Article
Economics
Sina Bahrami, Matthew Roorda
Summary: This study investigates the parking decisions of autonomous vehicle users and their impact on congestion. It was found that users may choose to park at home or travel longer distances to save money on parking fees. Implementing a uniform parking price could exacerbate congestion, but charging tolls for zero-occupant AVs could decrease vehicle kilometers traveled.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Mechanics
Keith Davey, Jingwen Zhang, Rooholamin Darvizeh
Summary: This paper introduces a two-experiment theory for fracture mechanics underpinned by experimental tests performed at two distinct scales. It is shown how the size effect associated with defect size is immediately accounted for, providing significantly improved representative behavior than can be otherwise achieved through experiments at a single scale.
ENGINEERING FRACTURE MECHANICS
(2022)
Article
Transportation Science & Technology
Baichuan Mo, Zhejing Cao, Hongmou Zhang, Yu Shen, Jinhua Zhao
Summary: The study examines the competitive relationship between autonomous vehicles and public transportation system, evaluating competition process, system performance, and stakeholder perspectives, as well as the impact of subsidies on competition results. The results show that competition can improve operators' profits and system efficiency, but may increase passengers' travel costs, highlighting the importance of optimizing supply strategies under specific operation goals and constraints.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Energy & Fuels
Ashish Kumar Loomba, Vinicius Eduardo Botechia, Denis Jose Schiozer
Summary: This study proposed and compared four workflows to optimize field development plans efficiently under uncertainty, resulting in significant reduction in computational time and cost. By considering various scenarios and employing predictive analytics, the study demonstrated improvements in field optimization within a shorter timeframe, providing practical solutions for field development while capturing associated uncertainty.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Mechanical
Wei Sun, Qingrui Song, Kun Liu, Xiaojun Liu, Jiaxin Ye
Summary: The addition of nano-sized fillers can greatly reduce the wear rate of polytetrafluoroethylene by forming a protective transfer film. The wear reduction is influenced by the properties of the polymer wear surface and the roughness of the transfer film.
Article
Computer Science, Interdisciplinary Applications
Amin Rezaei, Brian Caulfield
Summary: The study showed that AVs could significantly improve traffic quality, particularly by reducing stops, queue length, and delay time. Both TVs and AVs can efficiently share the road, with traffic quality improvement increasing as the proportion of AVs to TVs increases.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Automation & Control Systems
Matthew R. Wilkinson, Bernardo Castro-Dominguez, Chick C. Wilson, Uriel Martinez-Hernandez
Summary: This study modifies a 3D printer to enable rapid and autonomous sample characterization in pharmaceutical particle analysis, using low-cost hardware and open-source software. The system overcomes the limitations of subjective labeling and limited data in machine learning models, and allows researchers without access to sophisticated automation platforms to generate larger datasets for data-driven models.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Kung-Jeng Wang, Agustina Eunike, Ivan Kurniawan, Romadhani Ardi, Jing-Ming Chiu
Summary: This study utilizes agent-based simulation modelling to investigate the sequencing and scheduling performance of GPU-card assembly line, aiming to fully utilize resources and resolve conflicts between part tardiness and throughput.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Maryam Zarghami Dehaghani, Fatemeh Molaei, Farrokh Yousefi, S. Mohammad Sajadi, Amin Esmaeili, Ahmad Mohaddespour, Omid Farzadian, Sajjad Habibzadeh, Amin Hamed Mashhadzadeh, Christos Spitas, Mohammad Reza Saeb
Summary: Simulation of the thermal properties of BC(3)GrHs revealed that the presence of grain boundaries with topological defects such as pentagons and heptagons can significantly impact the interfacial thermal resistance. The Kapitza resistance was found to increase with higher defect density in the grain boundary. Symmetric grain boundaries with 5-7-6-6 and 5-7-5-7 defect pairs showed the lowest and highest values of Kapitza resistance, respectively, indicating the importance of defect structure in thermal properties. Additionally, temperature and strain were observed to affect the Kapitza resistance, while the length of the nanosheets and temperature gradient had a negligible effect.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Interdisciplinary Applications
Eduardo Felipe Zambom Santana, Gustavo Covas, Fabio Duarte, Paolo Santi, Carlo Ratti, Fabio Kon
Summary: The system of autonomous vehicles co-existing with human-driven vehicles is expected to reduce travel time for urban commuters and decrease the space required to handle traffic.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Chemistry, Physical
Evan Pretti, M. Scott Shell
Summary: Bottom-up coarse-graining methods provide systematic tools for creating simplified models of molecular systems, but the resulting coarse-grained models often fail to accurately reproduce all thermodynamic properties of the reference atomistic systems. This work introduces a new strategy for creating temperature-transferable CG models based on effective entropy functions and relative entropy minimization, allowing for improved temperature dependence predictions and parameterization. The approach is demonstrated to be successful for creating temperature-transferable CG models for complex molecular liquids.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Environmental Sciences
Kathiravan Thangavel, Dario Spiller, Roberto Sabatini, Stefania Amici, Sarathchandrakumar Thottuchirayil Sasidharan, Haytham Fayek, Pier Marzocca
Summary: This study focuses on the application of space-borne technology for accurate fire detection. By training convolutional neural networks, the feasibility of classifying wildfires in space missions is demonstrated. Onboard data processing proves to be beneficial for disaster management and climate change mitigation, enabling timely alerts and rapid responses.
