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        <identifier>oai:figshare.com:article/32149612</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
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        <setSpec>category_12</setSpec>
        <setSpec>category_16</setSpec>
        <setSpec>category_69</setSpec>
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        <setSpec>month_year_05_2026</setSpec>
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      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Interfacial Energetics of C&lt;sub&gt;2&lt;/sub&gt;–C&lt;sub&gt;18&lt;/sub&gt; Aliphatic Moieties on Hydrogenated Si(111) and Si(110) Surfaces:
A DFT Study</dc:title>
          <dc:creator>Sara Marchio (21015907)</dc:creator>
          <dc:creator>Francesco Buonocore (124769)</dc:creator>
          <dc:creator>Simone Giusepponi (21015910)</dc:creator>
          <dc:creator>Massimo Celino (1512820)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Cell Biology</dc:subject>
          <dc:subject>Physiology</dc:subject>
          <dc:subject>Inorganic Chemistry</dc:subject>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Physical Sciences not elsewhere classified</dc:subject>
          <dc:subject>tilted geometry adopted</dc:subject>
          <dc:subject>density functional theory</dc:subject>
          <dc:subject>charge transfer mechanisms</dc:subject>
          <dc:subject>atomic packing density</dc:subject>
          <dc:subject>molecular orbital hybridization</dc:subject>
          <dc:subject>interfacial electronic structure</dc:subject>
          <dc:subject>computational study based</dc:subject>
          <dc:subject>alkynyl chains containing</dc:subject>
          <dc:subject>engineering interface energetics</dc:subject>
          <dc:subject>18 &lt;/ sub</dc:subject>
          <dc:subject>110 ), due</dc:subject>
          <dc:subject>exhibits surface dipoles</dc:subject>
          <dc:subject>h – si</dc:subject>
          <dc:subject>surface dipoles</dc:subject>
          <dc:subject>molecular termination</dc:subject>
          <dc:subject>longer chains</dc:subject>
          <dc:subject>interfacial energetics</dc:subject>
          <dc:subject>dft study</dc:subject>
          <dc:subject>surface states</dc:subject>
          <dc:subject>tunneling transport</dc:subject>
          <dc:subject>tunneling barriers</dc:subject>
          <dc:subject>terminated si</dc:subject>
          <dc:subject>systematically investigate</dc:subject>
          <dc:subject>substrate orientation</dc:subject>
          <dc:subject>rational choice</dc:subject>
          <dc:subject>length dependence</dc:subject>
          <dc:subject>hydrogenated si</dc:subject>
          <dc:subject>dipole formation</dc:subject>
          <dc:subject>crystallographic orientations</dc:subject>
          <dc:subject>aliphatic moieties</dc:subject>
          <dc:description>We present a computational
study based on density functional theory
to systematically investigate how aliphatic moiety functionalization
affects the interfacial electronic structure of H-terminated Si(111)
and Si(110) surfaces. We explore the energetics, dipole formation,
and charge transfer mechanisms for alkyl, alkenyl, and 1-alkynyl chains
containing from 2 to 18 carbon atoms chemisorbed on both crystallographic
orientations. Our analysis reveals that alkenyl moieties exhibit pronounced
chain-length dependence of surface dipoles and tunneling barriers,
whereas alkyl and 1-alkynyl chains show saturation effects for longer
chains. We found that H–Si(111) exhibits surface dipoles up
to 33% larger than H–Si(110), due to differences in atomic
packing density and Si–H bond orientation. The resulting charge
injection barriers for both thermionic and tunneling transport are
quantified and discussed. The tilted geometry adopted by alkenyl moieties
on Si(110) is rationalized through analysis of molecular orbital hybridization
with surface states. These results provide quantitative guidelines
for engineering interface energetics in silicon-based molecular electronic
devices through rational choice of molecular termination and substrate
orientation.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acs.langmuir.6c00727.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Interfacial_Energetics_of_C_sub_2_sub_C_sub_18_sub_Aliphatic_Moieties_on_Hydrogenated_Si_111_and_Si_110_Surfaces_A_DFT_Study/32149612</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
