Showing papers by "North Carolina State University published in 2022"

Lignin-enzyme interaction: A roadblock for efficient enzymatic hydrolysis of lignocellulosics

Abstract: Efficiently producing second-generation biofuels from biomass is of strategic significance and meets sustainability targets, but it remains a long-term challenge due to the existence of biomass recalcitrance. Lignin contributes significantly to biomass recalcitrance by physically limiting the access of enzymes to carbohydrates, and this could be partially overcome by applying a pretreatment step to directly target lignin. However, lignin typically cannot be completely removed, and its structure is also significantly altered during the pretreatment. As a result, lignin residue in the pretreated materials still significantly hindered a complete conversion of carbohydrate to its monosugars by interacting with cellulase enzymes. The non-productive adsorption driven by hydrophobic, electrostatic, and/or hydrogen bonding interactions is widely considered as the major mechanism of action governing the unfavored lignin-enzyme interaction. One could argue this type of interaction between lignin residue and the activated enzymes is the major roadblock for efficient enzymatic hydrolysis of pretreated lignocellulosics. To alleviate the negative effects of lignin on enzyme performance, a deep understanding of lignin structural transformation upon different types of pretreatments as well as how and where does lignin bind to enzymes are prerequisites. In the last decade, the progress toward a fundamental understanding of lignin-enzyme interaction, structural characterization of lignin during pretreatment and/or conformation change of enzyme during hydrolysis is resulting in advances in the development of methodologies to mitigate the negative effect of lignin. Here in this review, the lignin structural transformation upon different types of pretreatments and the inhibition mechanism of lignin in the bioconversion of lignocellulose to bioethanol are summarized. Some technologies to minimize the adverse impact of lignin on the enzymatic hydrolysis, including chemical modification of lignin, adding blocking additives, and post-treatment to remove lignin were also introduced. The production of liquid biofuels from lignocellulosic biomass has shown great environmental benefits such as reducing greenhouse gas emissions and mitigate climate change. By addressing the root causes of lignin-enzyme interaction and how to retard this interaction, it is our hope that this comprehensive review will pave the way for significantly reducing the high cost associated with the enzymatic hydrolysis process, and ultimately achieving a cost-effective and sustainable biorefinery system.

POCLib: A High-Performance Framework for Enabling Near Orthogonal Processing on Compression

Abstract: Parallel technology boosts data processing in recent years, and parallel direct data processing on hierarchically compressed documents exhibits great promise. The high-performance direct data processing technique brings large savings in both time and space by removing the need for decompressing data. However, its benefits have been limited to data traversal operations; for random accesses, direct data processing is several times slower than the state-of-the-art baselines. This article proposes a novel concept, orthogonal processing on compression (orthogonal POC), which means that text analytics can be efficiently supported directly on compressed data, regardless of the type of the data processing – that is, the type of data processing is orthogonal to its capability of conducting POC. Previous proposals, such as TADOC, are not orthogonal POC. This article presents a set of techniques that successfully eliminate the limitation, and for the first time, establishes the near orthogonal POC feasibility of effectively handling both data traversal operations and random data accesses on hierarchically-compressed data. The work focuses on text data and yields a unified high-performance library, called POCLib. In a ten-node distributed Spark cluster on Amazon EC2, POCLib achieves 3.1× speedup over the state-of-the-art on random data accesses to compressed data, while preserving the capability of supporting traversal operations efficiently and providing large (3.9×) space savings.

Understanding, quantifying, and controlling the molecular ordering of semiconducting polymers: from novices to experts and amorphous to perfect crystals

Abstract: Molecular packing and texture of semiconducting polymers are often critical to the performance of devices using these materials. Although frameworks exist to quantify the ordering, interpretations are often just qualitative, resulting in imprecise use of terminology. Here, we reemphasize the significance of quantifying molecular ordering in terms of degree of crystallinity (volume fractions that are ordered) and quality of ordering and their relation to the size scale of an ordered region. We are motivated in part by our own imprecise and inconsistent use of terminology in the past, as well as the need to have a primer or tutorial reference to teach new group members. We strive to develop and use consistent terminology with regards to crystallinity, semicrystallinity, paracrystallinity, and related characteristics. To account for vastly different quality of ordering along different directions, we classify paracrystals into 2D and 3D paracrystals and use paracrystallite to describe the spatial extent of molecular ordering in 1-10 nm. We show that a deeper understanding of molecular ordering can be achieved by combining grazing-incidence wide-angle X-ray scattering and differential scanning calorimetry, even though not all aspects of these measurements are consistent, and some classification appears to be method dependent. We classify a broad range of representative polymers under common processing conditions into five categories based on the quantitative analysis of the paracrystalline disorder parameter (g) and thermal transitions. A small database is presented for 13 representative conjugated and insulating polymers ranging from amorphous to semi-paracrystalline. Finally, we outline the challenges to rationally design more perfect polymer crystals and propose a new molecular design approach that envisions conceptual molecular grafting that is akin to strained and unstrained hetero-epitaxy in classic (compound) semiconductors thin film growth.

