and high UV-radiation are also revealed and the selective pressure of this environment is further highlighted by a phylogenomic analysis differentiating important components of the glacier-fed stream microbiome from other ecosystems. Our findings reveal key genomic underpinnings of adaptive traits contributing to the success of complex biofilms to exploit environmental opportunities in glacier-fed streams, which are now rapidly changing owing to global warming.
• #### Modeling the size of co-seismic landslides via data-driven models: the Kaikōura's example

(California Digital Library (CDL), 2022-04-19) [Preprint]
The last three decades have witnessed a substantial methodical development of data-driven models for landslide prediction. However, this improvement has been dedicated almost exclusively to models designed to recognize locations where landslides may likely occur in the future. This notion is referred to as landslide susceptibility. However, the susceptibility is just one, albeit fundamental, information required to assess landslide hazard and to mitigate the threat that landslides may pose to human lives and infrastructure. Another complementary and equally important information is how large landslides may evolve into, once they initiate in a given slope. Only three scientific contributions have currently addressed the geographic estimation of how large co-seismic landslides may be. In the first one, the authors tested a model solely at the global scale, whereas the remaining two involved specific regional scale settings. The low number of previous research on the topic as well as specificities related to the associated study areas do not yet allow to fully support a standardized use of such models. In turn, this has repercussions on the operational feasibility and adoption potential of data-driven models capable of estimating landslide size in site-specific conditions. This manuscript addresses this gap in the literature, by further exploring the use of a Generalized Additive Model whose target variable is the topographically-corrected landslide extent aggregated at the slope unit level. In our case, the underlying assumption is that the variability of the landslide sizes across the geographic space behaves according to a Log-Normal probability distribution. We test this framework by going beyond the conventional non-spatial validation scheme in order to take a particularly critical look at the estimated model performance.The study focuses on co-seismic landslides mapped as a result of the ground motion generated by the Kaikōura earthquake (11:02 UTC, on November 13th 2016). The experiment led to further insights into the applicability of such approaches and produced more than satisfying performance scores, which we stress here in the prospect of stimulating further research towards spatially-explicit landslide size prediction.
• #### A Microporous Poly(arylene ether) Platform for Membrane-Based Gas Separation

(American Chemical Society (ACS), 2022-04-18) [Preprint]
Membrane-based gas separations are viewed as a critical component to accessing low-energy feedstocks and decarbonizing the chemical industry. However, it is exceedingly challenging to synthesize membrane materials that are high-performing, scalable, and processable. As a class of materials, microporous organic polymers (MOPs), which combine the gas sieving ability of microporous materials with the solution-processability of organic polymers, are highly desirable. Herein, we report the rational design and synthesis of linear microporous poly(arylene ether)s (PAEs) via Pd-catalyzed C-O polycondensation reaction. The scaffold of these microporous polymers consists of rigid three-dimensional triptycene and highly stereocontorted spirobifluorene, which endow these polymers with large internal free volume as well as high porosity with angstrom-sized pores. Unlike classic polymers of intrinsic microporosity (PIMs), this robust methodology for the synthesis of poly(arylene ether)s allows for the facile incorporation of functionalities and branched linkers for control of permeation and mechanical properties. CO2-philic groups, such as nitrile and tertiary amine groups, can be incorporated into this microporous polymeric scaffold for enhancing CO2 separation performance. In addition, a solution-processable branched polymer prepared using this synthetic strategy showed good gas separation performance and enhanced mechanical properties, which allowed for the formation of a submicron defect-free film with permeance-selectivity property sets that are comparable to high-performance ultrathin polymer membranes that have been optimized at industrial scale. In contrast with commercially available polymer membranes, the easily accessible PAE branching motif endows these materials with plasticization resistance. The structural tunability, high physical stability, and ease of processing suggest that this new platform of microporous polymers provides generalizable design strategies to address outstanding separation challenges for gas separation membranes.
• #### On the prediction of landslide occurrences and sizes via Hierarchical Neural Networks

