Review
Chemistry, Physical
Shiqiang Zhao, Hang Chen, Qiaozan Qian, Hewei Zhang, Yang Yang, Wenjing Hong
Summary: This review discusses the fabrication methods and construction routes of non-covalent interaction-based molecular electronic devices with graphene electrodes, as well as the recent progress in designing new-type molecular devices based on graphene and graphene-like 2D materials. The review also provides a prospect on the challenges and opportunities of non-covalent interaction-based molecular electronics.
Article
Materials Science, Multidisciplinary
Elisa Palacios-Lidon, Jaime Colchero, Miguel Ortuno, Eduardo Colom, Ana M. Benito, Wolfgang K. Maser, Andres M. Somoza
Summary: The study demonstrates that quantitatively mapping the nanoscale charge distribution and dynamics of graphene oxide (GO) can be achieved using Kelvin probe force microscopy (KPFM). Identification of charge domains reveals important charge interactions below 20 nm. The charge dynamics exhibit very long relaxation times and a logarithmic decay of the time correlation function, in agreement with Monte Carlo simulations, revealing a hopping transport mechanism described by Efros-Shklovskii's law.
ACS MATERIALS LETTERS
(2021)
Article
Physics, Applied
Leila Eslami, Nastaran Farshchi, Santanu K. Maiti, Somaieh Ahmadi
Summary: Using Green's function method, the study examines spin-resolved thermoelectric quantum transport in a molecular junction with phenalene molecule and external graphene leads. The results show that applying magnetic exchange potential increases the Seebeck coefficients and generates a current even without bias voltage. The system acts as a spin filter at specific chemical potential and the current dramatically increases in parallel configuration.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Thermodynamics
Vishnuprasad Selvaraj, Haribabu Krishnan
Summary: In this study, graphene-silver alloyed quantum dots were synthesized using an In-situ hydrothermal method to create nanofluid suspensions for cooling electronic systems. The nanofluid showed enhanced thermal conductivity and heat transfer capabilities, making it a promising coolant for heat-generating electronic systems.
APPLIED THERMAL ENGINEERING
(2021)
Article
Chemistry, Physical
G. H. Silvestre, F. Crasto de Lima, J. S. Bernardes, A. Fazzio, R. H. Miwa
Summary: In this theoretical study, the nanocellulose/graphene interfaces were investigated using first-principles calculations. It was found that the binding energies of the interfaces were primarily governed by van der Waals interactions and comparable to those of 2D interfaces. Structural characterization using simulations of X-ray absorption spectra revealed the location of graphene energy bands within the band gap of the nanocellulose sheet, with observed depletion/accumulation charge density regions. The tunability of the Dirac cone and charge density at the interface through external agents was demonstrated, indicating its importance for the development of electronic devices based on cellulose platforms.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Chemistry, Multidisciplinary
Zhen Yu Zhang, Guo Ping Wang
Summary: Time-domain study of coherent acoustic phonons in nanomaterials provides dynamic and unparalleled insight into their mechanical and structural features. The acoustic breathing mode of resonant coherent phonons (RCP) in nanoscale RP perovskite films is reported, which shows that RCP oscillation can be used as a novel and non-destructive approach for quantitatively evaluating the decomposition of moisture-exposed RP perovskite. These results reveal the decisive effect of structural geometry on acoustic performances in perovskite nanomaterials.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Electrochemistry
Qingxiao Zhou, Li Wang, Weiwei Ju, Dongtao Su, Juncheng Zhu, Yongliang Yong, Shilin Wu
Summary: The charge storage capacity, quantum capacitance, and atomic structures of transition-metal doped graphene-like/graphene heterostructures were studied using density functional theory (DFT). The impact of transition-metal (TM) doping on the capacitance capacity of different types of heterostructures was also examined. The findings showed that doping was more effective than vacancy defects in enhancing the quantum capacitance of heterostructures. The Sc-doped WSe2/graphene exhibited the highest quantum capacitance (838.24 mu F/cm2), making it a promising material for supercapacitors.
ELECTROCHIMICA ACTA
(2023)
Article
Chemistry, Analytical
Agnieszka Tabaczynska, Anna Dabrowska, Marcin Sloma
Summary: Through applying screen printing pastes containing silver nanoparticles and carbon to textiles, electro-conductive paths were successfully developed. The research results indicated that samples with 3% carbon nanotubes on aramid fiber substrate showed the best adhesion and resistance to washing and bending cycles, indicating potential applications in smart clothing.