Article
Computer Science, Artificial Intelligence
Jingwei Lu, Liyuan Han, Qinglai Wei, Xiao Wang, Xingyuan Dai, Fei-Yue Wang
Summary: This paper investigates event-triggered deep reinforcement learning using parallel control and proposes an event-triggered deep Q-network (ETDQN) for decision-making in autonomous driving. The ETDQN integrates action information into the feedback and constructs a dynamic control policy. The developed ETDQN outperforms dueling DDQN and reduces communication loss in event-triggered control.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Chemistry, Analytical
Sathwik S. Kasyap, Kostas Senetakis
Summary: The study focused on characterizing the grain-scale properties of the Mojave Mars Simulant, particularly the frictional and crushing behavior of small size samples. The results presented the micromechanical tribological response of Mars simulant for the first time and attempted to compare its behavior with other Earth and extra-terrestrial materials. Despite similarities with Moon simulants, significant differences were found in the severe damage of the grain surfaces of the MMS-1 samples, linked to dilation behavior at the grain-scale.
Article
Engineering, Petroleum
Faras Al Balushi, Qitao Zhang, Arash Dahi Taleghani
Summary: This study presents a novel concept for autonomously controlling fracture conductivity based on surrounding temperature. By utilizing proppants with negative thermal expansion coefficients, fracture conductivity can be adjusted according to temperature to achieve uniform flow across the fracture network. Microscale analysis shows an enhancement in permeability and fracture conductivity by half. Field-scale analysis confirms the effectiveness of this concept, with 31.4% more heat being extracted from EGS over 50 years of production when using the proposed proppants.
Article
Chemistry, Multidisciplinary
Joseph M. Palomba, Verda Saygin, Keith A. Brown
Summary: We developed a system that combines a MOF crystallite with an atomic force microscope cantilever to study the interaction between single-crystal MOFs and polymer films. By using this method, we discovered evidence of polymer intercalation into MOF pores. This approach can expedite the design of composites.
CHEMICAL COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Yihong Xu, Keith A. Brown
Summary: Efficiently pumping fluids without moving parts in miniaturized formats is challenging. In this study, a new type of fluid pump based on traveling-wave dielectrophoresis (twDEP) is proposed and explored numerically. The pump utilizes a series of electrodes driven at different phases to directly exert force on fluid molecules, enabling efficient fluid motion. The performance of twDEP pumps is predicted by a general equation that factors in voltage squared divided by the electrode period, complex permittivity of the fluid, and viscosity. The study suggests that the use of high power microwave technology and metasurfaces could make twDEP pumps practical.
Article
Chemistry, Physical
Wenlu Wang, Zhaoyi Zheng, Anton B. Resing, Keith A. Brown, Joerg G. Werner
Summary: This report presents an approach for obtaining conformal polymeric thin films on 3D structures using custom-designed dual-functional monomers. The authors demonstrated the full coating of a 3D mesoscaled battery electrode with an ultrathin lithium-ion permeable film using a specific monomer. The study provides insights into the control of thickness, permeability, and electronic properties of the films.
MOLECULAR SYSTEMS DESIGN & ENGINEERING
(2023)
Correction
Nanoscience & Nanotechnology
Verda Saygin, Bowen Xu, Sean B. Andersson, Keith A. Brown
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Materials Science, Multidisciplinary
Milad Abolhasani, Keith A. Brown
Summary: In the past five years, artificial intelligence (AI) has made significant advancements in various aspects of daily life, such as health, transportation, and the digital world, by utilizing data. Inspired by these success stories, materials researchers have started to incorporate AI into experimental materials science to accelerate materials discovery and development. This article reviews the role of AI in experimental materials science and summarizes the key aspects and challenges of autonomous experimentation discussed in each contributed article.
