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At least 1,423 records · Page 79

Co‐culture engineering for microbial biosynthesis of 3‐amino‐benzoic acid in Escherichia coli

Abstract 3‐amino‐benzoic acid (3AB) is an important building block molecule for production of a wide range of important compounds such as natural products with various biological activities. In the present study, we established a microbial biosynthetic system for de novo 3AB production from the simple substrate glucose. First, the active 3AB biosynthetic pathway was reconstituted in the bacterium Escherichia coli , which resulted in the production of 1.5 mg/L 3AB. In an effort to improve the production, an E. coli ‐ E. coli co‐culture system was engineered to modularize the biosynthetic pathway between an upstream strain and an downstream strain. Specifically, the upstream biosynthetic module was contained in a fixed E. coli strain, whereas a series of E. coli strains were engineered to accommodate the downstream biosynthetic module and screened for optimal production performance. The best co‐culture system was found to improve 3AB production by 15 fold, compared to the mono‐culture approach. Further engineering of the co‐culture system resulted in biosynthesis of 48 mg/L 3AB. Our results demonstrate co‐culture engineering can be a powerful new approach in the broad field of metabolic engineering.

Zhang, Haoran↗

Molecularly Functionalized Electrodes for Efficient Electrochemical Water Remediation

Here, the development and investigation of materials that leverage unique interfacial effects on electronic structure and redox chemistry are likely to play an outstanding role in advanced technologies for wastewater treatment. Here, the use of surface functionalization of metal oxides with a Ru(II)poly(pyridyl) complex was reported as a way to create hybrid assemblies with optimized electrochemical performance for water remediation, superior to those that could be achieved with the molecular catalyst or metal-oxide electrodes used individually. Mechanistic analysis demonstrated that the molecularly functionalized electrodes could suppress the formation of hydroxyl radicals (i. e., the dominant remediation pathway for bare metal-oxide electrodes), allowing the water remediation to proceed through the highly oxidizing Ru 3+ ions in the surface-bound complexes. Furthermore, the underlying metal-oxide substrates played a crucial role in altering the electronic structure and electrochemical properties of the surface-bound catalyst, such that the competing side reaction (i. e., water splitting) was largely inhibited.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Screening and Discovery of Metal Compound Active Sites for Strong and Selective Adsorption of N 2 in Air

Photocatalytic nitrogen fixation has the potential to provide a greener route for producing nitrogen-based fertilizers under ambient conditions. Computational screening is a promising route to discover new materials for the nitrogen fixation process, but requires identifying “descriptors” that can be efficiently computed. In this work, we argue that selectivity toward the adsorption of molecular nitrogen and oxygen can act as a key descriptor. A catalyst that can selectively adsorb nitrogen and resist poisoning of oxygen and other molecules present in air has the potential to facilitate the nitrogen fixation process under ambient conditions. Here we provide a framework for active site screening based on multifidelity density functional theory (DFT) calculations for a range of metal oxides, oxyborides, and oxyphosphides. The screening methodology consists of initial low-fidelity fixed geometry calculations and a second screening in which more expensive geometry optimizations were performed. The approach identifies promising active sites on several TiO 2 polymorph surfaces and a VBO 4 surface, and the full nitrogen reduction pathway is studied with the BEEF-vdW and HSE06 functionals on two active sites. The findings suggest that metastable TiO 2 polymorphs may play a role in photocatalytic nitrogen fixation, and that VBO 4 may be an interesting material for further studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lattice dynamics and thermoelectric properties of diamondoid materials

Abstract The diamondoid compounds are a large family of important semiconductors, which possess various unique transport properties and had been widely investigated in the fields of photoelectricity and nonlinear optics. For a significantly long period of time, diamondoid materials were not given much attention in the field of thermoelectricity. However, this changed when a series of diamondoid compounds showed a thermoelectric figure of merit ( ZT ) greater than 1.0. This discovery sparked considerable interest in further exploring the thermoelectric properties of diamondoid materials. This review aims to provide a comprehensive view of our current understanding of thermal and electronic transport in diamondoid materials and stimulate their development in thermoelectric applications. We present a collection of recent discoveries concerning the lattice dynamics and electronic structure of diamondoid materials. We review the underlying physics responsible for their unique electrical and phonon transport behaviors. Moreover, we provide insights into the advancements made in the field of thermoelectricity for diamondoid materials and the corresponding strategies employed to optimize their performance. Lastly, we emphasize the challenges that lie ahead and outline potential avenues for future research in the domain of diamondoid thermoelectric materials.