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    <record>
      <header>
        <identifier>oai:figshare.com:article/32149438</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_1</setSpec>
        <setSpec>category_4</setSpec>
        <setSpec>category_12</setSpec>
        <setSpec>category_13</setSpec>
        <setSpec>category_14</setSpec>
        <setSpec>category_16</setSpec>
        <setSpec>category_21</setSpec>
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      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Enhanced Expansion
of Bone Marrow-Derived Mesenchymal
Stem Cells on Collagen-Coated Microcarriers Functionalized with Chimeric
IGF-1–bFGF Proteins</dc:title>
          <dc:creator>Shiina Pasanen (23828470)</dc:creator>
          <dc:creator>Fumika Abe (23828473)</dc:creator>
          <dc:creator>Karina Erda Saninggar (23828476)</dc:creator>
          <dc:creator>Isao Hirata (2467459)</dc:creator>
          <dc:creator>Kotaro Tanimoto (287296)</dc:creator>
          <dc:creator>Koichi Kato (132460)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Cell Biology</dc:subject>
          <dc:subject>Genetics</dc:subject>
          <dc:subject>Molecular Biology</dc:subject>
          <dc:subject>Physiology</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Developmental Biology</dc:subject>
          <dc:subject>Hematology</dc:subject>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>stoichiometric uncertainty inherent</dc:subject>
          <dc:subject>molecule design provides</dc:subject>
          <dc:subject>functional assays demonstrated</dc:subject>
          <dc:subject>fixed molar ratio</dc:subject>
          <dc:subject>efficient functionalization strategies</dc:subject>
          <dc:subject>defined stoichiometry offer</dc:subject>
          <dc:subject>based culture offers</dc:subject>
          <dc:subject>chimeric growth factors</dc:subject>
          <dc:subject>like growth factor</dc:subject>
          <dc:subject>cell transplantation therapies</dc:subject>
          <dc:subject>scalable hmsc expansion</dc:subject>
          <dc:subject>binding chimeric proteins</dc:subject>
          <dc:subject>coated microcarriers functionalized</dc:subject>
          <dc:subject>separate proteins</dc:subject>
          <dc:subject>scalable platform</dc:subject>
          <dc:subject>factor controls</dc:subject>
          <dc:subject>enhanced expansion</dc:subject>
          <dc:subject>coated poly</dc:subject>
          <dc:subject>cell therapy</dc:subject>
          <dc:subject>binding peptide</dc:subject>
          <dc:subject>chimeric igf</dc:subject>
          <dc:subject>vinyl alcohol</dc:subject>
          <dc:subject>unique advantage</dc:subject>
          <dc:subject>significant implications</dc:subject>
          <dc:subject>robust strategy</dc:subject>
          <dc:subject>regenerative medicine</dc:subject>
          <dc:subject>highest effect</dc:subject>
          <dc:subject>fusing insulin</dc:subject>
          <dc:subject>findings demonstrate</dc:subject>
          <dc:subject>bone marrow</dc:subject>
          <dc:description>Human mesenchymal
stem cells (hMSCs) are promising for
cell transplantation
therapies. Nevertheless, their limited yield necessitates large-scale
ex vivo expansion. Microcarrier-based culture offers a scalable platform,
but efficient functionalization strategies are not available. Here,
we engineered collagen-binding chimeric proteins by fusing insulin-like
growth factor-1 (IGF-1) and basic fibroblast growth factor (bFGF)
with an osteopontin-derived collagen-binding peptide and immobilized
them on type I collagen-coated poly(vinyl alcohol) microcarriers.
This single-molecule design provides the unique advantage where the
surface is functionalized with a fixed molar ratio of IGF-1 to bFGF,
avoiding the stoichiometric uncertainty inherent to the coimmobilization
of separate proteins. Structural characterization confirmed proper
folding of the chimeras, and functional assays demonstrated that dual-domain
constructs markedly enhanced hMSC proliferation compared with single-factor
controls, with the IGF-1–bFGF chimera yielding the highest
effect. Expanded cells retained osteogenic differentiation potential.