Article
Engineering, Electrical & Electronic
Peizong Chen, Jia Yan, Ningning Zhang, Yan Zhan, Qiang Huang, Zuimin Jiang, Zhenyang Zhong
Summary: Semiconductor quantum-dot (QD)-based artificial graphene (AG) exhibits innovative properties and can achieve resonant tunneling effect through voltage scanning. The high conductance phase induced by collective resonant tunneling is the merit of artificial graphene. Phase transition and dual stable phases can be realized by manipulating the holes in quantum dots temporarily.
ACS APPLIED ELECTRONIC MATERIALS
(2022)
Article
Engineering, Electrical & Electronic
Jian Zhang, Liu Qian, Gabriela Borin Barin, Abdalghani H. S. Daaoub, Peipei Chen, Klaus Muellen, Sara Sangtarash, Pascal Ruffieux, Roman Fasel, Hatef Sadeghi, Jin Zhang, Michel Calame, Mickael L. L. Perrin
Summary: Individual graphene nanoribbons synthesized on surfaces can be contacted with carbon nanotubes and used to make multigate devices that exhibit quantum transport effects. Graphene nanoribbons synthesized with atomic precision can be precisely controlled for applications in quantum technology. The study reports the contacting and electrical characterization of on-surface synthesized graphene nanoribbons in a multigate device architecture using single-walled carbon nanotubes as electrodes, which show quantum transport phenomena indicating the contacting of individual nanoribbons.
NATURE ELECTRONICS
(2023)
Article
Materials Science, Multidisciplinary
Seung-Rok Kim, Jiwan Jeon, Yu-Chan Kim, Ji-Woo Park
Summary: In this study, a transparent and skin-attachable electrode (TSE) composed of highly conductive silver nanowires and biocompatible polyurethane composite using surface redissolution by ethanol was developed. The TSE can be fabricated into various patterns by a simple fabrication method and firmly mounted on the skin. It shows stable and conformal contact with the skin, allowing for effective body motion sensing and sensitive electrophysiological signal acquisition.
ADVANCED MATERIALS TECHNOLOGIES
(2023)
Article
Nanoscience & Nanotechnology
Nipun Kumar Gupta, Senthil Kumar Karuppannan, Rupali Reddy Pasula, Ayelet Vilan, Jens Martin, Wentao Xu, Esther Maria May, Andrew R. Pike, Hippolyte P. A. G. Astier, Teddy Salim, Sierin Lim, Christian A. Nijhuis
Summary: Understanding the mechanisms of charge transport in biomolecules is crucial for predictive biomolecular electronic devices. This paper highlights the significant role of graphene interfaces with Fe-storing proteins in charge transport across tunnel junctions, providing insights for studying and manipulating charge transport behavior.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Crystallography
Songmei Wu
Summary: Graphene has unique properties that make it a promising candidate for electrode materials, but challenges remain in the continuous preparation of graphene fibers and strong interlayer interactions. Combining graphene with other materials appears to be a more promising pathway for producing composite fibers, and this article provides a comprehensive overview of graphene-based composite fiber electrodes, their preparation methods, performance optimization, and applications in supercapacitors, while also addressing the remaining challenges in their development.
Article
Multidisciplinary Sciences
J. Cai, E. Griffin, V. H. Guarochico-Moreira, D. Barry, B. Xin, M. Yagmurcukardes, S. Zhang, A. K. Geim, F. M. Peeters, M. Lozada-Hidalgo
Summary: This study observes the strong acceleration of water dissociation reaction in strong electric fields using graphene electrodes, which is in agreement with theoretical predictions. This finding provides valuable insights into interfacial phenomena involving proton transport.
NATURE COMMUNICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Avner Niv, Ping'an Li, Tal Oz, Tilman Konig, Yoram Selzer
Summary: The study reports on electrical transport measurements of ballistic Bi constrictions with top and bottom gate electrodes, where interference between metallic-like surface states and quantized bulk states leads to Fano resonance features in the conductance; the average spacing between bulk states is smaller than their coupling to the leads, causing gradual changes in the scattering phases of the bulk states in response to a change in gate voltage; analysis suggests that surface states are mainly localized at the interface between Bi and the underlying SiO2 layer.