(Stochastic Environmental Research and Risk Assessment, Springer Science and Business Media LLC, 2022-04-01) [Article]
For more than three decades, the part of the geoscientific community studying landslides through data-driven models has focused on estimating where landslides may occur across a given landscape. This concept is widely known as landslide susceptibility. And, it has seen a vast improvement from old bivariate statistical techniques to modern deep learning routines. Despite all these advancements, no spatially-explicit data-driven model is currently capable of also predicting how large landslides may be once they trigger in a specific study area. In this work, we exploit a model architecture that has already found a number of applications in landslide susceptibility. Specifically, we opt for the use of Neural Networks. But, instead of focusing exclusively on where landslides may occur, we extend this paradigm to also spatially predict classes of landslide sizes. As a result, we keep the traditional binary classification paradigm but we make use of it to complement the susceptibility estimates with a crucial information for landslide hazard assessment. We will refer to this model as Hierarchical Neural Network (HNN) throughout the manuscript. To test this analytical protocol, we use the Nepalese area where the Gorkha earthquake induced tens of thousands of landslides on the 25th of April 2015. The results we obtain are quite promising. The component of our HNN that estimates the susceptibility outperforms a binomial Generalized Linear Model (GLM) baseline we used as benchmark. We did this for a GLM represents the most common classifier in the landslide literature. Most importantly, our HNN also suitably performed across the entire procedure. As a result, the landslide-area-class prediction returned not just a single susceptibility map, as per tradition. But, it also produced several informative maps on the expected landslide size classes. Our vision is for administrations to consult these suite of model outputs and maps to better assess the risk to local communities and infrastructure. And, to promote the diffusion of our HNN, we are sharing the data and codes in a githubsec repository in the hope that we would stimulate others to replicate similar analyses.
• #### Direct numerical simulations of intrusive density- and particle-driven gravity currents

(Physics of Fluids, American Institute of Physics Inc., 2022-04-01) [Article]
In the present study, mesopycnal flows are investigated using direct numerical simulations. In particular, intrusive density- and particle-driven gravity currents in the lock exchange setup are simulated with the high-order finite-difference framework Xcompact3d. To account for the settling velocity of particles, a customized Fick's law for the particle-solution species is used with an additional term incorporating a constant settling velocity proportional to the concentration of particles. A general energy budget equation is presented, for which the energy can migrate across the domain's boundaries. The relevant main features of intrusive gravity currents, such as front velocity, energy exchanges, sedimentation rate, deposit profile, and deposit map are discussed with the comparison between two- and three-dimensional simulations. In particular, the influence of the Grashof number, the interface thickness, the energy exchanges, the sedimentation process, and how the presence of more than one particle fraction may change the flow dynamics are investigated. The results are in good agreement with previous experiments and theoretical work, in particular for the prediction of the front velocity. For the particle-driven case, the suspended mass evolution along with the sedimentation rate suggests the occurrence of three different stages. In the first stage after the lock release, the particle mixture tends to suspend itself due to gravitational forces. Once most of the particle-mixture mass is suspended, the current intrudes while increasing its velocity, reaching its kinetic energy peak. In the last stage, the particles are deposited at a nearly constant sedimentation rate. As a result, the front velocity constantly decelerates.
• #### System Level Synthesis Beyond Finite Impulse Response Using Approximation by Simple Poles

(arXiv, 2022-03-31) [Preprint]
Optimal linear feedback control design is valuable but challenging. The system level synthesis approach uses a reparameterization to expand the class of problems that can be solved using convex reformulations, among other benefits. However, to solve system level synthesis problems prior work relies on finite impulse response approximations that lead to deadbeat control, and that can experience infeasibility and increased suboptimality, especially in systems with large separation of time scales. This work develops a new technique by combining system level synthesis with a new approximation based on simple poles. The result is a new design method which does not result in deadbeat control, is convex and tractable, always feasible, can incorporate prior knowledge, and works well for systems with large separation of time scales. A general suboptimality result is provided which bounds the approximation error based on the geometry of the pole selection. The bound is then specialized to a particularly interesting pole selection to obtain a non-asymptotic convergence rate. An example demonstrates superior performance of the method.
• #### Evolution Increases Primates Brain Complexity Extending RbFOX1 Splicing Activity to LSD1 Modulation