These findings demonstrate that chimeric growth factors with defined
stoichiometry offer a practical and robust strategy for scalable hMSC
expansion, with significant implications for regenerative medicine
and cell therapy.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acsomega.6c01367.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Enhanced_Expansion_of_Bone_Marrow-Derived_Mesenchymal_Stem_Cells_on_Collagen-Coated_Microcarriers_Functionalized_with_Chimeric_IGF-1_bFGF_Proteins/32149438</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
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    <record>
      <header>
        <identifier>oai:figshare.com:article/32149435</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_4</setSpec>
        <setSpec>category_734</setSpec>
        <setSpec>category_873</setSpec>
        <setSpec>portal_63</setSpec>
        <setSpec>item_type_6</setSpec>
        <setSpec>month_year_05_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>P450 Cyptide
Synthase AscB Catalyzes Fused Cyclophane
at the YxWxH Motif on the Precursor Peptides</dc:title>
          <dc:creator>Jabal
Rahmat Haedar (22915225)</dc:creator>
          <dc:creator>Abujunaid Habib Khan (23828464)</dc:creator>
          <dc:creator>Jemma Gullick (18072672)</dc:creator>
          <dc:creator>Mathias H. Hansen (12371683)</dc:creator>
          <dc:creator>Laura J. Coe (23828467)</dc:creator>
          <dc:creator>James J. De Voss (7490135)</dc:creator>
          <dc:creator>Viktors Romanuks (20654004)</dc:creator>
          <dc:creator>Gints Smits (1916074)</dc:creator>
          <dc:creator>Stefano Donadio (774816)</dc:creator>
          <dc:creator>Max J. Cryle (1814797)</dc:creator>
          <dc:creator>Chin-Soon Phan (3223515)</dc:creator>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>translationally modified peptides</dc:subject>
          <dc:subject>precursor peptides cyptides</dc:subject>
          <dc:subject>p450 cyptide synthases</dc:subject>
          <dc:subject>escherichia coli &lt;/</dc:subject>
          <dc:subject>amycolatopsis sacchari &lt;/</dc:subject>
          <dc:subject>c – n</dc:subject>
          <dc:subject>c –</dc:subject>
          <dc:subject>micromonospora &lt;/</dc:subject>
          <dc:subject>yxwxh motif</dc:subject>
          <dc:subject>unique feature</dc:subject>
          <dc:subject>second cyclophane</dc:subject>
          <dc:subject>ribosomally synthesized</dc:subject>
          <dc:subject>p450s ).</dc:subject>
          <dc:subject>new class</dc:subject>
          <dc:subject>links formed</dc:subject>
          <dc:subject>fused cyclophane</dc:subject>
          <dc:subject>functional studies</dc:subject>
          <dc:subject>first report</dc:subject>
          <dc:subject>dsm 44468</dc:subject>
          <dc:description>Cyptides are a new class of ribosomally synthesized and
post-translationally
modified peptides (RiPPs) with the unique feature of biaryl C–C,
C–N, or C–O cross-links formed by P450 cyptide synthases
(P450s). Through functional studies in &lt;i&gt;Escherichia coli&lt;/i&gt;, we discovered two newly identified P450 enzymes, AscB from &lt;i&gt;Amycolatopsis sacchari&lt;/i&gt; DSM 44468 and MmsB from &lt;i&gt;Micromonospora&lt;/i&gt; sp. HM5-17, that can catalyze the cross-linking between Tyr-C3 and
Trp-N1, as well as the hydroxylation at Trp-C5 in the YxWxH motif.