Efficient degradation of tetracycline by singlet oxygen-dominated peroxymonosulfate activation with magnetic nitrogen-doped porous carbon

Abstract: Nonradical reaction driven by peroxymonosulfate (PMS) based advanced oxidation processes has drawn widespread attention in water treatment due to their inherent advantages, but the degradation behavior and mechanism of organic pollutants are still unclear. In this study, the performance, intermediates, mechanism and toxicity of tetracycline (TC) degradation were thoroughly examined in the constructed magnetic nitrogen-doped porous carbon/peroxymonosulfate (Co-N/C-PMS) system. The results showed that 85.4% of TC could be removed within 15 min when Co-N/C and PMS was simultaneously added and the degradation rate was enhanced by 3.4 and 14.7 folds compared with Co-N/C or PMS alone, respectively. Moreover, the performance of Co-N/C was superior to that of most previously reported catalysts. Many lines of evidence indicated that Co-N/C-PMS system was a singlet oxygen-dominated nonradical reaction, which was less interfered by pH and water components, and displayed high adaptability to actual water bodies. Subsequently, the degradation process was elaborated on the basis of three-dimensional excitation-emission matrix spectra and liquid chromatography-mass spectrometry. At last, the toxicity of treated TC was greatly reduced by using microalgae Coelastrella sp. as ecological indicator. This study provides a promising approach based on singlet oxygen-dominated nonradical reaction for eliminating TC in water treatment.

Ionic Liquid Treatment for Highest‐Efficiency Ambient Printed Stable All‐Inorganic CsPbI ₃ Perovskite Solar Cells

Abstract: All-inorganic cesium lead triiodide (CsPbI3 ) perovskite is well known for its unparalleled stability at high temperatures up to 500 °C and under oxidative chemical stresses. However, upscaling solar cells via ambient printing suffers from imperfect crystal quality and defects caused by uncontrollable crystallization. Here, the incorporation of a low concentration of novel ionic liquid is reported as being promising for managing defects in CsPbI3 films, interfacial energy alignment, and device stability of solar cells fabricated via ambient blade-coating. Both theoretical simulations and experimental measurements reveal that the ionic liquid successfully regulates the perovskite thin-film growth to decrease perovskite grain boundaries, strongly coordinates with the undercoordinated Pb2+ to passivate iodide vacancy defects, aligns the interface to decrease the energy barrier at the electron-transporting layer, and relaxes the lattice strain to promote phase stability. Consequently, ambient printed CsPbI3 solar cells with power conversion efficiency as high as 20.01% under 1 sun illumination (100 mW cm-2 ) and 37.24% under indoor light illumination (1000 lux, 365 µW cm-2 ) are achieved; both are the highest for printed all-inorganic cells for corresponding applications. Furthermore, the bare cells show an impressive long-term ambient stability with only ≈5% PCE degradation after 1000 h aging under ambient conditions.

Observer Based Generalized Active Damping for Voltage Source Converters With LCL Filters

Abstract: An observer-based active damping (AD) controller is proposed along with a unified design and implementation framework for LCL-equipped voltage source converters. The AD controller uses feedback of either of the converter-side current or the grid-side current along with that of the grid voltage. The state of the arts offer observer-based AD only for current-mode control and are limited by their inflexibility to be used in conjunction with established supplementary control methods or by the lack of damping efficacy for all configurations of LCL resonance frequency and the measured current (grid-side vs. converter-side). The proposed AD method is identically applicable for current-mode control and virtual oscillator control (VOC) where explicit voltage/current tracking loops are not used. The proposed AD controller thus overcomes a major limitation of VOC which otherwise offers robust synchronization in reduced/zero-inertia networks and enhanced fault ride-through capability. Simplified design guidelines are presented through comprehensive small-signal analysis including the observer dynamics. The proposed method is shown to be effective for both converter-side and grid-side current measurements irrespective of the LCL resonance frequency relative to the critical frequency. The analysis and design methods are validated through laboratory hardware experiments.

