Downstream Units Research Articles

From agricultural waste to value: Integrated chemo and biocatalytic biorefinery processes to produce 2-furoic acid

The integration of biocatalysis in biorefineries can lead to synergies for raw material valorization. Enzymes must perform efficient and selective reactions when using crude effluents (to avoid costly downstream units). Herein, this is showcased with the synthesis of 2-furoic acid, starting from rice husk (agricultural waste), via a sequential organic-acid catalyzed pretreatment – to afford xylose and cellulose and lignin –, followed by the microwave-assisted acidic xylose dehydration to furfural, in situ extraction in ethyl acetate, and the final biocatalytic selective oxidation of furfural to 2-furoic acid (2-FA). To validate the concept, a xylose-rich hydrolysate (∼ 15 g xylose L−1) obtained from rice husk (RH) was used, achieving a furfural yield of 70 % in a biphasic system (water – ethyl acetate). The obtained furfural extracted in the ethyl acetate was subsequently oxidized to 2-furoic acid via an organic peroxide reaction mediated by Candida antarctica lipase B (CALB), with an overall yield of 90 %, and, with a yield of 41.72 % based on the initial xylose in biomass. Notably, 20 mg/mL CALB could tolerate up to 400 mM of furfural under optimum conditions of 40 °C, 48 h. The recyclability of the biocatalyst was investigated, enabling an efficient reuse of four consecutive cycles.

Process Development and Techno-Economic Analysis for Combined and Separated CO2 Capture-Electrochemical Utilization

Combining CO2 capture and utilization into a single unit operation offers a feasible solution for converting a sustainable feedstock into marketable commodity chemicals, while reducing energy requirements from separated processes. In this research, we developed a process model and performed a techno-economic analysis (TEA) for point-source CO2 capture and electrochemical-based utilization in light olefins production under both separated and integrated scenarios. CO2 containing flue gas from a 500 MW power plant was utilized as a feed while CO2 utilization involved electrochemical reduction reactions to produce light olefins directly from CO2. A meticulous analysis was conducted, probing into the multifaceted impacts of various operating parameters, material properties, and downstream treatment units. Factors such as pressure, temperature, H2O/CO2 molar ratio, catalyst and adsorbent activities, deactivation rate, and heat integration were optimized to achieve 95 % CO2 recovery and > 90 % conversion, and > 85 % ethylene yield. Through a comprehensive TEA, our findings unveiled that the combined process utilizing bifunctional adsorbent/catalyst materials (BFMs) incurs costs of approximately $284/ton CO2, whereas the separated process reported expenses of ∼$516/ton CO2. This study, pivotal in its contributions, evaluated economic feasibility of combined capture-conversion method based on BFMs for CO2 removal and subsequent utilization via a promising advanced process model for sustainable feedstocks conversion to commodity chemicals.

A Transient High-dimensional Geometry Affords Stable Conjunctive Subspaces for Efficient Action Selection.

Flexible action selection requires cognitive control mechanisms capable of mapping the same inputs to different output actions depending on the context. From a neural state-space perspective, this requires a control representation that separates similar input neural states by context. Additionally, for action selection to be robust and time-invariant, information must be stable in time, enabling efficient readout. Here, using EEG decoding methods, we investigate how the geometry and dynamics of control representations constrain flexible action selection in the human brain. Participants performed a context-dependent action selection task. A forced response procedure probed action selection different states in neural trajectories. The result shows that before successful responses, there is a transient expansion of representational dimensionality that separated conjunctive subspaces. Further, the dynamics stabilizes in the same time window, with entry into this stable, high-dimensional state predictive of individual trial performance. These results establish the neural geometry and dynamics the human brain needs for flexible control over behavior.

A multiobjective [formula omitted]-constraint based approach for the robust master surgical schedule under multiple uncertainties

The efficient scheduling of elective surgeries in hospitals is critical for ensuring patient satisfaction, cost-effectiveness, and overall operational efficiency. However, operating theater (OT) managers face complex and competing scheduling problems due to numerous sources of uncertainty and the impact of the proposed schedule on downstream recovery units, such as the intensive care unit (ICU). To address these challenges, this study develops a multiobjective robust planning model for the weekly Master Surgical Schedule (MSS) under multiple uncertainties. The model takes into account patient priority, assignment cost and workload balancing, while also considering the constraints of the OT, surgeon availabilities, downstream resources, and the uncertainty of surgery duration and patients’ length of stay (LOS) in the ICU. To evaluate the robust solutions, a Monte Carlo simulation is used to calculate the risk of constraint violations, and an adapted ϵ-constraint algorithm is used for the four-objective problem to compute the Pareto front and calculate the hypervolume for every degree of uncertainty. This provides a comprehensive decision tool for OT decision makers and allows for the comparison of various scenarios in terms of the number of scheduled patients, canceled patients, and the utilization rate of the OT.