Article
Materials Science, Multidisciplinary
Marcus M. Noack, Kristofer G. Reyes
Summary: The fields of machine learning (ML) and artificial intelligence (AI) have had a significant impact on science and engineering. The success of ML depends heavily on the sophistication of the underlying mathematical methods and software. This paper explores the connections between mathematics and ML, with a focus on Gaussian process-driven autonomous experimentation.
Article
Materials Science, Multidisciplinary
Xiting Peng, Xiaonan Wang, Keith A. Brown, Milad Abolhasani
Summary: The contradiction between the importance of materials to modern society and their slow development process has led to the emergence of intelligent laboratories, which integrate high-throughput experimentation, automation, theoretical computing, and artificial intelligence. These laboratories can autonomously carry out designed experiments and make scientific discoveries. This article presents the basic concepts and foundations of this new research paradigm, showcases typical application scenarios through case studies, and envisions a collaborative human-machine meta laboratory in the future.
Article
Multidisciplinary Sciences
Amanda A. Volk, Robert W. Epps, Daniel T. Yonemoto, Benjamin S. Masters, Felix N. Castellano, Kristofer G. Reyes, Milad Abolhasani
Summary: AlphaFlow is a self-driven fluidic lab that enables autonomous discovery and optimization of complex multi-step chemistries through reinforcement learning. It successfully identified and optimized a novel multi-step reaction route that outperformed conventional sequences.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Marcus M. Noack, Harinarayan Krishnan, Mark D. Risser, Kristofer G. Reyes
Summary: A Gaussian Process (GP) is a mathematical framework for stochastic function approximation, widely used in science and engineering. However, exact GPs are computationally expensive for large datasets, leading to the development of various approximation methods.
SCIENTIFIC REPORTS
(2023)
Article
Materials Science, Multidisciplinary
Verda Saygin, Kelsey Snapp, Aldair E. Gongora, Rashid Kolaghassi, Keith A. Brown
Summary: Vat polymerization is widely used for additive manufacturing of micro-architected structures. This study investigates the influence of oxygen inhibition on the mechanical properties of structures made using this technique. The surface of the structures was found to be incompletely cured, leading to softer properties. Post-print curing in nitrogen improved stiffness compared to air, but oxygen during printing resulted in softer samples than nitrogen photocured samples. These results highlight the significant impact of oxygen inhibition on micro-architected structures realized using vat polymerization.
ADVANCED MATERIALS TECHNOLOGIES
(2023)
Article
Engineering, Biomedical
Andre Gutierrez Marty, Paul E. Barbone, Elise F. Morgan
Summary: This study aims to understand how aging-related changes in cortical bone microstructure affect mechanical properties at the macroscale. By modeling cortical bone as a bundle of elastic-plastic fibers and simulating aging-related changes, the study found that changes to all three input parameters were needed to capture the decline in mechanical properties. Rupture of interstitial fibers led to initial strength loss, while plasticity and gradual rupture of osteons contributed to the remainder of the response.
JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS
(2023)
Article
Materials Science, Multidisciplinary
Chu Te Chen, Yu Fu, Xin Gao, Anthony Butler, Kristofer Reyes, Huamin Li, Michael Pentaris, Ajay Yadav, Keith T. Wong, Hongyan Yue, Fei Yao
Summary: This article reviews the latest advancements in 2D van der Waals heterostructures and mixed low-dimensional hybrids (MLDHs) in terms of structure construction and electrochemical applications. It discusses the synergistic effect of MLDH integration in advancing electrochemical energy applications and explores how mixed-dimensional physics and chemistry influence the performance of metal ion batteries and the electrocatalytic hydrogen evolution reaction.
Article
Materials Science, Multidisciplinary
Aldair E. Gongora, Kelsey L. Snapp, Richard Pang, Thomas M. Tiano, Kristofer G. Reyes, Emily Whiting, Timothy J. Lawton, Elise F. Morgan, Keith A. Brown
Summary: This research develops a transfer learning approach to predict impact protection using more widely available quasi-static testing, successfully predicting impact performance of different structures and showing that this method can accelerate design for specialty applications.
Article
Automation & Control Systems
Fazel Bateni, Robert W. Epps, Kameel Antami, Rokas Dargis, Jeffery A. Bennett, Kristofer G. Reyes, Milad Abolhasani
Summary: Lead halide perovskite nanocrystals are considered advanced functional materials with outstanding optoelectronic characteristics, but their precise synthesis and fundamental studies remain challenging. An autonomous fluidic micro-processor has been developed to accelerate complex synthesis and processing parameters, demonstrating efficient and intelligent navigation through halide exchange and cation doping reactions. This strategy can be further applied for autonomous discovery and development of novel impurity-doped nanocrystals for next-generation energy technologies.
ADVANCED INTELLIGENT SYSTEMS
(2022)