Article
Chemistry, Medicinal
Devon P. Holst, Pascal Friederich, Alan Aspuru-Guzik, Timothy P. Bender
Summary: This study used various computational methods to calibrate and compare the frontier orbital energies and optical gaps of novel boron subphthalocyanine derivatives and related compounds. The results showed that computationally inexpensive semiempirical methods outperformed most density functional theory methods for calibration. By using free software and a standard laptop, researchers can confidently determine the physical properties of these materials before the synthesis and purification process.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Chemistry, Multidisciplinary
Martin Seifrid, Riley J. Hickman, Andres Aguilar-Granda, Cyrille Lavigne, Jenya Vestfrid, Tony C. Wu, Theophile Gaudin, Emily J. Hopkins, Alan Aspuru-Guzik
Summary: Self-driving laboratories, in the form of automated experimentation platforms guided by machine learning algorithms, have emerged as a potential solution to the need for accelerated science. While automated synthesis remains a bottleneck, combining automated and manual synthesis efforts significantly expands the explorable chemical space. Quantifying the cost and considering the capabilities of both automated and manual synthesis can help determine the most efficient synthetic route.
ACS CENTRAL SCIENCE
(2022)
Article
Chemistry, Physical
Phillip W. K. Jensen, Lasse Bjorn Kristensen, Cyrille Lavigne, Alan Aspuru-Guzik
Summary: This study explores the application of molecules and molecular electronics in quantum computing, constructing one-qubit gates using scattering in molecules and two-qubit controlled-phase gates using electron-electron scattering along metallic leads. Furthermore, a class of circuit implementations is proposed, and the framework is demonstrated by illustrating one-qubit gates using the molecular electronic structure of molecular hydrogen as a baseline model.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Correction
Chemistry, Multidisciplinary
Sungwon Kim, Juhwan Noh, Geun Ho Gu, Alan Aspuru-Guzik, Yousung Jung
ACS CENTRAL SCIENCE
(2022)
Review
Chemistry, Multidisciplinary
Martin Seifrid, Robert Pollice, Andres Aguilar-Granda, Zamyla Morgan Chan, Kazuhiro Hotta, Cher Tian Ser, Jenya Vestfrid, Tony C. Wu, Alan Aspuru-Guzik
Summary: Self-driving laboratories have great potential for development, but there are still many challenges to be overcome. Cognitive challenges include optimization with constraints and unexpected outcomes, for which general algorithmic solutions have not yet been developed. A more practical challenge is software control and integration, as few instrument manufacturers design products with self-driving laboratories in mind. Motor function challenges mainly involve handling heterogeneous systems, such as dispensing solids or performing extractions. Therefore, it is important to carefully reconsider the translation of manual experimental protocols for self-driving laboratories.
ACCOUNTS OF CHEMICAL RESEARCH
(2022)
Editorial Material
Chemistry, Physical
John M. Herbert, Martin Head-Gordon, Hrant P. Hratchian, Teresa Head-Gordon, Rommie E. Amaro, Alan Aspuru-Guzik, Roald Hoffmann, Carol A. Parish, Christina M. Payne, Troy Van Voorhis
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Multidisciplinary Sciences
Daniel Flam-Shepherd, Kevin Zhu, Alan Aspuru-Guzik
Summary: This study investigates the application of chemical language models to challenging modeling tasks and demonstrates their ability to learn complex molecular distributions. The results show that language models are powerful generative models capable of accurately generating complex molecular distributions.
NATURE COMMUNICATIONS
(2022)
Review
Nanoscience & Nanotechnology
Zhenpeng Yao, Yanwei Lum, Andrew Johnston, Luis Martin Mejia-Mendoza, Xin Zhou, Yonggang Wen, Alan Aspuru-Guzik, Edward H. Sargent, Zhi Wei Seh
Summary: This Perspective highlights the recent advances in machine learning-driven energy research and proposes a set of key performance indicators to compare the benefits of different ML-accelerated workflows in the field of renewable energy.