Mechanistic modeling of minute virus of mice surrogate removal by anion exchange chromatography in micro scale

Biopharmaceutical products are often produced in Chinese hamster ovary (CHO) cell cultures that are vulnerable to virus infections. Therefore, it is a regulatory requirement that downstream purification steps for biopharmaceuticals can remove viruses from feedstocks. Anion exchange chromatography (AEX) is one of the downstream unit operations that is most frequently used for this purpose and claimed for its capability to remove viruses. However, the impact of various process parameters on virus removal by AEX is still not fully understood. Mechanistic modeling could be a promising way to approach this gap, as these models require comparatively few experiments for calibration. This makes them a valuable tool to improve understanding of viral clearance, especially since virus spiking studies are costly and time consuming.In this study, we present how the virus clearance of a MVM mock virus particle by Q Sepharose FF resin can be described by mechanistic modeling. A lumped kinetic model was combined with a steric mass action model and calibrated at micro scale using three linear gradient experiments and an incremental step elution gradient. The model was subsequently verified for its capability to predict the effect of different sodium chloride concentrations, as well as residence times, on virus clearance and was in good agreement with the LRVs of the verification runs. Overall, models like this could enhance the mechanistic understanding of viral clearance mechanisms and thereby contribute to the development of more efficient and safer biopharmaceutical downstream processes.

From circular to square‐based section spouted beds: Scale‐up and design overview of a multistage thermal unit

AbstractThis work summarizes the results of several research projects to demonstrate the possibility of scaling‐up spouted beds by assembling a number of square‐based jet units. Cylindrical vessels with a bottom cone and parallelepiped ones with a frustum base do not differ to a large extent in terms of hydrodynamic features. The existing correlations can be used to predict these square‐based spouted beds. Spouted beds can be very reasonably described as well‐mixed reactors. By assembling several units, it is possible to approach a plug flow state for solids residence time distribution (RTD) in continuous processes. Spouting stability is fully reached when the modules do not interfere each other: this goal is obtained by positioning the downstream units at a certain lower level and having the solids move by overflow; placing internal vertical baffles between contiguous units is the solution. Two hydrodynamical models are proposed to describe single and multiple spouted beds; their predictions help in choosing the best geometrical configuration for the assemblage. A possible application of a multiple spouted bed reactor was envisaged for gasifying pelletized textile residues to generate syngas which can be directly used in situ as a co‐fuel. Two units were built: a single 0.2 m side square‐based spouted bed furnace and the consequent dual stage scale‐up apparatus suitable for an auto thermal process. In the bottom stage, four units work independently to run combustion/gasification of low‐quality solid residues, while the upper stage had a cascade of four modules to run pyrolysis/gasification of selected biomass and obtain valuable secondary products.

Process-Induced Crystal Surface Anisotropy and the Impact on the Powder Properties of Odanacatib.

Crystalline active pharmaceutical ingredients with comparable size and surface area can demonstrate surface anisotropy induced during crystallization or downstream unit operations such as milling. To the extent that varying surface properties impacts bulk powder properties, the final drug product performance such as stability, dissolution rates, flowability, and dispersibility can be predicted by understanding surface properties such as surface chemistry, energetics, and wettability. Here, we investigate the surface properties of different batches of Odanacatib prepared through either jet milling or fast precipitation from various solvent systems, all of which meet the particle size specification established to ensure equivalent biopharmaceutical performance. This work highlights the use of orthogonal surface techniques such as Inverse Gas Chromatography (IGC), Brunauer-Emmett-Teller (BET) surface area, contact angle, and X-ray Photoelectron Spectroscopy (XPS) to demonstrate the effect of processing history on particle surface properties to explain differences in bulk powder properties.

