Crystal structure informed mesoscale deformation model for HCP Cu6Sn5 intermetallic compound

In the electronic packaging and energy storage sectors, the study of Cu6Sn5 intermetallic compound (IMC) is getting more attention. At temperatures above 186 oC, this IMC exists in a hexagonal closed packed (HCP) crystalline structure. Crystal plasticity finite element simulations are performed on Cu6Sn5 IMC by taking the information about its lattice parameters and direction dependent elastic properties. Three types of models corresponding to deformations in basal, prismatic and pyramidal modes are developed. With the same type of loading in the elastic regime and boundary conditions, the results of the computations reveal the differences in displacement magnitudes among the three model types

DCE-MRI for pre-treatment prediction and post-treatment assessment of treatment response in sites of squamous cell carcinoma in the head and neck

Background and Purpose It is important to identify patients with head and neck squamous cell carcinoma (SCC) who fail to respond to chemoradiotherapy so that they can undergo post-treatment salvage surgery while the disease is still operable. This study aimed to determine the diagnostic performance of dynamic contrast enhanced (DCE)-MRI using a pharmacokinetic model for pre-treatment predictive imaging, as well as post-treatment diagnosis, of residual SCC at primary and nodal sites in the head and neck. Material and Methods Forty-nine patients with 83 SCC sites (primary and/or nodal) underwent pre-treatment DCEMRI, and 43 patients underwent post-treatment DCE-MRI, of which 33 SCC sites had a residual mass amenable to analysis. Pre-treatment, post-treatment and %change in the mean Ktrans, kep, ve and AUGC were obtained from SCC sites. Logistic regression was used to correlate DCE parameters at each SCC site with treatment response at the same site, based on clinical outcome at that site at a minimum of two years. Results None of the pre-treatment DCE-MRI parameters showed significant correlations with SCC site failure (SF) (29/83 sites) or site control (SC) (54/83 sites). Post-treatment residual masses with SF (14/33) had significantly higher kep (p = 0.05), higher AUGC (p = 0.02), and lower % reduction in AUGC (p = 0.02), than residual masses with SC (19/33), with the% change in AUGC remaining significant on multivariate analysis. Conclusion Pre-treatment DCE-MRI did not predict which SCC sites would fail treatment, but post-treatment DCE-MRI showed potential for identifying residual masses that had failed treatment

DCE-MRI for pre-treatment prediction and post-treatment assessment of treatment response in sites of squamous cell carcinoma in the head and neck

Background and Purpose It is important to identify patients with head and neck squamous cell carcinoma (SCC) who fail to respond to chemoradiotherapy so that they can undergo post-treatment salvage surgery while the disease is still operable. This study aimed to determine the diagnostic performance of dynamic contrast enhanced (DCE)-MRI using a pharmacokinetic model for pre-treatment predictive imaging, as well as post-treatment diagnosis, of residual SCC at primary and nodal sites in the head and neck. Material and Methods Forty-nine patients with 83 SCC sites (primary and/or nodal) underwent pre-treatment DCEMRI, and 43 patients underwent post-treatment DCE-MRI, of which 33 SCC sites had a residual mass amenable to analysis. Pre-treatment, post-treatment and %change in the mean Ktrans, kep, ve and AUGC were obtained from SCC sites. Logistic regression was used to correlate DCE parameters at each SCC site with treatment response at the same site, based on clinical outcome at that site at a minimum of two years. Results None of the pre-treatment DCE-MRI parameters showed significant correlations with SCC site failure (SF) (29/83 sites) or site control (SC) (54/83 sites). Post-treatment residual masses with SF (14/33) had significantly higher kep (p = 0.05), higher AUGC (p = 0.02), and lower % reduction in AUGC (p = 0.02), than residual masses with SC (19/33), with the% change in AUGC remaining significant on multivariate analysis. Conclusion Pre-treatment DCE-MRI did not predict which SCC sites would fail treatment, but post-treatment DCE-MRI showed potential for identifying residual masses that had failed treatment

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Geometrical effects on growth kinetics of interfacial intermetallic compounds in Sn/Cu joints reflowed with Cu nanoparticles doped flux