Xie, Hongyao↗

Flexible‐rate optoelectronic wireless transmission system at 101 GHz using multiband CAP‐PAM modulation and envelope detection

Abstract In this paper, we have experimentally demonstrated the first flexible‐rate optoelectronic terahertz wireless transmission system at 101 GHz based on multiband CAP‐PAM modulation and cost‐efficient envelope detection. Instead of traditional M‐QAM mapping, PAM‐N mapping is used in CAP modulation with low‐computational complexity. The system performances and optimal capacity in both single‐band case and multiband case are intensively investigated. The results show that the highest data rate for single‐band system is 13.35 Gbit/s with CAP‐PAM‐5 modulation, while the optimum aggregate transmission line rate of 8.49 Gbit/s can be obtained with 4‐sub‐bands CAP‐PAM‐{5,3,2,2} modulation under 7% FEC limit of 3.8 × 10 −3 for four‐user access.

Zhang, Jiao↗

Ab initio simulations of liquid electrolytes for energy conversion and storage

Understanding physicochemical properties of liquid electrolytes is essential for predicting and optimizing device performance for a wide variety of emerging energy technologies, including photoelectrochemical water splitting, supercapacitors, and batteries. We review recent progress and open challenges in predicting structural, dynamical, and electronic properties of the liquids using first-principles approaches. We briefly summarize the basic concepts of first-principles molecular dynamics (FPMD), and we discuss how FPMD methods have enriched our understanding of a number of liquids, including aqueous solutions, organic electrolytes and ionic liquids. We also discuss technical challenges in extending FPMD simulations to the study of liquid electrolytes in more complex environments, including the interface between electrolytes and electrodes, which is a key component in many energy storage and conversion systems.

25 ENERGY STORAGE↗

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗

Post‐Annealing Treatment on Hydrothermally Grown Antimony Sulfoselenide Thin Films for Efficient Solar Cells

Herein, antimony sulfoselenide (Sb 2 (S, Se) 3 ) thin‐film solar cells are fabricated by a hydrothermal method followed by a post‐deposition annealing process at different temperatures and the impact of the annealing temperature on the morphological, structural, optoelectronic, and defect properties of the hydrothermally grown Sb 2 (S, Se) 3 films is investigated. It is found that a proper annealing temperature leads to high‐quality Sb 2 (S, Se) 3 films with large crystal grains, high crystallinity, preferred crystal orientation, smooth and uniform morphology, and reduced defect density. These results show that suppressing deep‐level defects is crucial to enhance solar cell performance. After optimizing the annealing process, Sb 2 (S, Se) 3 solar cells with an improved power conversion efficiency 2.04 to 8.48% are obtained.

14 SOLAR ENERGY↗

Design space exploration and decision‐making for a segmented ultralight morphing 50‐MW wind turbine

Abstract Wind turbine design encompasses many different aspects including aerodynamic, structural, electrical, and control system design. To achieve optimal plant performance, a system design approach is utilized in which the performance of the whole wind turbine is evaluated and quantified during operational scenarios with subsystem interactions. In this paper, the design for a Segmented Ultralight Morphing Rotor (SUMR) 50‐MW wind turbine is presented utilizing levelized cost of energy (LCOE) for design choices, with additional quantification of simulated performance shortcomings at the 50‐MW scale. The multi‐disciplinary design process results in a final ultra‐scale turbine configuration that outperforms other existing offshore wind farms regarding the LCOE.

Kianbakht, Sepideh↗

The FMO-DFTB Method

Although the fragment molecular orbital (FMO) method enables electronic structure calculations with near-linear scaling behavior with respect to system size, the computational cost of ab initio methods typically employed in conjunction with FMO is still prohibitive for routine calculations of very large systems or long timescale molecular dynamics simulations. We, therefore, combined the FMO and density-functional tight-binding (DFTB) method, which is one of the emerging semi-empirical quantum chemical methods, and have demonstrated that FMO-DFTB is capable of performing geometry optimizations for systems containing up to one million atoms using limited computational resources. In this chapter, we will review the basics of the DFTB method first before introducing FMO-DFTB, focusing on the relationship with density functional theory and other FMO methodologies. We also demonstrate the latest scalings of FMO-DFTB2 and DFTB3 using three-dimensional water clusters, showing that the most favorable scaling is O(N1.16). Applications of FMO-DFTB to various systems are briefly summarized, and an outlook to future applications is provided.