Purification of recombinantly produced somatostatin-28 comparing hydrochloric acid and polyethyleneimine as E. coli extraction aids

Peptides are used for diagnostics, therapeutics, and as antimicrobial agents. Most peptides are produced by chemical synthesis, but recombinant production has recently become an attractive alternative due to the advantages of high titers, less toxic waste and correct folding of tertiary structure. Somatostatin-28 is a peptide hormone that regulates the endocrine system, cell proliferation and inhibits the release of numerous secondary hormones in human body. It is composed of 28 amino acids and has one disulfide bond, which makes it to an optimal model peptide for a whole downstream purification process. We produced the peptide in the periplasm of E. coli using the CASPON™ technology, an affinity fusion technology system that enables high soluble expression of recombinant proteins and cleaves the fusion tag with a circularly permuted human caspase-2. Furthermore, purification of the products is straight forward using an established platform process. Two different case studies for downstream purification are presented, starting with either hydrochloric acid or polyethyleneimine as an extraction aid. After release of affinity-tagged somatostatin-28 out of E. coli's periplasm, several purification steps were performed, delivering a pure peptide solution after the final polishing step. The process was monitored by reversed-phase high-performance liquid chromatography as well as mass spectrometry to determine the yield and correct disulfide bond formation. Monitoring of impurities like host cell proteins, DNA and endotoxins after each downstream unit confirmed effective removal for both purification pathways.

Aerodynamic Performance and Coupling Gain Effect of Archimedes Spiral Wind Turbine Array

The Archimedes spiral wind turbine (ASWT), as a novel type of horizontal-axis wind turbine, is well suited for remote islands. To explore the aerodynamic performance and coupling gain effect of ASWT array, a three-dimensional numerical simulation was carried out using the computational fluid dynamics (CFD) method. The influence of arrangement, relative spacing, and rotation configuration on the performance of a double-unit array and triangular array is studied. The results demonstrate that, in parallel arrangements, the double unit achieve higher performance than an isolated ASWT within a specific range of parallel spacing. However, the effect of performance improvement gradually diminishes as the parallel spacing increases. In tandem arrangements, the upstream unit performance remains largely unaffected when tandem spacing exceeds 5 D, while the downstream unit’s performance declines notably with reducing tandem spacing. The downstream unit in reverse rotation configuration accrues more energy than its counterpart operating at the co-rotation configuration. In triangular arrangements, the reverse rotation configuration can achieve better performance due to the meshing effect between the wake of the upstream ASWT and the downstream ASWT. This configuration allows the array system to maintain a higher maximum power output within a smaller spacing. The research results can provide a basis and reference for designing the layout scheme of a multi-unit ASWT power station.

A Cyber-Physical Production System for the Integrated Operation and Monitoring of a Continuous Manufacturing Train for the Production of Monoclonal Antibodies.

The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber-physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs.

Passive Mooring-based Turbine Repositioning Technique for Wake Steering in Floating Offshore Wind Farms

Power loss due to wake effects from upstream wind turbines is an important factor in the design of floating wind farms. These wake disturbances also increase fatigue loads on downstream units. Economic-driven wind farm layout optimization may culminate in non-standard, irregular configurations of offshore wind farms that deviate from conventional engineering practices. Consequently, wind farm developers are inclined towards a more geometrically coherent layout that are sub-optimal. Floating wind turbines horizontal offsets can be used to overcome wake losses. In this study, a novel method suggesting various mooring orientation methods to passively reposition the wind turbines in the farm to maximize annual energy yield. Preliminary parametric optimization demonstrates the effectiveness of the proposed method for standard floating wind farm designs to reduce wake effects by as much as 30% at rated wind speed compared to a baseline case, while preserving the farm’s overall uniformity.

A robust mixed-integer binary programming model for operating theater scheduling to the patient and the surgeon under uncertainty in an open-heart Surgery Department

In hospitals, the surgical ward is both a cost and revenue center. In this ward, hospitals face challenges such as increasing demand, limited resources, and rising costs. Consequently, the decisions made have an implications effect on the hospital's performance. Therefore, in this paper a robust mixed-integer binary programming model is proposed with three objectives of maximizing the efficiency of available resources, minimizing the patients waiting time, and minimizing surgery costs that are formulated utilizing the augmented epsilon constraint approach. This model allocates the operating room to the patient and the surgeon and then obtains the required bed capacity inside the downstream units for stand-alone cardiac hospitals. This model includes different preferences for hospital, surgeon, and patient: waiting time, patient cancellations, tardiness, uncertainties in surgery durations, the patient operation start times, the overtime per working day, time windows, SICU beds, planning horizon, and the idle times of the surgeons, operating theater, and working day. The proposed model is solved using robust optimization to deal with stochastic. The proposed model is formulated on the stochastic programming method proposed by Bertsimas and Sim. In the proposed model, a rolling horizon method is used to reschedule the program after cancellation. The computational results illustrate that the rolling horizon method reduces waiting time and increases throughput. The results illustrate that the benefit obtained from the introduced model has improvements in reducing the surgery costs, and patient waiting time, and increasing the efficiency of available resources. This study has been performed at Shahid Rajaei Heart Hospital in Iran.

