Design of high-strength refractory complex solid-solution alloys

Nickel-based superalloys and near-equiatomic high-entropy alloys containing Molybdenum are known for higher temperature strength and corrosion resistance. Yet, complex solid-solution alloys offer a huge design space to tune for optimal properties at slightly reduced entropy. For refractory Mo-W-Ta-Ti-Zr, we showcase KKR electronic-structure methods via the coherent-potential approximation to identify alloys over 5-dimensional design space with improved mechanical properties and necessary global (formation enthalpy) and local (short-range order) stability. Deformation is modeled with classical molecular dynamic simulations, validated from our first-principles data. We predict complex solid-solution alloys of improved stability with greatly enhanced modulus of elasticity ($3\times$ at 300 K) over near-equiatomic cases, as validated experimentally, and with higher moduli above 500~K over commercial alloys ($2.3\times$ at 2000 K). We also show that optimal complex solid-solution alloys are not described well by classical potentials due to critical electronic effects.Comment: 9 pages, 6 figure

Allelic diversity of MSP1 and MSP2 repeat loci correlate with levels of malaria endemicity in Senegal and Nigerian populations.

BACKGROUND: Characterizing the genetic diversity of malaria parasite populations in different endemic settings (from low to high) could be helpful in determining the effectiveness of malaria interventions. This study compared Plasmodium falciparum parasite population diversity from two sites with low (pre-elimination) and high transmission in Senegal and Nigeria, respectively. METHODS: Parasite genomic DNA was extracted from 187 dried blood spot collected from confirmed uncomplicated P. falciparum malaria infected patients in Senegal (94) and Nigeria (93). Allelic polymorphism at merozoite surface protein 1 (msp1) and merozoite surface protein- 2 (msp2) genes were assessed by nested PCR. RESULTS: The most frequent msp1 and msp2 allelic families are the K1 and IC3D7 allelotypes in both Senegal and Nigeria. Multiplicity of infection (MOI) of greater that 1 and thus complex infections was common in both study sites in Senegal (Thies:1.51/2.53; Kedougou:2.2/2.0 for msp1/2) than in Nigeria (Gbagada: 1.39/1.96; Oredo: 1.35/1.75]). The heterozygosity of msp1 gene was higher in P. falciparum isolates from Senegal (Thies: 0.62; Kedougou: 0.53) than isolates from Nigeria (Gbagada: 0.55; Oredo: 0.50). In Senegal, K1 alleles was associated with heavy than with moderate parasite density. Meanwhile, equal proportions of K1 were observed in both heavy and moderate infection types in Nigeria. The IC3D7 subtype allele of the msp2 family was the most frequent in heavily parasitaemic individuals from both countries than in the moderately infected participants. CONCLUSION: The unexpectedly low genetic diversity of infections high endemic Nigerian setting compared to the low endemic settings in Senegal is suggestive of possible epidemic outbreak in Nigeria

The Microscopic Mechanism of Lithiation and Delithiation in the Ag/C Buffer Layer for Anode‐Free Solid‐State Batteries

Lithium metal solid-state batteries (LMSSBs) have demonstrated their high energy density and cycling performance at high current densities in an anode-free architecture, featuring a thin Ag/C composite buffer layer (BL) between the current collector (CC) and the solid electrolyte (SE). This study explains the microscopic mechanism of the Ag/C BL by using first-principles atomistic and continuum modeling. It is shown that Ag effectively acts as a homogeneous solid-solution beyond AgLi2.32 and maintains a positive potential even at AgLi25 during lithiation. Key factors underlying the working of the Ag/C BL include lower interfacial resistance at the BL/CC interface than at the BL/SE interface, leading to predominant Li deposition on BL/CC, and substantial Ag–Li volume expansion during lithiation. This, combined with stronger BL/SE adhesion, causes BL/SE separation and Ag–Li extrusion toward the CC side. During delithiation, Ag re-precipitates as nanoparticles uniformly on the CC, with its positive lithiation potential homogenizing Li currents in subsequent cycles. Other metals are less effective due to their relatively large overpotential, premature lithiation termination, and limited volume expansions hindering movement toward the CC. The study aids the BL design, focusing on metal choice and optimization material and microstructural properties, such as the Li-ion conductivity and interfacial resistance