Nishimoto, Yoshio↗

Possible role of interference, protein noise, and sink effects in nonphotochemical quenching in photosynthetic complexes

Here, we analyze theoretically a simple and consistent quantum mechanical model that reveals the possible role of quantum interference, protein noise, and sink effects in the nonphotochemical quenching (NPQ) in light-harvesting complexes (LHCs). The model consists of a network of five interconnected sites (excitonic states of light-sensitive molecules) responsible for the NPQ mechanism. The model also includes the “damaging” and the dissipative channels. The damaging channel is responsible for production of singlet oxygen and other destructive outcomes. In this model, both damaging and “dissipative” charge transfer channels are described by discrete electron energy levels attached to their sinks, that mimic the continuum part of electron energy spectrum. All five excitonic sites interact with the protein environment that is modeled using a stochastic process. Our approach allowed us to derive the exact and closed system of linear ordinary differential equations for the reduced density matrix and its first momentums. Moreover, these equations are solved numerically including for strong interactions between the light-sensitive molecules and protein environment. As an example, we apply our model to demonstrate possible contributions of quantum interference, protein noise, and sink effects in the NPQ mechanism in the CP29 minor LHC. The numerical simulations show that using proper combination of quantum interference effects, properties of noise, and sinks, one can significantly suppress the damaging channel. Finally, our findings demonstrate the possible role of interference, protein noise, and sink effects for modeling, engineering, and optimizing the performance of the NPQ processes in both natural and artificial light-harvesting complexes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive wavelet compression of large additive manufacturing experimental and simulation datasets

New manufacturing technologies such as additive manufacturing require research and development to minimize the uncertainties in the produced parts. The research involves experimental measurements and large simulations, which result in huge quantities of data to store and analyze. We address this challenge by alleviating the data storage requirements using lossy data compression. We select wavelet bases as the mathematical tool for compression. Unlike images, additive manufacturing data is often represented on irregular geometries and unstructured meshes. Thus, we use Alpert tree-wavelets as bases for our data compression method. We first analyze different basis functions for the wavelets and find the one that results in maximal compression and miminal error in the reconstructed data. We then devise a new adaptive thresholding method that is data-agnostic and allows a priori estimation of the reconstruction error. Finally, we propose metrics to quantify the global and local errors in the reconstructed data. One of the error metrics addresses the preservation of physical constraints in reconstructed data fields, such as divergence-free stress field in structural simulations. While our compression and decompression method is general, we apply it to both experimental and computational data obtained from measurements and thermal/structural modeling of the sintering of a hollow cylinder from metal powders using a Laser Engineered Net Shape process. The results show that monomials achieve optimal compression performance when used as wavelet bases. The new thresholding method results in compression ratios that are two to seven times larger than the ones obtained with commonly used thresholds. Overall, adaptive Alpert tree-wavelets can achieve compression ratios between one and three orders of magnitude depending on the features in the data that are required to preserve. Furthermore, these results show that Alpert tree-wavelet compression is a viable and promising technique to reduce the size of large data structures found in both experiments and simulations.

42 ENGINEERING↗

The Effect of Membrane Structure Prepared from Carboxymethyl Cellulose and Cellulose Nanofibrils for Cationic Dye Removal

Water-stable and eco-friendly membranes were fabricated from carboxymethyl cellulose (CMC) acting as anionic adsorbent and cellulose nanofibrils (CNFs) as strengthening filler by solvent- and unidirectional freeze-casting processes, both supported with simultaneous citric acid (CA) mediated cross-linking. Spectroscopic, thermogravimetric and potentiometric titration techniques were applied to evaluate the efficacy of the cross-linking as well as to quantify the processing-dependant surface charge. In addition, the CMC/CNF assembling and membrane porosity were identified microscopically as the combinatorial effect of components ratio and the applied fabrication technique. Finally, the membrane’s cationic dyes adsorption capacity and kinetic were evaluated depending on the dyes ionization constants, solution pH, and the contact time using batch equilibrium experiment, and further evaluated for filtration performance at optimal pH. The resulting, freeze-casted membranes demonstrate anisotropic to isotropic and highly (> 90%) porous structures with gradient pore sizes (from few nm up to 200 µm range). This provides relatively high and stable flux rates (150–190 kL/m{sup 2} h MPa) with ~ 100% cationic dye adsorption, fast dynamic (8.536–5.446 kg/g min) and capacity (1828–1398 g/kg), which highlight their potential in dead-end filtration technologies without need for additional separation step. The similar dye adsorption capacity was assessed for denser and nano-porous (< 50 nm) solvent-casted membranes, however, with much lower and time-declining flux rates (100–10 L/m{sup 2} h MPa), demonstrating their potential usage in spiral wound-cross-flow modules. Both types of membranes anyhow showed high dye removal capacity (≥ 90%) even after 4th (solvent-casted) and 50th (freeze-casted) reusing cycle, present a high-value alternative to commercial activated carbons or other bio-nano-absorbents.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Enhanced sensitivity of hemoglobin sensor using dual-core photonic crystal fiber