However, only AscB was able to catalyze the formation of a second
cyclophane between Trp-C4 and His-Nτ, generating a fused cyclophane
in the YxWxH motif. This is the first report of an enzyme that can
catalyze such cross-linking in RiPPs.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acs.orglett.6c01044.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/P450_Cyptide_Synthase_AscB_Catalyzes_Fused_Cyclophane_at_the_YxWxH_Motif_on_the_Precursor_Peptides/32149435</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:figshare.com:article/32149375</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_1</setSpec>
        <setSpec>category_4</setSpec>
        <setSpec>category_19</setSpec>
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      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Carrier-Regulation
in Organic Cathodes for Photochargeable
Batteries Boosting High Photoresponse and Long Durability</dc:title>
          <dc:creator>Chang Tong (369266)</dc:creator>
          <dc:creator>Huicong Li (5718995)</dc:creator>
          <dc:creator>Zhuocheng Tian (18406101)</dc:creator>
          <dc:creator>Zhicheng Zhang (490080)</dc:creator>
          <dc:creator>Lianmeng Cui (13850074)</dc:creator>
          <dc:creator>Dongxue Wang (621725)</dc:creator>
          <dc:creator>Liang Zhou (85586)</dc:creator>
          <dc:creator>Jianlong Xia (1563811)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Pharmacology</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Information Systems not elsewhere classified</dc:subject>
          <dc:subject>yet face challenges</dc:subject>
          <dc:subject>sustainable energy conversion</dc:subject>
          <dc:subject>smooth electron pathway</dc:subject>
          <dc:subject>mismatched charge kinetics</dc:subject>
          <dc:subject>enhance charge utilization</dc:subject>
          <dc:subject>enables high photostability</dc:subject>
          <dc:subject>efficient charge separation</dc:subject>
          <dc:subject>cs ), along</dc:subject>
          <dc:subject>chemical conversion process</dc:subject>
          <dc:subject>510 mv cm</dc:subject>
          <dc:subject>4 μa cm</dc:subject>
          <dc:subject>study introduces carrier</dc:subject>
          <dc:subject>acceptor ” structure</dc:subject>
          <dc:subject>transformative demonstration</dc:subject>
          <dc:subject>sustaining cyclability</dc:subject>
          <dc:subject>show promise</dc:subject>
          <dc:subject>primarily caused</dc:subject>
          <dc:subject>photocathode co</dc:subject>
          <dc:subject>organic cathodes</dc:subject>
          <dc:subject>multistep solar</dc:subject>
          <dc:subject>multiregulation strategy</dc:subject>
          <dc:subject>limited cyclicity</dc:subject>
          <dc:subject>inefficient photocharging</dc:subject>
          <dc:subject>electrochemical processes</dc:subject>
          <dc:subject>efficiently shuttled</dc:subject>
          <dc:subject>coregulation strategy</dc:subject>
          <dc:subject>ca &lt;/</dc:subject>
          <dc:subject>800 times</dc:subject>
          <dc:subject>8 %.</dc:subject>
          <dc:description>Photochargeable batteries (PCBs) show promise for sustainable
energy
conversion and storage, yet face challenges in inefficient photocharging
and limited cyclicity, primarily caused by mismatched charge kinetics
in the multistep solar-to-electric-to-chemical conversion process.
To address this, we introduce a coregulation strategy that integrates
a photocathode featuring electron “Acceptor-Acceptor-Acceptor”
structure for efficient charge separation (CS), along with ammonium-based
carriers exhibiting rapid transfer dynamics to enhance charge utilization
in PCBs. When illuminated, the smooth electron pathway in photocathode
yields persistent photogenerated charges that are efficiently shuttled
by NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt; carriers to engage in electrochemical
processes. Consequently, this multiregulation strategy with orchestrating
carriers and photocathodes produces high photocurrent of 31.4 μA
cm&lt;sup&gt;–2&lt;/sup&gt; and photovoltage of 510 mV cm&lt;sup&gt;–2&lt;/sup&gt;, thereby enhancing reversible capacity of &lt;i&gt;ca&lt;/i&gt;. 29.8%.
