It
is challenging to design complex synthetic life-like systems
that can show both autoevolution and fuel-driven transient behaviors.
Here, we report a new class of chemical reaction networks (CRNs) to
construct life-like polymer hydrogels. The CRNs are constituted of
autocatalytic cascade reactions and fuel-driven reaction networks.
The reactions start with only two compounds, that is, thiol of 4-arm-PEG-SH
and thiuram disulfides, and undergo thiol oxidation (k
1), disulfide metathesis (k
2), and thionate hydrolysis-coupling reactions (k
3) subsequently, leading to a four-state autonomous transition
of sol(I) → soft gel → sol(II) → stiff gel. Moreover,
thiuram disulfides can be applied as a fuel to drive the repeated
occurrence of metathesis and hydrolysis-coupling reactions, generating
dissipative stiff gel → sol(II) → stiff gel cycles.
Systematic kinetics studies reveal that the event and lifetime of
every transient state could be delicately tailored-up by varying the
thiuram disulfide concentration, pH of the system, and thiuram structures.
Since the consecutive transient behaviors are precisely predictable,
we envision the strategy’s potential in guiding the molecular
designs of autonomous and adaptive materials for many fields.
Managing the declining yield of non-food crops has opened new strategic challenges amidst global uncertainties. The COVID-19 scenario has increased awareness of natural lifestyle and eco-friendly products, largely dependent on non-food crop material. This strategic shift requires moving beyond traditional farm practices to improve agricultural production efficiency, and developing countries in particular have shown a consistent loss in their self-sufficiency of industrial crops despite being major exporters of non-food crop materials. However, existing studies analyze production efficiencies of non-food crops from general or theoretical aspects often by virtual estimates from breaking down the multiple factors of crop productivity. This study examined multiple factors of crop production to identify “which crop inputs have been inefficiently used overtime” by tracking efficiency changes and various input issues in overall cotton production from practical aspects, i.e., scaling non-constant returns of those multiple factors would allow for the violation of various situations. Accordingly, a stochastic frontier approach was employed to measure the production frontier and efficiency relationship using time-series data of Pakistan’s cotton production from 1971–2018—a specific non-food crop perspective from a top-ranked cotton-producing country that has recently been shifted towards being a non-exporter of cotton due to low yield. The coefficient of area, seed, and labor indicates the positive relationship with cotton production, while fertilizer, irrigation, electricity, and machinery are statistically negative. This implies that policymakers need priority-based strategies for the judicial use of synthetic fertilizers, irrigation, a subsidy policy, and technology adoption, which could significantly improve the efficiencies of cotton productivity from the same land resources. Being adaptable to other developing economies, the analysis would strategically facilitate designing and developing affordable technology-driven solutions and their customized extensions towards sustainable non-food crop production practices and Agri-Resources efficiencies.
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