Hasil untuk "Chemical technology"

Jianwei Wang, F. Sciarrino, A. Laing et al.

Quantum technologies comprise an emerging class of devices capable of controlling superposition and entanglement of quantum states of light or matter, to realize fundamental performance advantages over ordinary classical machines. The technology of integrated quantum photonics has enabled the generation, processing and detection of quantum states of light at a steadily increasing scale and level of complexity, progressing from few-component circuitry occupying centimetre-scale footprints and operating on two photons, to programmable devices approaching 1,000 components occupying millimetre-scale footprints with integrated generation of multiphoton states. This Review summarizes the advances in integrated photonic quantum technologies and its demonstrated applications, including quantum communications, simulations of quantum chemical and physical systems, sampling algorithms, and linear-optic quantum information processing. This Review covers recent progress in integrated quantum photonics (IQP) technologies and their applications. The challenges and opportunities of realizing large-scale, monolithic IQP circuits for future quantum applications are discussed.

Jonathan Hwang, Reshma R. Rao, L. Giordano et al.

P. Tian, Yingxu Wei, M. Ye et al.

Guanying Chen, Hailong Qiu, P. Prasad et al.

Applications in Theranostics Guanying Chen,*,†,‡ Hailong Qiu,†,‡ Paras N. Prasad,*,‡,§ and Xiaoyuan Chen* †School of Chemical Engineering and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China ‡Department of Chemistry and the Institute for Lasers, Photonics, and Biophotonics, University at Buffalo, State University of New York, Buffalo, New York 14260, United States Department of Chemistry, Korea University, Seoul 136-701, Korea Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland 20892-2281, United States

Akshay R. Mankar, A. Pandey, Arindam Modak et al.

Depleting fossil reserves and growing energy needs have raised the demand for an alternative and clean energy source. The use of ubiquitously available lignocellulosic biomass for developing economic and eco-friendly large scale biorefinery applications has provided the much-needed impetus in this regard. The pretreatment process is a vital step for biomass transformation into added value products such as sugars, biofuels, etc. Different pretreatment approaches are employed to overcome the recalcitrance of lignocellulosic biomass and expedite its disintegration into individual components- cellulose, hemicellulose, and lignin. The conventional pretreatment methods lack sustainability and practicability for industrial scale up. The review encompasses the recent advances in selective physical and chemical pretreatment approaches such as milling, extrusion, microwave, ammonia fibre explosion, eutectic solvents etc. The study will allow a deeper understanding of these pretreatment processes and increase their scope as sustainable technologies for developing modern biorefineries.

M. Fomina, G. Gadd

S. Jackson

J. Callow, M. Callow

M. Mauter, M. Elimelech

S. S. Ahluwalia, D. Goyal

B. Sundman, B. Jansson, J. Andersson

A. Bridgwater, G. Peacocke

Shou-Shan Fan, M. Chapline, N. Franklin et al.

M. Mollah, R. Schennach, J. Parga et al.

B. Cushing, V. Kolesnichenko, C. O'connor

M. Gavrilescu, Y. Chisti

Hongjing Tao, Lei Zhang, Zhipeng Sun et al.

The current methods for detecting coal gangue face several challenges, including low detection accuracy, a high probability of missed detections, and inadequate real-time performance. These issues stem from the complexities associated with diverse industrial environments and mining conditions, such as the mixing of coal gangue and insufficient illumination within coal mines. A detection model, referred to as EBD-YOLO, is proposed based on YOLOv11n. First, the C3k2-EMA module is integrated with the EMA attention mechanism within the C3k2 module of the backbone network, thereby enhancing the model’s feature extraction capabilities. Second, the introduction of the BiFPN module reduces computational complexity while enriching both semantic information and detail within the model. Finally, the incorporation of the DyHead detector head further enhances the model’s ability to express features in complex environments. The experimental results indicate that the precision (P) and recall (R) of the EBD-YOLO model are 88.7% and 83.9%, respectively, while the mean average precision (mAP@0.5) is 91.7%. These metrics represent increases of 3.4%, 3.7%, and 3.9% compared to those of the original model, respectively. Additionally, the frames per second (FPS) improved by 10.01%. Compared to the mainstream YOLO target detection algorithms, the EBD-YOLO detection model achieves the highest mAP@0.5 while maintaining superior detection speed. It exhibits a slight increase in computational load, despite an almost unchanged number of parameters, and demonstrates the best overall detection performance. The EBD-YOLO detection model effectively addresses the challenges of missed detections, false detections, and real-time detection in the complex environment of coal mines.

Miisa J. Tavaststjerna, Stephen J. Picken, Santiago J. Garcia

Abstract Micropatterned surfaces with both hydrophilic and hydrophobic regions are relevant for a wide range of applications from fuel cells to water harvesting systems. The preferential nucleation of water on hydrophilic regions can also be used to control frost nucleation on chemically patterned surfaces. So far, this concept has been tested on brittle silicon surfaces with only a few different sizes and shapes of hydrophilic regions. In this work, the concept of controlled icing is investigated on five polymeric surfaces with different surface energies modified by micropatterning them with three types of hydrophilic polymer brushes. Frost formation and propagation on the resulting patterned surfaces with regions of varying wettability is monitored and quantified using high‐resolution thermal imaging. The study proves that control over frost nucleation and propagation using regions of varying wettability can be achieved on commodity polymers. In addition to influencing the time and location of ice nucleation, the local patterning affects the freezing propagation mode and rate due to its impact on the continuity and thickness of molecular water layers (MWL). These results show that local control over the state of MWLs is key to controlling both ice nucleation and propagation of freezing events on surfaces.

Michelangelo Marasco, John Kirkpatrick, Teresa Carlomagno et al.

SHP2 is a tyrosine phosphatase that plays a regulatory role in multiple intracellular signaling cascades and is known to be oncogenic in certain contexts. In the absence of effectors, SHP2 adopts an autoinhibited conformation with its N-SH2 domain blocking the active site. Given the key role of N-SH2 in regulating SHP2, this domain has been extensively studied, often by X-ray crystallography. Using a combination of structural analyses and molecular dynamics (MD) simulations we show that the crystallographic environment can significantly influence the structure of the isolated N-SH2 domain, resulting in misleading interpretations. As an orthogonal method to X-ray crystallography, we use a combination of NMR spectroscopy and MD simulations to accurately determine the conformation of apo N-SH2 in solution. In contrast to earlier reports based on crystallographic data, our results indicate that apo N-SH2 in solution primarily adopts a conformation with a fully zipped central β-sheet, and that partial unzipping of this β-sheet is promoted by binding of either phosphopeptides or even phosphate/sulfate ions.

Haoyan Ding, Wenyuan Sun, Guoyan Zheng

Periacetabular osteotomy (PAO) is an effective approach for the surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip joint and the limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted, augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 headset, which is a state-of-the-art (SOTA) optical see-through (OST) head-mounted display (HMD). For AR guidance, we propose an optical marker-based AR registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS such that the virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns a bone saw with osteotomy planes planned in preoperative images. Then, it provides surgeons with not only virtual constraints to restrict movement of the bone saw but also AR guidance for visual feedback without sight diversion, leading to higher surgical accuracy and improved surgical safety. Comprehensive experiments were conducted to evaluate both the AR registration accuracy and osteotomy accuracy of the developed navigation system. The proposed AR registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The robotic system achieved an average center translation error of 0.96 ± 0.23 mm, an average maximum distance of 1.31 ± 0.20 mm, and an average angular deviation of 3.77 ± 0.85°. Experimental results demonstrated both the AR registration accuracy and the osteotomy accuracy of the developed system.