A novel multi-operation sequencing formulation for the crude oil scheduling problem with restricted overlapping constraints

The scheduling of crude oil operations holds critical significance in the petrochemical industry due to its profound influence on downstream unit operations and, consequently, overall business profitability. This work presents a novel multi-operation sequencing formulation considering operations with restricted overlapping constraints. This operation-centric model also distinguishes itself by incorporating constraints posed by refinery practice such as downstream product management, multiparcel unloading, brine settling, and changeover detection. A new symmetry-breaking strategy is applied to remove symmetric solutions properly and expedite problem solving while ensuring solution quality. Case studies of various examples are conducted to validate the efficacy of the proposed model. Comparative analyses are performed with the unit-specific event-based formulation, which enables multiple time grids tailored to different units and is widely used in continuous-time modeling. Results further demonstrate the great potential of the presented formulation in generating tighter bounds and accelerating convergence.

A multi-objective planning and scheduling model for elective and emergency cases in the operating room under uncertainty

Hospitals are paramount hubs for delivering healthcare services, with their Operating Rooms (ORs) as a pivotal and financially substantial component. Efficient surgery ward planning is crucial in healthcare institutions, aiming to improve medical service quality while reducing costs. This research delves into the intricacies of integrated OR planning and scheduling, focusing on elective and emergency patients in an uncertain environment. To address these challenges, a mixed integer programming (MIP) framework is developed to minimize inactivity and patient wait times while optimizing high-priority resource allocation. Both upstream and downstream units of the ward, the Pre-operative Holding Unit (PHU), Post Anesthesia Care Unit (PACU), and Intensive Care Unit (ICU) are included. The inherently uncertain aspects of surgery, including surgical duration, Length of Stay (LOS), and the influx of emergency patients, demand an intelligent optimization approach. Consequently, a robust optimization strategy is harnessed to effectively grapple with this pervasive uncertainty. A deterministic model is introduced and improved using an enhanced epsilon constraint method. The culmination of this analytical journey yields a collection of Pareto-optimal solutions. Empirical results, supported by managerial insights, highlight the superiority of the proposed method over the traditional weighting approach.

Evaluation of hydrometallurgical black mass recycling with simulation-based life cycle assessment

PurposeThe recycling of lithium-ion batteries is an emerging field faced with the challenge of recovering more than the most valuable elements from the batteries. While the literature presents many innovative approaches to the problem, an overview of the technical and environmental prospects of hydrometallurgical black mass recycling remains crucial. The goal was to analyze the impacts of a black mass process flowsheet and suggest ways to further reduce the impacts of battery recycling.MethodsThe flowsheet was drafted from the literature by combining both state-of-the-art and experimentally demonstrated unit processes by starting with the leaching system, where reductive leaching is performed using only the copper and iron impurities already present in the black mass. The process targeted copper, manganese, cobalt, nickel, and lithium recovery, and three scenarios for manganese recovery were investigated. The flowsheet was simulated using HSC Sim software, and the mass and energy balances were adapted into internally consistent life cycle inventories. The scope was “gate-to-gate” in Europe and CML methodology was used for impact assessment.Results and discussionAssuming that mechanical pre-treatment carries more environmental benefits than burdens, the results indicated that hydrometallurgical black mass recycling had a tentatively lower environmental footprint compared to virgin raw materials in all impact categories except ozone depletion, the results indicated that hydrometallurgical black mass recycling had a tentatively lower environmental footprint compared to virgin raw materials in all impact categories except ozone depletion. Sulfuric acid and neutralizing chemicals were among the most significant contributors to the impacts, and therefore further analysis was conducted based on an experimental study on low acid leaching with a low (< 0.5 M) initial sulfuric acid concentration instead of the baseline 2 M. This reduced the impacts by approximately 30–40% in all categories by decreasing downstream chemical consumption, and more significantly decreased ozone depletion. The challenges and opportunities for further process improvement were also considered.ConclusionsThe study highlights the importance of process optimization to improve the environmental sustainability of battery chemical production, but also revealed critical research gaps in the experimental literature. Rather than focusing on a single unit process, experimental black mass recycling research should aim at finding solutions that are optimal for the up- and downstream units, such as minimization of aluminum in the black mass and acid consumption.