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification

Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation

Design of high-strength refractory complex solid-solution alloys

Nickel-based superalloys and near-equiatomic high-entropy alloys containing molybdenum are known for higher temperature strength and corrosion resistance. Yet, complex solid-solution alloys offer a huge design space to tune for optimal properties at slightly reduced entropy. For refractory Mo-W-Ta-Ti-Zr, we showcase KKR electronic structure methods via the coherent-potential approximation to identify alloys over five-dimensional design space with improved mechanical properties and necessary global (formation enthalpy) and local (short-range order) stability. Deformation is modeled with classical molecular dynamic simulations, validated from our first-principle data. We predict complex solid-solution alloys of improved stability with greatly enhanced modulus of elasticity (3× at 300 K) over near-equiatomic cases, as validated experimentally, and with higher moduli above 500 K over commercial alloys (2.3× at 2000 K). We also show that optimal complex solid-solution alloys are not described well by classical potentials due to critical electronic effects.</p

Effect of solid-electrolyte pellet density on failure of solid-state batteries

Abstract Despite the potentially higher energy density and improved safety of solid-state batteries (SSBs) relative to Li-ion batteries, failure due to Li-filament penetration of the solid electrolyte and subsequent short circuit remains a critical issue. Herein, we show that Li-filament growth is suppressed in solid-electrolyte pellets with a relative density beyond ~95%. Below this threshold value, however, the battery shorts more easily as the density increases due to faster Li-filament growth within the percolating pores in the pellet. The microstructural properties (e.g., pore size, connectivity, porosity, and tortuosity) of $$75\%{{{{{\rm{L}}}}}}{{{{{{\rm{i}}}}}}}_{2}{{{{{\rm{S}}}}}}-25\%{{{{{{\rm{P}}}}}}}_{2}{{{{{{\rm{S}}}}}}}_{5}$$ 75 % L i 2 S − 25 % P 2 S 5 with various relative densities are quantified using focused ion beam–scanning electron microscopy tomography and permeability tests. Furthermore, modeling results provide details on the Li-filament growth inside pores ranging from 0.2 to 2 μm in size. Our findings improve the understanding of the failure modes of SSBs and provide guidelines for the design of dendrite-free SSBs

Effect of solid-electrolyte pellet density on failure of solid-state batteries

Despite the potentially higher energy density and improved safety of solid-state batteries (SSBs) relative to Li-ion batteries, failure due to Li-filament penetration of the solid electrolyte and subsequent short circuit remains a critical issue. Herein, we show that Li-filament growth is suppressed in solid-electrolyte pellets with a relative density beyond ~95%. Below this threshold value, however, the battery shorts more easily as the density increases due to faster Li-filament growth within the percolating pores in the pellet. The microstructural properties (e.g., pore size, connectivity, porosity, and tortuosity) of [Formula: see text] with various relative densities are quantified using focused ion beam-scanning electron microscopy tomography and permeability tests. Furthermore, modeling results provide details on the Li-filament growth inside pores ranging from 0.2 to 2 μm in size. Our findings improve the understanding of the failure modes of SSBs and provide guidelines for the design of dendrite-free SSBs

Spatiotemporal Dynamic of the RTS,S/AS01 Malaria Vaccine Target Antigens in Senegal

International audienceABSTRACT. The RTS,S/AS01 malaria vaccine confers only moderate protection against malaria. Evidence suggests that the effectiveness of the RTS,S/AS01 vaccine depends upon the parasite population genetics, specifically regarding the circumsporozoite protein haplotypes in the population. We investigated Plasmodium falciparum circumsporozoite protein (PfCSP) gene sequences from two endemic sites in 2018 in Senegal. The PfCSP sequences were compared with those retrieved from the Pf3k genome database. In the central repeat region of PfCSP, the distribution of haplotypes differed significantly between the two study sites (Fisher’s exact test, P < 0.001). No 3D7 vaccine strain haplotype was observed in this locus. In the C-terminal region, there was no significant difference in haplotypes distribution between Kedougou and Diourbel (Fischer’s exact test, P = 0.122). The 3D7 haplotype frequency was 8.4% in early samples (2001–2011), but then it contracted in the subsequent years. The extensive plasticity of the P. falciparum genes coding the RTS,S/AS01 vaccine target antigens may influence the immune responses to circulating alleles. Monitoring the genetic diversity baseline and its dynamics over time and space would be instrumental in rationally improving the malaria RTS,S/AS01 vaccine and/or its implementation schedule

Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal

Abstract Background Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. Methods This study examined parasites from 3147 clinical infections sampled between the years 2012–2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. Results Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence ( 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low