Moreover, low-corrosive NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt; enables high photostability
of PCB, sustaining cyclability over 800 times. This study introduces
carrier/photocathode co-regulation as a transformative demonstration
for advancing PCBs, complementing existing photoelectrode optimization
frameworks.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acs.nanolett.6c00492.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Carrier-Regulation_in_Organic_Cathodes_for_Photochargeable_Batteries_Boosting_High_Photoresponse_and_Long_Durability/32149375</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:figshare.com:article/32149372</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_4</setSpec>
        <setSpec>category_21</setSpec>
        <setSpec>category_146</setSpec>
        <setSpec>category_272</setSpec>
        <setSpec>category_734</setSpec>
        <setSpec>category_873</setSpec>
        <setSpec>category_931</setSpec>
        <setSpec>portal_63</setSpec>
        <setSpec>item_type_3</setSpec>
        <setSpec>month_year_05_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Enabling Direct Engineering of Porous Biochar with
Machine Learning Using Only Simple Feedstock Information for Efficient
Adsorption of CO&lt;sub&gt;2&lt;/sub&gt;</dc:title>
          <dc:creator>Chengkai Cao (23828401)</dc:creator>
          <dc:creator>Zejian Ai (23828404)</dc:creator>
          <dc:creator>Weijin Zhang (5431907)</dc:creator>
          <dc:creator>Jianan Li (290570)</dc:creator>
          <dc:creator>Hao Zhan (6853280)</dc:creator>
          <dc:creator>Lijian Leng (3684337)</dc:creator>
          <dc:creator>Hailong Li (216327)</dc:creator>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Information Systems not elsewhere classified</dc:subject>
          <dc:subject>unified predictive framework</dc:subject>
          <dc:subject>mainly focused either</dc:subject>
          <dc:subject>machine learning using</dc:subject>
          <dc:subject>gradient boosting regression</dc:subject>
          <dc:subject>efficiently screen feedstocks</dc:subject>
          <dc:subject>coupled machine learning</dc:subject>
          <dc:subject>enabling direct engineering</dc:subject>
          <dc:subject>simple feedstock information</dc:subject>
          <dc:subject>2 &lt;/ sup</dc:subject>
          <dc:subject>correlating biochar properties</dc:subject>
          <dc:subject>e &lt;/ sub</dc:subject>
          <dc:subject>2 &lt;/ sub</dc:subject>
          <dc:subject>predicted maximum co</dc:subject>
          <dc:subject>using biomass composition</dc:subject>
          <dc:subject>engineering biochar porosity</dc:subject>
          <dc:subject>biomass composition</dc:subject>
          <dc:subject>engineering biochar</dc:subject>
          <dc:subject>r &lt;/</dc:subject>
          <dc:subject>promising feedstock</dc:subject>
          <dc:subject>&gt;&lt; sup</dc:subject>
          <dc:subject>biomass pyrolysis</dc:subject>
          <dc:subject>porous biochar</dc:subject>
          <dc:subject>performance biochar</dc:subject>
          <dc:subject>engineer biochar</dc:subject>
          <dc:subject>work provides</dc:subject>
          <dc:subject>wide applications</dc:subject>
          <dc:subject>validations based</dc:subject>
          <dc:subject>sustainable co</dc:subject>
          <dc:subject>related areas</dc:subject>
          <dc:subject>pyrolysis parameters</dc:subject>
          <dc:subject>input variables</dc:subject>
          <dc:subject>high co</dc:subject>
          <dc:subject>existing studies</dc:subject>
          <dc:subject>efficient strategy</dc:subject>
          <dc:subject>designing high</dc:subject>
          <dc:subject>chemical descriptors</dc:subject>
          <dc:subject>capture technologies</dc:subject>
          <dc:subject>bean straw</dc:subject>
          <dc:subject>62 mmol</dc:subject>
          <dc:description>Biochar, derived from biomass pyrolysis
and activation, is a versatile
porous carbon material with wide applications in CO&lt;sub&gt;2&lt;/sub&gt; adsorption.