Numerical study on the effect of smoke emitted from the vents on the roof of a diesel train on the intake of downstream air-conditioning units

Constrained by economic development and geographical features, numerous railway lines remain unelectrified, underscoring the expansive potential of diesel trains. Diesel engine emissions discharged from the roof of trains pose a challenge as some of the smoke infiltrates the cabin through the intake of roof-mounted air-conditioning units (ACUs). This intrusion diminishes the indoor air quality, posing health risks to passengers and potentially jeopardizing their safety. This study employs the shear stress transport k-omega turbulence model to formulate a multiphase flow model for simulating smoke diffusion in diesel trains. Additionally, we conducted an optimization design to minimize smoke entry into the ACUs. This study defined six cases based on variations in the shape and height of the cover and the spacing of the smoke vents. The results show that the effect of the diffusion characteristics decreased with the cover height. With the progression of airflow diffusion, the effect of the smoke vent structure on the concentration diminished farther from the vents. The minimum smoke mass flow rate into the intake occurred with the vent spacing of 2.14 m and without a cover, resulting in a 57.0% decrease compared with the maximum. Thus, a smoke vent spacing of 2.14 m without a cover was deemed to be the optimal configuration. The research results provide certain engineering guidance significance for the design and operation of train-smoke vent structures.

Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks.

Primates can recognize objects despite 3D geometric variations such as in-depth rotations. The computational mechanisms that give rise to such invariances are yet to be fully understood. A curious case of partial invariance occurs in the macaque face-patch AL and in fully connected layers of deep convolutional networks in which neurons respond similarly to mirror-symmetric views (e.g. left and right profiles). Why does this tuning develop? Here, we propose a simple learning-driven explanation for mirror-symmetric viewpoint tuning. We show that mirror-symmetric viewpoint tuning for faces emerges in the fully connected layers of convolutional deep neural networks trained on object recognition tasks, even when the training dataset does not include faces. First, using 3D objects rendered from multiple views as test stimuli, we demonstrate that mirror-symmetric viewpoint tuning in convolutional neural network models is not unique to faces: it emerges for multiple object categories with bilateral symmetry. Second, we show why this invariance emerges in the models. Learning to discriminate among bilaterally symmetric object categories induces reflection-equivariant intermediate representations. AL-like mirror-symmetric tuning is achieved when such equivariant responses are spatially pooled by downstream units with sufficiently large receptive fields. These results explain how mirror-symmetric viewpoint tuning can emerge in neural networks, providing a theory of how they might emerge in the primate brain. Our theory predicts that mirror-symmetric viewpoint tuning can emerge as a consequence of exposure to bilaterally symmetric objects beyond the category of faces, and that it can generalize beyond previously experienced object categories.

GMP implementation of a hybrid continuous manufacturing process for a recombinant non-mAb protein-A case study.

Advances in manufacturing technology coupled with the increased potency of new biotherapeutic modalities have created an external environment where continuous manufacturing (CM) can address a growing need. Amgen has successfully implemented a hybrid CM process for a commercial lifecycle program. In this process, the bioreactor, harvest, capture column, and viral inactivation/depth filtration unit operations were integrated together in an automated, continuous module, while the remaining downstream unit operations took place in stand-alone batch mode. CM operations are particularly suited for so-called "high mix, low volume" manufacturing plants, where a variety of molecules are manufactured in relatively low volumes. The selected molecule fit this mold and was manufactured in a low-capital micro-footprint suite attached to an existing therapeutic production facility. Use of a hybrid process within an already operating facility required less capital and minimized complexity. To enable this hybrid CM process, an established fed-batch process was converted to a perfusion process with continuous harvest. Development efforts included both process changes and the generation of a novel cell line adapted to long-term perfusion. Chromatography resins were updated, and purification processes adapted to handle variable inputs due to the fluctuations in harvest titer from the lengthy production process. A novel automated single-use (SU) viral inactivation (VI) skid was introduced, which entailed the development of a robust pH verification and alarm system, along with procedures for product isolation to allow discard of specific cycles. The CM process demonstrated consistent performance, meaning it met predefined performance criteria (including product quality attributes, or PQAs) when operated within established process parameters and manufactured according to applicable procedures. Using a 75% reduction in scale, it resulted in a five-fold reduction in process media and buffer usage, a fifteen-fold increase in mass per thaw, and an overall process productivity increase of 45-fold (as measured by grams drug substance per liter per day.) The hybrid CM process also enabled increased material demand to be met with no change in cost of goods manufactured or plant capacity, due to the repurposing of existing facility space and the flexible duration of the hybrid CM harvest. Overall, the success of the hybrid CM platform represents an exciting opportunity to reduce costs and increase process efficiency in industry.

