Analytical and data strategy for continuous downstream manufacturing

As advances emerge in developing continuous biomanufacturing processes, there is an increased need to deploy PAT tools to characterize, monitor, and control key quality attributes and a criticality to have a data infrastructure to support the immense amount of information being generated. While the desire for these tools exists in traditional batch processing, in a continuous operation, these become a requirement to ensure consistent product quality and enable proactive approaches in maintaining performance. The ultimate goal is to deploy PAT tools to reliably provide real-time information on product and process impurities throughout the entire operation. However, in its current state, there is a reliance on a mixture of inline, at-line, and offline technologies. By identifying the time criticality of CQAs, efforts can be focused on where to prioritize real-time measurements or instead, quicker or more automated testing for a subset of analytics. This work describes the application of this approach in the development of small-scale, compact in-line UV instruments to measure real-time protein concentration and in the integration of an automated sampling system with at-line and offline instrumentation for in-process impurity characterization. Introduction of these PAT tools add to the complexity of the data infrastructure as it introduces requirements for platforms capable of supporting spectral data, chemometric model deployment, spectral instrument management, and time-alignment of discrete data. With the vast amount of information produced in a continuous environment, interface and analysis tools need to be developed so that any end-user can digest data into a format that easily allows them to gain insight into an ongoing batch. This work will highlight the data architecture of the continuous platform, with a focus on software tools selected for aggregation and real-time data visualization. The capabilities of these software packages were demonstrated through a proof-of-concept study using single-pass tangential flow filtration (SPTFF) as a model unit operation, which allowed integration of continuous, spectral, and discrete data. These tools allowed scientists to go from viewing real-time data across multiple, equipment-specific software to one consolidated interface, which in turn reduced time spent in compiling data for analysis and reporting. In addition, advanced capabilities of deploying model predictive control in SPTFF were demonstrated to show the application of a closed loop process control in continuous manufacturing

Calcium as a Mediator for the Electrochemical Synthesis of NH3

NH3 is an important commodity chemical to make fertilizers, pharmaceuticals, textile fibers, ammunition, etc. Haber-Bosch process used to make NH3 has a massive carbon footprint associated with it and it is desired to synthesize NH3 in a sustainable manner. Li-mediated NH3 synthesis is a promising approach to make NH3 at ambient conditions and it has been widely investigated. In this letter we explore other mediators beyond Li such as Ca, Mg, Sr, Y, and V. Our DFT results suggest that Ca, and Mg are promising mediators. Hence, we experimentally investigated Ca as a mediator and the proposed process is referred to as the Ca-mediated NH3 synthesis. An NH3 FE of 15.05 ± 2.50 % was obtained from the Ca-mediated NH3 synthesis at 50 bar. This letter serves as the proof of concept for Ca-mediated NH3 synthesis and this work would motivate further research to improve the performance for Li-free ammonia synthesis

Discovery of Ag as an Active and Selective Catalyst for the Electrochemical Synthesis of Urea from NO3- and CO2 with ~100 % Selectivity at -100 mA/cm2 Urea Current Density

The current method to synthesize urea is highly energy intensive and has a massive carbon footprint. Electrochemical synthesis of urea from NO3- and CO2 is an attractive and sustainable way as renewable energy can be used to synthesize green urea at ambient conditions by utilizing the waste NO3- and CO2 from the air or flue gas. In this work, we conduct a thorough catalytic screening on various metal-based catalysts. ~100 % urea Faradaic efficiency and ~-100 mA/cm2 of urea current density is observed at -1.2 V vs. RHE when Ag GDE is used. FTIR analysis further confirms the formation of urea and the presence of *CO intermediates. The excellent kinetics and selectivity towards urea on Ag are explained by a combination of facile first and second C-N bond formation steps and an endergonic (ΔG > 1.5 eV) formamide (HCONH2) formation step from *CONH2 from our DFT studies

Sequential Hydrolysis of Metal Oxo Clusters Drives Polymorphism in Electrodeposited Zirconium Metal–Organic Frameworks

Over the past few decades, significant developments have been made in the electrodeposition of nanomaterials, mainly due to its streamlined process for producing thin films which are deployed toward various catalysis applications. Concurrently, advances in the electrodeposition of porous materials such as metal–organic frameworks (MOFs) in the past decade have aimed at optimizing their performance for gas storage and catalysis applications. Despite being a relatively recent fabrication method, electrodeposition of MOFs has seen success in only a few instances, which is limited by the formation of unwanted oxide/hydroxide in the metallic component during the linker attachment step. Some studies have shown how to prevent these unwanted metal oxides/hydroxides by controlling solution acidity (or pH) and temperature, resulting in the successful demonstration of the electrochemical synthesis of a subset of MOFs (paddlewheel-based Cu and Zn MOFs) on conductive substrates. However, a comprehensive understanding of the electrochemical synthesis pathway for these porous frameworks is still lacking. We address this gap by presenting, for the first time, a detailed deprotonation mechanism outlining the evolution of Zirconium (Zr) oxo cluster directing the synthesis of porphyrin-based zirconium MOFs. These MOFs are known to exhibit diverse polymorphic topologies that are influenced by modulator type and concentrations. In this work, we show that applied current can influence the polymorphic topologies of Zr MOF by varying local cathodic pH. While synthesizing these MOFs electrochemically, the modulator concentrations are maintained constant to demonstrate the effect of applied current density and solution pKa leading to phase-pure polymorphs of MOF-525 at a higher current density and PCN-222 at a lower current density. The density functional theory calculations reveal that zirconium-oxo clusters undergo sequential hydrolysis, with the pKa of the cluster dictating the extent of deprotonation. The degree of deprotonation, in turn, determines the 12- and 8-connections in MOF-525 and PCN-222, respectively. Finally, the study demonstrates the robustness of the electrochemical protocol by applying it to pyrene- and tricarboxylic-linker-based Zirconium MOFs