However, existing studies have mainly focused either on engineering
biochar porosity or on correlating biochar properties with CO&lt;sub&gt;2&lt;/sub&gt; adsorption capacity (CO&lt;sub&gt;2&lt;/sub&gt;Ad-q&lt;sub&gt;e&lt;/sub&gt;), without
integrating both physical and chemical descriptors into a unified
predictive framework. To address this gap, a coupled machine learning
(ML) approach was developed to predict and engineer biochar for CO&lt;sub&gt;2&lt;/sub&gt; adsorption. A gradient boosting regression (GBR) model was
constructed by using biomass composition, pyrolysis parameters, activation
conditions, and adsorption conditions as input variables, which achieved
excellent predictive performance with an &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; of 0.99 and an RMSE of 0.15. Moreover, the model requires only biomass
composition, without any requirements to produce and characterize
the biochar, to efficiently screen feedstocks and identify optimal
production conditions for engineering biochar with high CO&lt;sub&gt;2&lt;/sub&gt;Ad-q&lt;sub&gt;e&lt;/sub&gt;. Validations based on an extra unseen data set further
confirmed the robustness of the model. After screening several hundred
biomass samples reported in the literature, bean straw was identified
as the most promising feedstock, with a predicted maximum CO&lt;sub&gt;2&lt;/sub&gt;Ad-q&lt;sub&gt;e&lt;/sub&gt; of 6.62 mmol/g. This work provides a data-driven
and efficient strategy for designing high-performance biochar, contributing
to the advancement of sustainable CO&lt;sub&gt;2&lt;/sub&gt; capture technologies
and related areas.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.1021/acssuschemeng.5c12782.s002</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Enabling_Direct_Engineering_of_Porous_Biochar_with_Machine_Learning_Using_Only_Simple_Feedstock_Information_for_Efficient_Adsorption_of_CO_sub_2_sub_/32149372</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:figshare.com:article/32149369</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_4</setSpec>
        <setSpec>category_21</setSpec>
        <setSpec>category_146</setSpec>
        <setSpec>category_272</setSpec>
        <setSpec>category_734</setSpec>
        <setSpec>category_873</setSpec>
        <setSpec>category_931</setSpec>
        <setSpec>portal_63</setSpec>
        <setSpec>item_type_6</setSpec>
        <setSpec>month_year_05_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Enabling Direct Engineering of Porous Biochar with
Machine Learning Using Only Simple Feedstock Information for Efficient
Adsorption of CO&lt;sub&gt;2&lt;/sub&gt;</dc:title>
          <dc:creator>Chengkai Cao (23828401)</dc:creator>
          <dc:creator>Zejian Ai (23828404)</dc:creator>
          <dc:creator>Weijin Zhang (5431907)</dc:creator>
          <dc:creator>Jianan Li (290570)</dc:creator>
          <dc:creator>Hao Zhan (6853280)</dc:creator>
          <dc:creator>Lijian Leng (3684337)</dc:creator>
          <dc:creator>Hailong Li (216327)</dc:creator>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Information Systems not elsewhere classified</dc:subject>
          <dc:subject>unified predictive framework</dc:subject>
          <dc:subject>mainly focused either</dc:subject>
          <dc:subject>machine learning using</dc:subject>
          <dc:subject>gradient boosting regression</dc:subject>
          <dc:subject>efficiently screen feedstocks</dc:subject>
          <dc:subject>coupled machine learning</dc:subject>
          <dc:subject>enabling direct engineering</dc:subject>
          <dc:subject>simple feedstock information</dc:subject>
          <dc:subject>2 &lt;/ sup</dc:subject>
          <dc:subject>correlating biochar properties</dc:subject>
          <dc:subject>e &lt;/ sub</dc:subject>
          <dc:subject>2 &lt;/ sub</dc:subject>
          <dc:subject>predicted maximum co</dc:subject>
          <dc:subject>using biomass composition</dc:subject>
          <dc:subject>engineering biochar porosity</dc:subject>
          <dc:subject>biomass composition</dc:subject>
          <dc:subject>engineering biochar</dc:subject>
          <dc:subject>r &lt;/</dc:subject>
          <dc:subject>promising feedstock</dc:subject>
          <dc:subject>&gt;&lt; sup</dc:subject>
          <dc:subject>biomass pyrolysis</dc:subject>
          <dc:subject>porous biochar</dc:subject>
          <dc:subject>performance biochar</dc:subject>
          <dc:subject>engineer biochar</dc:subject>
          <dc:subject>work provides</dc:subject>
          <dc:subject>wide applications</dc:subject>
          <dc:subject>validations based</dc:subject>
          <dc:subject>sustainable co</dc:subject>
          <dc:subject>related areas</dc:subject>
          <dc:subject>pyrolysis parameters</dc:subject>
          <dc:subject>input variables</dc:subject>
          <dc:subject>high co</dc:subject>
          <dc:subject>existing studies</dc:subject>
          <dc:subject>efficient strategy</dc:subject>
          <dc:subject>designing high</dc:subject>
          <dc:subject>chemical descriptors</dc:subject>
          <dc:subject>capture technologies</dc:subject>
          <dc:subject>bean straw</dc:subject>
          <dc:subject>62 mmol</dc:subject>
          <dc:description>Biochar, derived from biomass pyrolysis
and activation, is a versatile
porous carbon material with wide applications in CO&lt;sub&gt;2&lt;/sub&gt; adsorption.