(The Journal of Neuroscience, Society for Neuroscience, 2022-03-29) [Article]
Recent branching (100 MYA) of the mammalian evolutionary tree has enhanced brain complexity and functions at the putative cost of increased emotional circuitry vulnerability. Thus, to better understand psychopathology, a burden for the modern society, novel approaches should exploit evolutionary aspects of psychiatric-relevant molecular pathways. A handful of genes is nowadays tightly associated to psychiatric disorders. Among them, neuronal-enriched RbFOX1 modifies the activity of synaptic regulators in response to neuronal activity, keeping excitability within healthy domains. We here dissect a higher primates-restricted interaction between RbFOX1 and the transcriptional corepressor Lysine Specific Demethylase 1 (LSD1/KDM1A). A single nucleotide variation (AA to AG) in LSD1 gene appeared in higher primates and humans, endowing RbFOX1 with the ability to promote the alternative usage of a novel 3′ AG splice site, which extends LSD1 exon E9 in the upstream intron (E9-long). Exon E9-long regulates LSD1 levels by Nonsense-Mediated mRNA Decay. As reintroduction of the archaic LSD1 variant (AA) abolishes E9-long splicing, the novel 3′ AG splice site is necessary for RbFOX1 to control LSD1 levels. LSD1 is a homeostatic immediate early genes (IEGs) regulator playing a relevant part in environmental stress-response. In primates and humans, inclusion of LSD1 as RbFOX1 target provides RbFOX1 with the additional ability to regulate the IEGs. These data, together with extensive RbFOX1 involvement in psychiatric disorders and its stress-dependent regulation in male mice, suggest the RbFOX1-LSD1-IEGs axis as an evolutionary recent psychiatric-relevant pathway. Notably, outside the nervous system, RbFOX2-dependent LSD1 modulation could be a candidate deregulated mechanism in cancer.
• #### Long-Tailed Recognition via Weight Balancing

(arXiv, 2022-03-27) [Preprint]
In the real open world, data tends to follow long-tailed class distributions, motivating the well-studied long-tailed recognition (LTR) problem. Naive training produces models that are biased toward common classes in terms of higher accuracy. The key to addressing LTR is to balance various aspects including data distribution, training losses, and gradients in learning. We explore an orthogonal direction, weight balancing, motivated by the empirical observation that the naively trained classifier has "artificially" larger weights in norm for common classes (because there exists abundant data to train them, unlike the rare classes). We investigate three techniques to balance weights, L2-normalization, weight decay, and MaxNorm. We first point out that L2-normalization "perfectly" balances per-class weights to be unit norm, but such a hard constraint might prevent classes from learning better classifiers. In contrast, weight decay penalizes larger weights more heavily and so learns small balanced weights; the MaxNorm constraint encourages growing small weights within a norm ball but caps all the weights by the radius. Our extensive study shows that both help learn balanced weights and greatly improve the LTR accuracy. Surprisingly, weight decay, although underexplored in LTR, significantly improves over prior work. Therefore, we adopt a two-stage training paradigm and propose a simple approach to LTR: (1) learning features using the cross-entropy loss by tuning weight decay, and (2) learning classifiers using class-balanced loss by tuning weight decay and MaxNorm. Our approach achieves the state-of-the-art accuracy on five standard benchmarks, serving as a future baseline for long-tailed recognition.
• #### Discovery of high-frequency retrograde vorticity waves in the Sun