Dielectric and mechanical properties of hypersonic radome materials and metamaterial design: A review

Abstract: This review paper examines ten current ceramic radome materials under research and development and provides a comprehensive overview of available high temperature and high frequency data from literature. An examination of metamaterials for radio-frequency transparent radomes is given and our preliminary experimental results of a high-temperature metamaterial design are presented. The next-generation hypersonic vehicles’ radome temperatures will exceed 1000℃ and speeds will exceed Mach 5. An ideal radome material will have a high flexural strength, low dielectric constant and loss tangent, and high resistance to thermal shock and corrosion. The microstructural effect on the dielectric and mechanical properties and the effects of environmental factors such as rain are discussed. The impact of metamaterial structure on key radome factors such as boresight error, gain, and polarization is examined. After examining the associated benefits with the use of metamaterials, our preliminary results for a potential high-temperature metamaterial design are presented.

Exploring Data Analytics Without Decompression on Embedded GPU Systems

Abstract: With the development of computer architecture, even for embedded systems, GPU devices can be integrated, providing outstanding performance and energy efficiency to meet the requirements of different industries, applications, and deployment environments. Data analytics is an important application scenario for embedded systems. Unfortunately, due to the limitation of the capacity of the embedded device, the scale of problems handled by the embedded system is limited. In this paper, we propose a novel data analytics method, called G-TADOC, for efficient text analytics directly on compression on embedded GPU systems. A large amount of data can be compressed and stored in embedded systems, and can be processed directly in the compressed state, which greatly enhances the processing capabilities of the systems. Particularly, G-TADOC has three innovations. First, a novel fine-grained thread-level workload scheduling strategy for GPU threads has been developed, which partitions heavily-dependent loads adaptively in a fine-grained manner. Second, a GPU thread-safe memory pool has been developed to handle inconsistency with low synchronization overheads. Third, a sequence-support strategy is provided to maintain high GPU parallelism while ensuring sequence information for lossless compression. Moreover, G-TADOC involves special optimizations for embedded GPUs, such as utilizing the CPU-GPU shared unified memory. Experiments show that G-TADOC provides 13.2× average speedup compared to the state-of-the-art TADOC. G-TADOC also improves performance-per-cost by 2.6× and energy efficiency by 32.5× over TADOC.

Centimeter-Sized 2D Perovskitoid Single Crystals for Efficient X-ray Photoresponsivity

Abstract: Metal-halide perovskitoids with corner-, edge-, and face-sharing octahedra provide a fertile “playground” for structure modulation. With low defect density, low ion migration, and high intrinsic stability, two-dimensional (2D) perovskitoid single crystals are expected to be ideal materials for room-temperature semiconductor detectors (RTSDs) as high-energy radiation. However, there is no report yet on the use of 2D perovskitoid single crystals for X-ray detection, as well as on how the halide-modulated molecular assembly would affect their structure and properties. Herein, based on an amidino-based organic spacer, we successfully synthesized a novel family of centimeter-sized 2D perovskitoid single crystals, (3AP)PbX4 (3AP = 3-amidinopyridine, X = Cl, Br, and I). This is the first time that centimeter-sized 2D perovskitoid single crystals are demonstrated for X-ray photoresponse. Detailed investigations reveal a unique crystal packing with corner-sharing and edge-sharing octahedra of inorganic frameworks and 3AP cations lying between adjacent inorganic layers in a parallel and antisymmetric manner. Changing the halide from I to Br and Cl results in greater Pb–X–Pb angles and stronger hydrogen bonding in perovskitoids and therefore consequently a better elastic recovery under stress, a more efficient charge transport in the inorganic layer, and a lower ionic migration. By varying halide substitution, an efficient X-ray photoresponse is achieved with a sensitivity up to 791.8 μC Gyair–1 cm–2 for (3AP)PbCl4 and a low detection limit of 1.54 μGyair s–1. These results reveal that the large 2D perovskitoid single crystals provide a promising platform for high performance optoelectronics.

A hydrologist's guide to open science

Abstract: Abstract. Open, accessible, reusable, and reproducible hydrologic research can have a significant positive impact on the scientific community and broader society. While more individuals and organizations within the hydrology community are embracing open science practices, technical (e.g., limited coding experience), resource (e.g., open access fees), and social (e.g., fear of weaknesses being exposed or ideas being scooped) challenges remain. Furthermore, there are a growing number of constantly evolving open science tools, resources, and initiatives that can be overwhelming. These challenges and the ever-evolving nature of the open science landscape may seem insurmountable for hydrologists interested in pursuing open science. Therefore, we propose the general “Open Hydrology Principles” to guide individual and community progress toward open science for research and education and the “Open Hydrology Practical Guide” to improve the accessibility of currently available tools and approaches. We aim to inform and empower hydrologists as they transition to open, accessible, reusable, and reproducible research. We discuss the benefits as well as common open science challenges and how hydrologists can overcome them. The Open Hydrology Principles and Open Hydrology Practical Guide reflect our knowledge of the current state of open hydrology; we recognize that recommendations and suggestions will evolve and expand with emerging open science infrastructures, workflows, and research experiences. Therefore, we encourage hydrologists all over the globe to join in and help advance open science by contributing to the living version of this document and by sharing open hydrology resources in the community-supported repository (https://open-hydrology.github.io, last access: 1 February 2022).

