The metal-support interaction is one of the most important pillars in heterogeneous catalysis, but developing a fundamental theory has been challenging because intricate interfaces. Based on experimental ‎data, interpretable machine learning, theoretical derivation, and first-principles simulations, we established ‎general metal-oxide interactions grounded ‎metal-metal metal-oxygen interactions. applies to metal nanoparticles atoms oxide supports films supports. We found that for...

Learning microscopic properties of a material from its macroscopic measurables is grand and challenging goal in physical science. Conventional wisdom to first identify structures exploiting characterization tools, such as spectroscopy, then infer interest, often with assistance theory simulations. This indirect approach has limitations due the accumulation errors retrieving spectral signals lack quantitative structure–property relationship. A new pathway directly highly desirable, it would...

The nature of the active sites and their structure sensitivity are keys to rational design efficient catalysts but have been debated for almost one century in heterogeneous catalysis. Though Brønsted–Evans–Polanyi (BEP) relationship along with linear scaling relation has long used study reactivity, explicit geometry, composition properties absent this relationship, a fact that prevents its exploration supported catalysts. In work, based on interpretable multitask symbolic regression...

While the abilities of language models are thoroughly evaluated in areas like general domains and biomedicine, academic chemistry remains less explored. Chemical QA tools also play a crucial role both education research by effectively translating complex chemical information into an understandable format. Addressing this gap, we introduce ScholarChemQA, large-scale dataset constructed from papers. Specifically, questions paper titles with question mark, multi-choice answers reasoned out...

User cooperation can provide spatial transmit diversity gains, enhance coverage and potentially increase capacity. Existing works have focused on two-user cooperative systems with perfect channel state information at the receivers. In this paper, we develop several distributed space-time processing schemes for general N-user systems, which do not require either relays or destination. We prove that full gain be achieved in such systems. Simulations demonstrate these achieve significant performance

We consider a two-person zero-sum mutual information game between one jammer ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">J</i> ) and relay (Rfr) in both nonfading fading scenarios. Assuming that the source xmlns:xlink="http://www.w3.org/1999/xlink">S</i> destination xmlns:xlink="http://www.w3.org/1999/xlink">D</i> are unaware of game, we derive optimal pure or mixed strategies for Rfr depending on link qualities whether players active during...

Over the last few years, machine learning is gradually becoming an essential approach for investigation of heterogeneous catalysis. As one important catalysts, binary alloys have attracted extensive attention screening bifunctional catalysts. Here we present a holistic framework to rapidly predict adsorption energies on surfaces metals and alloys. We evaluate different machine-learning methods understand their applicability problem combine tree-ensemble method with compressed-sensing...

Metal catalysts supported on oxides play a paramount role in numerous industrial reactions. ‎Modulating metal-support interaction is key strategy to boost ‎catalytic productivity and ‎stability; however, the nature of quantification remain major ‎unsolved problems. By ‎leveraging interpretable ‎machine learning, domain knowledge, ‎experimental data available, we discover physical equation ‎applicable ‎to metal nanoparticles adatoms oxides, oxide films metals. Though ‎metal-oxygen dominates...

Metal catalysts supported on oxides play a paramount role in numerous industrial reactions. ‎Modulating metal-support interaction is key strategy to boost ‎catalytic productivity and ‎stability; however, the nature of quantification remain major ‎unsolved problems. By ‎leveraging interpretable ‎machine learning, domain knowledge, ‎experimental data available, we discover physical equation ‎applicable ‎to metal nanoparticles adatoms oxides, oxide films metals. Though ‎metal-oxygen dominates...

Accurate thermochemical properties for chemical species are of vital importance in combustion research. Empirical group additivity approaches extensively used to generate thermochemistry data kinetic models, but the accuracy is limited. In this work, we performed electronic structure calculations determine reliable an extensive set molecules that were taken from a large and well-established model. The developed database consists 1340 contain up 18 5 carbon oxygen atoms, respectively....

In this article, a classification model based on the majority rule sorting (MR-Sort) method is employed to evaluate vulnerability of safety-critical systems with respect malevolent intentional acts.The built basis (limited-size) set data representing (a priori known) examples.The empirical construction introduces source uncertainty into analysis process: quantitative assessment performance (in terms accuracy and confidence in assignments) thus order.Three different approaches are here...

Network coding in wired networks has been shown to achieve considerable throughput gains relative traditional routing networks. For wireless multihop however, the ergodic capacity is unknown. In this context, scaling of with number nodes ( n ) recently received increasing attention. While existing works mainly focus on source-destination pairs, paper deals any-toany links, where each node communicates all other nodes. Complex field network (CFNC) adopted at physical layer allow exchanging...

Sulfur-containing fuels, such as petroleum natural gas, and biofuels, produce SO2, SO3, other highly toxic gases upon combustion, which are harmful to human health the environment, making it essential understand their thermochemical properties. This study used high-level quantum chemistry calculations determine thermodynamic parameters, including entropy, enthalpy, specific heat capacity for an extensive set of sulfur-containing species. The B3LYP/cc-pVTZ level theory was geometry...

Network coding in wired networks has been shown to achieve considerable throughput gains relative traditional routing networks. While the ergodic capacity of wireless multihop is unknown, scaling with number nodes (n) recently received increasing attention. existing works mainly focus on n source-destination pairs, this paper deals any-to-any links, where each node communicates all other nodes. Complex field network (CFNC) adopted at physical layer allow exchanging information simultaneous...

Network coding has been shown to improve throughput, minimize delay and economize the energy requirements in wireless networks. This paper presents an algebraic polyphase approach linear network problem. By modeling nodes as consisting of periodic time varying filters, model incorporates realistic constraints including omni directionality transmissions, half-duplex operation interference effects. A rank criterion is introduced, which together with transmission constraints, constitutes...

Accurate thermochemical properties for chemical species are of vital importance in combustion chemistry research. Group additivity approaches widely used to generate thermochemistry data kinetic models, but this approach has limited accuracy. Following on previous studies by the community, we performed electronic structure calculations obtain reliable a large set molecules taken from well-established model. The developed database consists 1340 that contain up 18 and 5 carbon oxygen atoms,...

Sulfur containing fuels, such as petroleum natural gas, and biofuels, produce SO2, SO3 other highly toxic gases upon combustion--harmful to human health the environment, making it essential understand their thermochemical properties. In this study, thermodynamic parameters, including entropy, enthalpy, specific heat capacity were determined for an extensive set of sulfur species using high level quantum chemistry calculations. Geometry optimization, vibration frequency calculation dihedral...