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Mn-Promoted Surface Modification of MgO in Cu-Based Catalysts Enhances the Low-Temperature Reverse Water-Gas Shift Reaction

2026-03-31T15:00:00Z

Title: Mn-Promoted Surface Modification of MgO in Cu-Based Catalysts Enhances the Low-Temperature Reverse Water-Gas Shift Reaction Author(s): Byun, Hyukjun; Lee, Ji Eun; Park, Jung-Hyeok; Kim, Hyokyung; Kim, Kyung-Min; Jeong, Beomgyun; Kwak, Sang Kyu; Lee, Chang-Ha Abstract: Effective catalysts for converting carbon dioxide into value-added chemicals highly contribute to achieving net-zero emissions. The reverse water-gas shift (rWGS) reaction is essential for CO2-to-CO conversion, yet its efficiency at low temperatures remains limited. Herein, we demonstrate that Mn-doped Cu/MgO catalysts (MgCuXMnY) deliver high rWGS activity at a low temperature. The optimized catalyst (MgCu45Mn5) exhibited rWGS activity of 410.6 mu mol(CO2) g(cat)(-1) s(-1) at 400 degrees C with >99% CO selectivity. Comprehensive experimental and computational analyses revealed the distinct yet cooperative roles of Cu, MgO, and Mn: Cu serving as the active center for H-2 dissociation into H atoms (H+/e(-) pairs), MgO acting as a basic support that hosts surface Mg-OH groups and stabilizes key reaction intermediates along the associative pathway, and Mn functioning as an electronic promoter that enhances the reactivity of oxygen species at the Cu/MgO interface. Specifically, Mn doping into MgO altered lattice parameters and drove Mn valence cycling (Mn2+ <-> Mn3+ <-> Mn4+) via Mn <- O electron transfer (charge compensation), promoting electrophilic oxygen species (O-2(-), O-) formation and accelerating Mg-OH formation. These surface Mg-OH groups intensified the adsorption of CO2 through hydrogen bonding (O-H & centerdot;& centerdot;& centerdot;O-CO2), activating into reaction intermediates. Further, Mn-driven electron back-donation facilitated CO formation, exhibited by effectively weakened C-O and C-H bonds in the reaction intermediates. Ab initio calculations revealed that Mn doping upshifts band gap states, increasing charge transfer and boosting the level of CO2 and H adsorption. Comparative CO2 adsorption studies onto -OH groups indicated stronger CO2 adsorption for the Cu/MgO-Mn system, further validating the boosted CO2 adsorption by Mn-induced hydrogen bonding. This work establishes the optimization of Mn-promoted MgO as an effective strategy for Cu-based catalyst support engineering, providing a blueprint for efficient, low-temperature CO2 conversion.

A machine learning approach to genome-wide association mapping of disease resistance and geographic origin in sorghum

2026-01-31T15:00:00Z

Title: A machine learning approach to genome-wide association mapping of disease resistance and geographic origin in sorghum Author(s): Ahn, Ezekiel; Baek, Insuck; Park, Sunchung; Prom, Louis K.; Lim, Seunghyun; Jang, Jae Hee; Hong, Seok Min; Kim, Moon S.; Meinhardt, Lyndel W.; Magill, Clint Abstract: Sorghum, the fifth most important cereal crop globally, faces persistent threats from fungal diseases that limit productivity and resilience. To investigate the genetic basis of disease resistance and geographic adaptation, we applied a machine learning-enabled genome-wide association study (GWAS) to a panel of 377 genetically diverse sorghum accessions, incorporating nearly 300,000 SNP markers and phenotypic evaluations for resistance to anthracnose, head smut, and downy mildew. While disease resistance phenotypes did not cluster strictly by geographic origin, SNP-based analyses revealed significant genetic differentiation among accessions from different regions, particularly involving a genetically distinct group from Senegal. Bootstrap Forest models highlighted candidate SNPs predictive of geographic origin, most notably on Chromosome 10, near genes encoding transcription factors (e.g., bHLH, EREBP-like) and DUF6598-domain proteins with potential roles in plant defense. For disease resistance, top-ranked SNPs were located near genes implicated in canonical immune pathways, including zinc-binding proteins (anthracnose), NB-ARC and LRR-containing proteins (head smut), and F-box proteins (downy mildew). Although exploratory in nature, these findings suggest that local adaptation to pathogen pressure may have shaped sorghum's genomic landscape. The identified candidate genes and associated SNPs help prioritize targets for marker-assisted selection and follow-up functional validation, contributing to the development of sorghum varieties with enhanced resistance and adaptability.