Learning Distributed Stabilizing Controllers for Multi-Agent Systems

Abstract: We address model-free distributed stabilization of heterogeneous continuous-time linear multi-agent systems using reinforcement learning (RL). Two algorithms are developed. The first algorithm solves a centralized linear quadratic regulator (LQR) problem without knowing any initial stabilizing gain in advance. The second algorithm builds upon the results of the first algorithm, and extends it to distributed stabilization of multi-agent systems with predefined interaction graphs. Rigorous proofs are provided to show that the proposed algorithms achieve guaranteed convergence if specific conditions hold. A simulation example is presented to demonstrate the theoretical results.

PUSHing Core-collapse Supernovae to Explosions in Spherical Symmetry. V. Equation of State Dependency of Explosion Properties, Nucleosynthesis Yields, and Compact Remnants

Abstract: Abstract In this fifth paper of the series, we use the parameterized, spherically symmetric explosion method PUSH to investigate the impact of eight different nuclear equations of state (EOS). We present and discuss the explosion properties and the detailed nucleosynthesis yields, and predict the remnant (neutron star or black hole) for all our simulations. For this, we perform two sets of simulations. First, a complete study of nonrotating stars from 11 to 40 M ⊙ at three different metallicities using the SFHo EOS; and, second, a suite of simulations for four progenitors (16 M ⊙ at three metallicities and 25 M ⊙ at solar metallicity) for eight different nuclear EOS. We compare our predicted explosion energies and yields to observed supernovae and to the metal-poor star HD 84937. We find EOS-dependent differences in the explosion properties and the nucleosynthesis yields. However, when comparing to observations, these differences are not large enough to rule out any EOS considered in this work.

Branched Alkoxy Side Chain Enables High-Performance Non-Fullerene Acceptors with High Open-Circuit Voltage and Highly Ordered Molecular Packing

Abstract: The linear alkyl chains on the β-position of the thieno[3,2-b]thiophene units of Y6 play a critical role in determining the molecular properties of non-fullerene acceptors (NFAs) and device performance of the corresponding organic solar cells (OSCs). This linear chain can be substituted with either alkoxy or branched alkyl side chains, which are two common strategies to modify the property of Y6-type molecules. In this paper, we use a combination of these two strategies by using branched alkoxy side chains to modify Y6 and develop a new NFA named Y6-O2BO. Interestingly, this branched alkoxy substitution introduces different effects from previously used branched alkyl or linear alkoxy modifications. More ordered molecular packing and enhanced crystallinity are observed for Y6-O2BO-based blend films, which should be beneficial for charge carrier transportation. The Y6-O2BO-based device exhibits a much enhanced open-circuit voltage (VOC) compared to those based on linear alkoxy or branched alkyl chain substituted molecules. By using a mixture of Y6 and Y6-O2BO, the VOC of ternary devices can be linearly tuned between 0.84 and 0.96 V based on the ratio of these two acceptors. As a result, the optimal OSC yields an improved VOC of 0.88 V and a high FF of 0.79, leading to a maximum efficiency of 17.5%. This reveals the effectiveness of branched alkoxy chains in elevating VOC and further optimizing the performance of OSCs.

Robotic Knee Tracking Control to Mimic the Intact Human Knee Profile Based on Actor-Critic Reinforcement Learning

Abstract: We address a state-of-the-art reinforcement learning (RL) control approach to automatically configure robotic prosthesis impedance parameters to enable end-to-end, continuous locomotion intended for transfemoral amputee subjects. Specifically, our actor-critic based RL provides tracking control of a robotic knee prosthesis to mimic the intact knee profile, This is a significant advance from our previous RL based automatic tuning of prosthesis control parameters which have centered on regulation control with a designer prescribed robotic knee profile as the target. In addition to presenting the tracking control algorithm based on direct heuristic dynamic programming (dHDP), we provide a control performance guarantee including the case of constrained inputs. We show that our proposed tracking control possesses several important properties, such as weight convergence of the learning networks, Bellman (sub) optimality of the cost-to-go value function and control input, and practical stability of the human-robot system. We further provide a systematic simulation of the proposed tracking control using a realistic human-robot system simulator, the OpenSim, to emulate how the dHDP enables level ground walking, walking on different terrains and at different paces. These results show that our proposed dHDP based tracking control is not only theoretically suitable, but also practically useful.