© 2018 Elsevier B.V. In this study, Cu nanoparticles prepared by chemical reduction method, were doped into flux (0–2 wt%) and disseminated to the pure Sn solder ball at 250. The enhanced spreading rate due to use of nanoparticles, increased the base diameter (W) and decreased the height (H) of the solder at constant volume. The finite element analysis for Cu concentration, temperature and velocity; in relation to the magnitudes of W and H show that larger W is responsible for enhancement of supersaturation and radial thermal gradient, whereas smaller H is responsible for reduction in flow velocity. The growth kinetics of interfacial Cu 6 Sn 5 film during isothermal reflow is proportional to W 2/3 during isothermal reflow whereas linearly dependent on H during air cooling. As the ripening at isothermal stage and precipitation at cooling stage contribute to the gross growth behavior of Cu 6 Sn 5 intermetallic compounds layer growth, the combined geometrical effect of base diameter and height of the solder specimen renders solder corresponding to flux with 2.0 wt% nanoparticles to have the overall thickest intermetallics.status: publishe

Enhancement of hardness of bulk solder by doping Cu nanoparticles at the interface of Sn/Cu solder joint

© 2019 In this study, Cu NPs prepared by chemical reduction method,were doped into flux at weight proportions (0, 0.2, 0.5, 1 and 2 wt.%) and then reflow soldering was performed for the pure Sn solder (initial diameter = 1400 μm) with Cu substrate at 250 °C for 120 s. The presence of Cu nanoparticles (NPs) in soldering flux was observed to enhance the spreading of solder on Cu substrate. Solder with larger base spread area, characterized with faster diffusion of Cu from substrate attained quicker supersaturation during reflow and larger precipitation of primary Cu 6 Sn 5 intermetallics (IMCs) upon air cooling. The solders containing greater area proportion of primary IMCs are characterized with enhanced effective elastic modulus. Experimentally, the solders prepared with Cu nanoparticles composed flux,were characterized with the increase in Vicker's microhardness. Solder processed with flux containing 2 wt.% Cu nanoparticles possessed Vicker's hardness of 18.6 HV, whereas solder prepared with undoped flux only had hardness of 13.8 HV. Numerical computation of the Cu diffusion and the elasticity have been done using finite element method.status: publishe

In Situ Study the Grooving Effect Induced by Ag Particles on Rapid Growth of Cu₆Sn₅ Grain at Sn-xAg/Cu Soldering Interface during the Heat Preservation Stage

Synchrotron radiation X-ray imaging technique was applied for in situ observation of Cu6Sn5 intermetallic compounds (IMC) growth in Sn/Cu and Sn-3.5Ag/Cu joints under isothermal temperature conditions of 250/300/350 °C and time duration of 1.5 h. The IMC in Sn-Ag solder was characterized by the formation of grooves during the interfacial reaction, and this can be attributed to the Ag content. Kinetically, the growth rate constants for the height of Cu6Sn5 were observed to increase with temperatures and the presence of Ag in solder. As compared to pure Sn solders, the Sn-3.5Ag solders were observed with interfacial IMC of greater height, smaller base width, and lowered aspect ratio

Integration of machine learning with phase field method to model the electromigration induced Cu6_{6}Sn5_{5} IMC growth at anode side Cu/Sn interface

Currently, in the era of big data and 5G communication technology, electromigration has become a serious reliability issue for the miniaturized solder joints used in microelectronic devices. Since the effective charge number (Z*) is considered as the driving force for electromigration, the lack of accurate experimental values for Z* poses severe challenges for the simulation-aided design of electronic materials. In this work, a data-driven framework is developed to predict the Z* values of Cu and Sn species at the anode based LIQUID, Cu$_6$Sn$_5$ intermetallic compound (IMC) and FCC phases for the binary Cu-Sn system undergoing electromigration at 523.15 K. The growth rate constants (k$_{em}$) of the anode IMC at several magnitudes of applied low current density (j = 1 × 10$^6$ to 10 × 10$^6$ A/m$^2$) are extracted from simulations based on a 1D multi-phase field model. A neural network employing Z* and j as input features, whereas utilizing these computed k$_{em}$ data as the expected output is trained. The results of the neural network analysis are optimized with experimental growth rate constants to estimate the effective charge numbers. For a negligible increase in temperature at low j values, effective charge numbers of all phases are found to increase with current density and the increase is much more pronounced for the IMC phase. The predicted values of effective charge numbers Z* are then utilized in a 2D simulation to observe the anode IMC grain growth and electrical resistance changes in the multi-phase system. As the work consists of the aspects of experiments, theory, computation, and machine learning, it can be called the four paradigms approach for the study of electromigration in Pb-free solder. Such a combination of multiple paradigms of materials design can be problem-solving for any future research scenario that is marked by uncertainties regarding the determination of material properties