NATURE REVIEWS MATERIALS
(2023)
Article
Multidisciplinary Sciences
Pauric Bannigan, Zeqing Bao, Riley J. Hickman, Matteo Aldeghi, Florian Hase, Alan Aspuru-Guzik, Christine Allen
Summary: Long-acting injectables are considered promising for chronic disease treatment, and this study demonstrates the use of machine learning to predict drug release and guide the design of new formulations. The data-driven approach has the potential to reduce development time and cost.
NATURE COMMUNICATIONS
(2023)
Article
Chemistry, Medicinal
Po-Yu Kao, Ya-Chu Yang, Wei-Yin Chiang, Jen-Yueh Hsiao, Yudong Cao, Alex Aliper, Feng Ren, Alan Aspuru-Guzik, Alex Zhavoronkov, Min-Hsiu Hsieh, Yen-Chu Lin
Summary: This article explores the application of hybrid quantum-classical generative adversarial networks (GAN) in drug discovery. By substituting each element of GAN with a variational quantum circuit (VQC), small molecule discovering is achieved. Applying VQC in both the noise generator and discriminator, it can generate small molecules with better physicochemical properties and performance while having fewer trainable parameters. However, the hybrid quantum-classical GANs still face challenges in generating unique and valid molecules compared to their classical counterparts.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Stanley Lo, Martin Seifrid, Theeophile Gaudin, Alaan Aspuru-Guzik
Summary: One of the biggest challenges in polymer property prediction is finding an effective representation that accurately captures the sequence of repeat units. Inspired by data augmentation techniques in computer vision and natural language processing, we explore rearranging the molecular representation iteratively while preserving connectivity to augment polymer data and reveal additional substructural information. We evaluate the impact of this technique on machine learning models trained on three polymer datasets and compare it to common molecular representations. Data augmentation does not significantly improve machine learning property prediction performance compared to non-augmented representations, except in datasets where the target property is primarily influenced by the polymer sequence.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Physical
Philipp Schleich, Joseph Boen, Lukasz Cincio, Abhinav Anand, Jakob S. Kottmann, Sergei Tretiak, Pavel A. Dub, Alan Aspuru-Guzik
Summary: The limited availability of noisy qubits in current quantum computing hardware restricts the investigation of larger, more complex molecules in quantum chemistry calculations. In this study, a classical and near-classical treatment within the framework of quantum circuits is explored. A product ansatz for the parametrized wavefunction is used, along with post-treatment to account for interactions between subsystems. The circuit structure is molecule-dependent and is constructed using simulated annealing and genetic algorithms.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Sergio Pablo-Garcia, Santiago Morandi, Rodrigo A. Vargas-Hernandez, Kjell Jorner, Zarko Ivkovic, Nuria Lopez, Alan Aspuru-Guzik
Summary: GAME-Net is a graph deep learning model trained with small molecules containing a wide set of functional groups for predicting the adsorption energy of closed-shell organic molecules on metal surfaces, avoiding expensive density functional theory simulations. The model yields a mean absolute error of 0.18 eV on the test set and is 6 orders of magnitude faster than density functional theory.
NATURE COMPUTATIONAL SCIENCE
(2023)
Article
Chemistry, Multidisciplinary
Naruki Yoshikawa, Kourosh Darvish, Mohammad Ghazi Vakili, Animesh Garg, Alan Aspuru-Guzik
Summary: Self-driving laboratories require robotic liquid handling and transfer, and we propose a 3D-printed digital pipette design that overcomes the limitations of current robot grippers. It is cost-effective and easy to assemble, and performance evaluation shows comparable precision to commercial devices.
Review
Chemistry, Multidisciplinary
Martin Seifrid, Robert Pollice, Andres Aguilar-Granda, Zamyla Morgan Chan, Kazuhiro Hotta, Cher Tian Ser, Jenya Vestfrid, Tony C. Wu, Alan Aspuru-Guzik
Summary: To address climate change and disease risks, it is crucial to accelerate technological advancements through better integration between hypothesis generation, design, experimentation, and data analysis. Automated laboratories can significantly speed up molecular and materials discovery by generating information-rich data. Open high-quality datasets will enhance the accessibility and reproducibility of science. This paper presents successful efforts in building self-driving laboratories for the development of new materials.
ACCOUNTS OF CHEMICAL RESEARCH
(2022)