A Hemoglobin (Hb) biosensor based on dual-core photonic crystal fiber is proposed and analyzed. In this paper, the effective refractive index dependency on the Hb concentration within a blood sample is utilized in obtaining the transmission spectrum variation. The results are calculated using full vectorial finite element method. Through this study, the effect of the structure geometrical parameters on the sensor performance is optimized to maximize the sensor sensitivity. The numerical results show a sensitivity of 8.013 nm/g/dL for the X-polarized mode at 3.7 cm fiber length and 7.68 nm/g/dL for the Y-polarized mode at 3.2 cm fiber length of the proposed sensor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-Cycle Fatigue Behavior of Vacuum-Carburized 20Cr2Ni4 Steel with Different Case Depths

High-cycle fatigue behavior of vacuum-carburized 20Cr2Ni4 steel with three different case depths was studied by using rotating bending fatigue test. The results show that fatigue strength exhibits an increase–decrease pattern with increasing effective case dept, which is regarded to be mainly due to the unavoidable change in other parameters such as residual stress and grain size in case layer besides case depth. The present data and data in the available literature suggest that a dimensionless parameter of relative case depth is more appropriate to reflect the influence of case depth on fatigue strength. Further fracture surface analysis revealed that the fatigue failure was dominated by surface crack initiation mainly due to the extremely high cleanness of the tested steel with inclusion control. It is thus concluded that both relative case depth and other parameters should be comprehensively considered in obtaining optimized fatigue performance of vacuum-carburized steel.

36 MATERIALS SCIENCE↗

Effectiveness of nature-based solutions to reduce flooding in Quad Cities Metro Area (QCMA) using SWMM-HEC based flood model

Nature-based solutions (NbS) have gained significant attention as strategies for addressing urban environmental challenges, particularly since the establishment of the UN Sustainable Development Goals (SDGs) for 2030. However, the current research on NbS for urban flood management lacks comprehensive methodological approaches for identifying suitable areas and evaluating their effectiveness across different urban settings. Here, this study attempts to fill this gap by proposing a methodological framework integrating multi-criteria analysis with a SWMM-HEC-based hydrologic and hydraulic (HH) model to assess the suitability of NbS for the Quad Cities Metro Area (QCMA), consisting of Davenport, Bettendorf, Moline, and Rock Island. Eight NbS options-green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels/cisterns - were considered based on volumetric efficiency and runoff reduction efficiency. The study reveals that implementing the proposed NbS could have substantially reduced flood depths in key historical flood events by 21% in 1993, 15% in 2008, 16% in 2011, 23% in 2014, 40% in 2019, and 10% in 2023. The findings highlight a critical trade-off between peak runoff and NbS implementation: while NbS effectively reduce flood impacts, they also enhance volumetric efficiency by approximately 43%. In high-density areas of the QCMA, flood depth reductions of around 20% suggest that NbS are a viable solution for dense urban environments with limited space. This shows the potential for integrating NbS into existing infrastructure, offering a promising approach for cities facing increasing flooding risks. The proposed methodology provides a practical framework for incorporating NbS into urban stormwater management, addressing gaps in optimizing NbS performance, and offering a pathway to scale their application in other urban areas with various environmental and social contexts.

CMIP6↗

Metal Amorphous Nanocomposite (MANC) Alloy Cores with Spatially Tuned Permeability for Advanced Power Magnetics Applications

Metal amorphous nanocomposite (MANC) alloys are an emerging class of soft magnetic materials showing promise for a range of inductive components targeted for higher power density and higher efficiency power conversion applications including inductors, transformers, and rotating electrical machinery. Magnetization reversal mechanisms within these alloys are typically determined by composition optimization as well as controlled annealing treatments to generate a nanocomposite structure composed of nanocrystals embedded in an amorphous precursor. Here in this paper we demonstrate the concept of spatially varying the permeability within a given component for optimization of performance by using the strain annealing process. The concept is realized experimentally through the smoothing of the flux profile from the inner to outer core radius achieved by a monotonic variation in tension during the strain annealing process. Great potential exists for an extension of this concept to a wide range of other power magnetic components and more complex spatially varying permeability profiles through advances in strain annealing techniques and controls.

36 MATERIALS SCIENCE↗

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