Results 141 to 150 of about 2,867,791 (321)

Exciton Binding Energy Modulation in 2D Perovskites: A Phenomenological Keldysh Framework

Advanced Functional Materials, EarlyView.
The intrinsic screening effects are successfully decoupled from structural distortion by rigorously designing a series of 2D perovskites. This enabled us to demonstrate how the dielectric environment modulates the quasiparticle bandgap and exciton binding energy.
Kitae Kim, Namhee Kwon, Sang Woo Park, Wonsik Kim, Seunghwan Kim, Eunki Yoon, Aelim Ha, Donggyu Lee, Young Yong Kim, Jong‐Cheol Lee, Sungho Lee, Junghan Lee, Kyu Hyoung Lee, Yeonjin Yi, Ki‐Ha Hong, Soohyung Park   +15 more
wiley   +1 more source

Almost optimal measurement scheduling of molecular Hamiltonian via finite projective plane

Physical Review Research
We propose an efficient and almost optimal scheme for measuring molecular Hamiltonians in quantum chemistry on quantum computers, which requires 2N^{2} distinct measurements in the leading order with N being the number of molecular orbitals.
Wataru Inoue, Koki Aoyama, Yusuke Teranishi, Keita Kanno, Yuya O. Nakagawa, Kosuke Mitarai   +5 more
doaj   +1 more source

Melt Grafting of Geometry‐Tailored Voltage Stabilizers for High‐Performance Polypropylene Insulation

Advanced Functional Materials, EarlyView.
A scalable one‐step melt grafting strategy is developed to enhance the dielectric properties of isotactic polypropylene by covalently incorporating thermally stable aromatic voltage stabilizers. This solvent‐free approach improves volume resistivity and DC breakdown strength through deep trap formation and charge localization, offering a sustainable ...
Nazirul Mubin bin Normansah, Taehoon Kwon, Hana Kim, Shin‐Ki Hong, Seung Won Lee, Se Hee Lee, Ik‐Su Kwon, Masahiro Kozako, Minhee Kim, Seunggun Yu   +9 more
wiley   +1 more source

Unleashed from constrained optimization: quantum computing for quantum chemistry employing generator coordinate inspired method

npj Quantum Information
Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems.
Muqing Zheng, Bo Peng, Ang Li, Xiu Yang, Karol Kowalski   +4 more
doaj   +1 more source

Selective Charge Injection via Topological van der Waals Contacts for Barrier‐Free p‐Type TMD Transistors

Advanced Functional Materials, EarlyView.
 Topological van der Waals contacts represent a new class of electrodes for 2D semiconductors, enabling precise control of the Schottky barrier height (SBH) and contact resistance (RC) through interlayer distance and orbital hybridization engineering. In Se‐based transition metal dichalcogenides, these contacts achieve an ultralow SBH of 7 meV, RC of 0.
Soheil Ghods, Ho‐Chan Jang, Jun‐Hui Choi, Min Woo Kim, Hyunjin Lee, Tae‐Hoon Kim, Keun Heo, Hyung Jun Kwun, Taehun Lee, Yoon Kyeung Lee, Sang Hoon Lee, Seung‐Il Kim, Woonhyuk Baek, Sukang Bae, Ji‐Yun Moon, Jae‐Hyun Lee   +15 more
wiley   +1 more source

Foundations and applications of the orbital theory in chemistry: A philosophical perspective

Eclética Química
The concept of atomic and molecular orbitals has been a fundamental pillar in modern chemistry, shedding light on the structures and reactivity of chemical compounds.
Ricardo Vivas-Reyes, Daniela Navarro, Luis Eduardo Cortes   +2 more
doaj   +1 more source

Germanane Quantum Dots Promote Metabolic Reprogramming of Immune Cells Toward Regulatory T Cells and Suppress Inflammation In Vitro and In Vivo

Advanced Functional Materials, EarlyView.
Metabolic changes in immune cells direct the phenotype and function of the host immune system. Smart nanomaterials must target metabolic pathways to direct immune cell fate. This study reports the fabrication and first application of germanane quantum dots (GeHQDs) to modulate inflammation in vitro and in vivo.
Abhay Srivastava, Alireza Rafieerad, Weiang Yan, Keshav Narayan Alagarsamy, Qingdong Guan, Leena Regi Saleth, Michel Aliani, Sanjiv Dhingra   +7 more
wiley   +1 more source

Big Data meets Quantum Chemistry Approximations: The $\Delta$-Machine Learning Approach

, 2015
Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry.
Dral, Pavlo O., Ramakrishnan, Raghunathan, Rupp, Matthias, von Lilienfeld, O. Anatole   +3 more
core  

Pore Size Effects of Mesoporous N‐Doped Carbon Nanospheres as Advanced Support Material on the Activity of Molybdenum Sulfide Catalysts for the Hydrogen Evolution Reaction

Advanced Functional Materials, EarlyView.
By tuning the pore size of mesoporous N‐doped carbon (MPNC) nanospheres as support material for molybdenum sulfide, the electrochemical activity of the composite material for the hydrogen evolution reaction can be optimized. An ideal MPNC pore size of 60 nm allows a high number of molybdenum sulfide active sites while maintaining efficient proton and ...
Niklas Ortlieb, Christian Völker, Lars Guggolz, Anna Fischer   +3 more
wiley   +1 more source

Mapping Machine Learning Trends in Chemistry Research using LLM with Multi-Turn Prompting

Sistemasi: Jurnal Sistem Informasi
A review of research in the field of chemistry that incorporates machine learning is essential to identify recent developments and explore its potential applications. Published research articles provide an opportunity to analyze emerging research trends.
Andreo Yudertha, Riski Dwimalida Putri
doaj   +1 more source