(Nature Astronomy, Springer Science and Business Media LLC, 2022-03-24) [Article]
Classical helioseismology, which relies on acoustic waves, has been successfully applied to image the Sun’s interior rotation and structure. However, acoustic waves are insensitive to parameters such as magnetic fields, turbulent viscosity and entropy gradients in the deep convection zone, which are critical inputs to theories of solar dynamics. Inertial oscillations can bridge this gap with their complementary sensitivities to these parameters. Here, by employing helioseismic and correlation-tracking analyses of ground- and space-based observations, we detect equatorially antisymmetric vorticity waves, propagating retrograde at three times the phase speeds of Rossby–Haurwitz waves of the same wavenumber. This high-frequency dispersion relation cannot be explained by standard hydrodynamic mechanisms. We investigate three possibilities: that these vorticity waves are excited by the Coriolis force and modified by internal magnetic fields, gravity or compressibility. Incontrovertible identification of any of these coupled oscillations would influence our understanding of deep-interior magnetism, internal gravity oscillations or large-scale convection. Through observational evidence and theoretical arguments, however, we exclude these coupling mechanisms. The as-yet undetermined nature of these waves promises novel physics and fresh insight into solar dynamics.
• #### Nanospace Engineering of Triazine−Thiophene-Intertwined Porous-Organic-Polymers $\textit{via}$ Molecular Expansion in Tweaking CO$_{2}$ Capture

(ACS Applied Nano Materials, American Chemical Society (ACS), 2022-03-22) [Article]
• #### Distinct Susceptibility Patterns of Active and Relict Landslides Reveal Distinct Triggers: A Case in Northwestern Turkey

(Remote Sensing, MDPI AG, 2022-03-09) [Article]
To understand the factors that make certain areas especially prone to landslides, statistical approaches are typically used. The interpretation of statistical results in areas characterised by complex geological and geomorphological patterns can be challenging, and this makes the understanding of the causes of landslides more difficult. In some cases, landslide inventories report information on the state of activity of landslides, adding a temporal dimension that can be beneficial in the analysis. Here, we used an inventory covering a portion of Northwestern Turkey to demonstrate that active and relict landslides (that is, landslides that occurred in the past and are now stabilised) could be related to different triggers. To do so, we built two landslide susceptibility models and observed that the spatial patterns of susceptibility were completely distinct. We found that these patterns were correlated with specific controlling factors, suggesting that active landslides are regulated by current rainfalls while relict landslides may represent a signature of past earthquakes on the landscape. The importance of this result resides in that we obtained it with a purely data-driven approach, and this was possible because the active/relict landslide classification in the inventory was accurate.
• #### Isolation of thioinosine and butanolides from a Terrestrial Actinomycetes sp. GSCW-51 and their in-silico Studies for Potential against SARS-CoV-2

(Chemistry & Biodiversity, Wiley, 2022-02-25) [Article]
• #### Landslide susceptibility maps of Italy: lesson learnt from dealing with multiple landslide classes and the uneven spatial distribution of the national inventory

(California Digital Library (CDL), 2022-02-25) [Preprint]
Landslide susceptibility corresponds to the probability of landslide occurrence across a given geographic space. This probability is usually estimated by using a binary classifier which is informed of landslide presence/absence data and associated landscape characteristics. Here, we consider the Italian national landslide inventory to prepare slope-unit basedlandslide susceptibility maps. These maps are prepared for the eight types of mass movements existing in the inventory, (Complex, Deep Seated Gravitational Slope Deformation,Diffused Fall, Fall, Rapid Flow, Shallow, Slow Flow, Translational) and build one susceptibility map for each type.The analysis -- carried out by using a Bayeian version of a Generalized Additive Model with a multiple intercept for each Italian region -- revealed that the inventory may have been compiled with different levels of detail. This would be consistent with the datases being assembled from twenty sub--inventories, each prepared by different administrations of the Italian regions. As a result, this spatial inhonomegenity may lead to a biased national--scale susceptibility maps.On the basis of these considerations, we further analyzed the national database to confirm or reject the varying quality hypothesis suggested by the multiple intercepts results. For each landslide type, we then tried to build unbiased susceptibility models by removing regions with a poor landslide inventory from the calibration stage, and used them only as a prediction target of a simulation routine. We analyzed the resulting eight maps finding out a congruent dominant pattern in the Alpine and Apennine sectors.The whole procedure is implemented in R--INLA. This allowed to examine fixed (linear) and random (nonlinear) effects from an interpretative standpoint and produced a full prediction equipped with an estimated uncertainty.We propose this overall modeling pipeline for any landslide datasets where a significant mapping bias may influence the susceptibility pattern over space.
• #### Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry

(Microbial Biotechnology, Wiley, 2022-02-17) [Article]
Microalgae industrial production is viewed as a solution for alternative production of nutraceuticals, cosmetics, biofertilizers, and biopolymers. Throughout the years, several technological advances have been implemented, increasing the competitiveness of microalgae industry. However, online monitoring and real-time process control of a microalgae production factory still require further development. In this mini-review, non-destructive tools for online monitoring of cellular agriculture applications are described. Still, the focus is on the use of fluorescence spectroscopy to monitor several parameters (cell concentration, pigments, and lipids) in the microalgae industry. The development presented makes it the most promising solution for monitoring up-and downstream processes, different biological parameters simultaneously, and different microalgae species. The improvements needed for industrial application of this technology are also discussed.
• #### A Dual Functional Polymer Interlayer Enables Near-Infrared Absorbing Organic Photoanodes for Solar Water Oxidation

(Advanced Energy Materials, Wiley, 2022-02-13) [Article]
Organic photovoltaic devices employing bulk heterojunctions (BHJs) of polymer donors and small molecular nonfullerene acceptors have recently demonstrated high performance, with strong visible and near-infrared absorption and low energy losses. Such junctions are promising candidates for solar-driven water splitting; however, the poor underwater stability of the small molecular acceptor in such devices has limited their viability to date. Here, a stable and efficient organic photoanode is demonstrated for water oxidation based upon a Y6:PM6 BHJ with a further dual functional PM6 layer transferred from water, and Au/NiFe electrocatalyst top layers. The additional PM6 layer functions to 1) increase operational stability and 2) suppress recombination losses between the BHJ and electrocatalyst layers. These BHJ/PM6 based photoanodes exhibit a photocurrent density of 4.0 mA cm−2 at 1.23 V versus the reversible hydrogen electrode and promising operational stability compared to the anode without a PM6 layer, maintaining a photocurrent ≥ 2 mA cm−2 over 1 h. Employing these photoanodes, solar water oxidation under near-infrared irradiation is demonstrated with an incident photon-to-current efficiency up to 25% at 770 nm illumination.
• #### A Molecular Dynamics Study of the Stability and Mechanical Properties of a Nano-Engineered Fuzzy Carbon Fiber Composite

(Journal of Composites Science, MDPI AG, 2022-02-10) [Article]
Carbon fiber-reinforced polymer composites are used in various applications, and the interface of fibers and polymer is critical to the composites’ structural properties. We have investigated the impact of introducing different carbon nanotube loadings to the surfaces of carbon fibers and characterized the interfacial properties by molecular dynamics simulations. The carbon fiber (CF) surface structure was explicitly modeled to replicate the graphite crystallites’ interior consisting of turbostratic interconnected graphene multilayers. Then, single-walled carbon nanotubes and polypropylene chains were packed with the modeled CFs to construct a nano-engineered “fuzzy” CF composite. The mechanical properties of the CF models were calculated through uniaxial tensile simulations. Finally, the strength to peel the polypropylene from the nano-engineered CFs and interfacial energy were calculated. The interfacial strength and energy results indicate that a higher concentration of single-walled carbon nanotubes improves the interfacial properties.