SERAH-CIM: Sparsity-Aware Effective Row Activation Analog-Digital Hybrid eDRAM CIM With In-Macro Multi-Row-Multi-Task Control

2026-03-31T15:00:00Z

Title: SERAH-CIM: Sparsity-Aware Effective Row Activation Analog-Digital Hybrid eDRAM CIM With In-Macro Multi-Row-Multi-Task Control Author(s): Jeong, Hoichang; Kim, Seungbin; Kim, Dongwook; Jung, Jueun; Lee, Kyuho Jason Abstract: This article presents a sparsity-aware analog-digital hybrid embedded dynamic random access memory (eDRAM) computing-in-memory (CIM) processor for highly energy-efficient deep neural network (DNN) acceleration. Although CIM architectures execute multiplication-and-accumulation (MAC) more efficiently than von Neumann architectures, their practical energy efficiency for DNN acceleration remains limited due to several challenges. First, prior CIMs struggled to exploit massive sparsity because of their highly parallelized structures. Second, CIMs typically adopt computation in either the analog or the digital domain, facing fundamental trade-offs between analog-to-digital converter (ADC) overhead and throughput. Third, system throughput is degraded due to 1) workload imbalance among CIM macros during sparsity-aware computation caused by a random sparsity pattern, which ruins CIM macro utilization and 2)frequent refresh and weight-update operations that have plagued prior eDRAM CIMs. To address these challenges, the proposed eDRAM CIM processor introduces four key features: 1) input activation (IA) grouping convolution, which completely skips zero-weight computations by activating only the effective rows of the CIM macro, increasing the effective computation ratio by 4.59 & times; ; 2) a hybrid-CIM macro integrated with SAR-Flash ADC (SF-ADC) and reversed-MAC near-memory logic (RM-NML) for energy-efficient MAC operations in both the analog and the digital domains, improving macro efficiency by 2.39 & times; ; 3) sparsity-aware proactive scheduling (SPS) to maximize CIM macro utilization, reducing system latency by 10.4%; and 4)in-macro Multi-row-Multi-task (MRMT) control that enables concurrent refresh/update during in-memory computation, resulting in a 22.0% reduction in system latency and a 1.3 & times; increase in system energy efficiency. Fabricated in a 28 nm CMOS process, the proposed processor demonstrates high-energy efficiency across various benchmarks, outperforming previous CIM processors by 1.55 & times; and 10.37 & times; for ResNet-18 and VGGNet-16, respectively.

Chemotaxis-consumption system with Robin boundary conditions coupled to the (Navier-)Stokes equations

2025-12-31T15:00:00Z

Title: Chemotaxis-consumption system with Robin boundary conditions coupled to the (Navier-)Stokes equations Author(s): Kim, Dongkwang; Ahn, Jaewook Abstract: In this paper, we consider the chemotaxis-consumption system on a bounded smooth domain Omega subset of & Ropf;(n), n = 2, 3, with fluid coupling {p(t)+u center dot del p-del center dot(D(p)del p)=del center dot(pS(x,p,c)center dot del c) u.del c-Delta c=pc ut+k(u center dot del)u-Delta u+del pi=p del Phi, del center dot u=0. subject to the boundary conditions v center dot (D(p)del p + pS(x, p, c)del c)|partial derivative Omega = 0, (v center dot del c + c)partial derivative|Omega =gamma , and u|partial derivative Omega= 0. When (n, k) = (2, 1), we establish the global existence and uniform boundedness of classical solutions for all suitably regular initial data, under general structural conditions on the tensor-valued sensitivity S and a strictly positive lower bound on the diffusivity D. In case (n, k) = (3, 0), we show that the same result holds provided that D meets a certain diffusion enhancement condition depending on gamma. Moreover, we construct finite-time blow-up solutions for the radially symmetric, fluid-free system when n = 2, 3, D( ) less than or similar to (1 +xi )(m-1) with 0 < m < 2n and S equivalent to (n & times;n). We prove that, for any prescribed initial mass, blow-up occurs when gamma is sufficiently large.