Ambient wind conditions impact on energy requirements of an offshore direct air capture plant

This study proposes an off-grid direct air (carbon) capture (DAC) plant installed on the deck of an offshore floating wind turbine. The main objective is to understand detailed flow characteristics and CO2 dispersion around air contactors when placed in close proximity to one another. A solid sorbent DAC design is implemented using a commercially deployed air contactor configuration and sorbent. The sorbent is assumed to undergo a temperature vacuum swing adsorption cycle. Computational fluid dynamics (CFD) is used to determine the local conditions entering each unit based on varying wind speed and angle. Two-dimensional (2D) simulations were used to determine the pressure drop through a detailed air contactor design considering the sorbents APDES-NFC, Tri-PE-MCM, MIL-101(Cr)-PEI-800, and Lewatit VP OC 106. Only APDES-NFC was explored for further analysis in the three dimensional (3D) CFD dispersion model. 3D simulations were used to model flow patterns and CO2 dispersion using passive scalars. A worst case scenario is analyzed for all DAC units in adsorption mode with fans running simultaneously. 2D simulations show an under utilization of contactor length, and quantify pressure loss curves for four common sorbents. One commercially deployed sorbent is considered for further analysis; a pressure drop of 390.62 Pa is experienced for a flow velocity of 0.73 m s−1 through a 1.5m×1.5m×1.5m contactor. Using 3D simulations, fan energy demands are computed based on flow velocities and applied pressure gradients. There is found to be a decrease in overall fan power demand as wind speed increases. High wind speeds can passively drive the adsorption process with fans shut off at certain wind directions. This occurs at an average contactor inlet velocity of 17.5 m s−1, correlating to a hub height (150 m) wind speed of 24 m s−1. Thermal energy demands are computed based on inlet CO2 concentrations entering downstream units. Thermodynamic work for desorption based on an assumed second law efficiency is compared to thermal energy for desorption computed using a simplified isotherm method, taking into account the impacts of humidity on CO2 adsorption. Going from 414.72 ppm to 300 ppm CO2 inlet concentration requires an additional 63.9 kWh (t- CO2)−1 using the 2nd law thermodynamic efficiency method and 25.9 kWh (t- CO2)−1 using the isotherm method. Contactor arrangement, wind angles, and wind speeds have a significant impact on flow patterns experienced, and resulting CO2 dispersion. High wind speeds assist in CO2 dispersion, resulting in higher inlet concentrations to downstream DAC units and decreased thermal energy requirement.

A modular and multi-functional purification strategy that enables a common framework for manufacturing scale integrated and continuous biomanufacturing.

Biopharmaceutical manufacture is transitioning from batch to integrated and continuous biomanufacturing (ICB). The common framework for most ICB, potentially enables a global biomanufacturing ecosystem utilizing modular and multi-function manufacturing equipment. Integrating unit operation hardware and software from multiple suppliers, complex supply chains enabled by multiple customized single-use flow paths, and large volume buffer production/storage make this ICB vision difficult to achieve with commercially available manufacturing equipment. Thus, we developed SymphonX™, a downstream processing skid with advanced buffer management capabilities, a single disposable generic flow path design that provides plug-and-play flexibility across all downstream unit operations and a single interface to reduce operational risk. Designed for multi-product and multi-process cGMP facilities, SymphonX™ can perform stand-alone batch processing or ICB. This study utilized an Apollo™ X CHO-DG44 mAb-expressing cell line in a steady-state perfusion bioreactor, harvesting product continuously with a cell retention device and connected SymphonX™ purification skids. The downstream process used the same chemistry (resins, buffer composition, membrane composition) as our historical batch processing platform, with SymphonX™ in-line conditioning and buffer concentrates. We used surge vessels between unit operations, single-column chromatography (protein A, cation and anion exchange) and two-tank batch virus inactivation. After the first polishing step (cation exchange), we continuously pooled product for 6 days. These 6 day pools were processed in batch-mode from anion exchange to bulk drug substance. This manufacturing scale proof-of-concept ICB produced 0.54 kg/day of drug substance with consistent product quality attributes and demonstrated successful bioburden control for unit-operations undergoing continuous operation.