However, existing studies have mainly focused either on engineering
biochar porosity or on correlating biochar properties with CO&lt;sub&gt;2&lt;/sub&gt; adsorption capacity (CO&lt;sub&gt;2&lt;/sub&gt;Ad-q&lt;sub&gt;e&lt;/sub&gt;), without
integrating both physical and chemical descriptors into a unified
predictive framework. To address this gap, a coupled machine learning
(ML) approach was developed to predict and engineer biochar for CO&lt;sub&gt;2&lt;/sub&gt; adsorption. A gradient boosting regression (GBR) model was
constructed by using biomass composition, pyrolysis parameters, activation
conditions, and adsorption conditions as input variables, which achieved
excellent predictive performance with an &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; of 0.99 and an RMSE of 0.15. Moreover, the model requires only biomass
composition, without any requirements to produce and characterize
the biochar, to efficiently screen feedstocks and identify optimal
production conditions for engineering biochar with high CO&lt;sub&gt;2&lt;/sub&gt;Ad-q&lt;sub&gt;e&lt;/sub&gt;. Validations based on an extra unseen data set further
confirmed the robustness of the model. After screening several hundred
biomass samples reported in the literature, bean straw was identified
as the most promising feedstock, with a predicted maximum CO&lt;sub&gt;2&lt;/sub&gt;Ad-q&lt;sub&gt;e&lt;/sub&gt; of 6.62 mmol/g. This work provides a data-driven
and efficient strategy for designing high-performance biochar, contributing
to the advancement of sustainable CO&lt;sub&gt;2&lt;/sub&gt; capture technologies
and related areas.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acssuschemeng.5c12782.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Enabling_Direct_Engineering_of_Porous_Biochar_with_Machine_Learning_Using_Only_Simple_Feedstock_Information_for_Efficient_Adsorption_of_CO_sub_2_sub_/32149369</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:figshare.com:article/32149363</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_4</setSpec>
        <setSpec>category_16</setSpec>
        <setSpec>category_21</setSpec>
        <setSpec>category_39</setSpec>
        <setSpec>category_146</setSpec>
        <setSpec>category_734</setSpec>
        <setSpec>category_873</setSpec>
        <setSpec>category_915</setSpec>
        <setSpec>portal_63</setSpec>
        <setSpec>item_type_6</setSpec>
        <setSpec>month_year_05_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>3,5-Dinitrobenzoic
Acid Enables Stable and Efficient
HTL-Free MAPbI&lt;sub&gt;3&lt;/sub&gt; Perovskite Solar Cells</dc:title>
          <dc:creator>Saravanan Subramani (20539965)</dc:creator>
          <dc:creator>Govindaraj Rajamanickam (12440627)</dc:creator>
          <dc:creator>Chauhan Anil Kumar (23828398)</dc:creator>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Physiology</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Ecology</dc:subject>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Physical Sciences not elsewhere classified</dc:subject>
          <dc:subject>uncoordinated lead ions</dc:subject>
          <dc:subject>present work provides</dc:subject>
          <dc:subject>minimizing nonradiative recombination</dc:subject>
          <dc:subject>enhancing charge transportation</dc:subject>
          <dc:subject>30 ° c</dc:subject>
          <dc:subject>severe surface defects</dc:subject>
          <dc:subject>carboxyl (− cooh</dc:subject>
          <dc:subject>perovskite solar cells</dc:subject>
          <dc:subject>power conversion efficiency</dc:subject>
          <dc:subject>benzene ring limit</dc:subject>
          <dc:subject>highly efficient cpscs</dc:subject>
          <dc:subject>dnbz additive containing</dc:subject>
          <dc:subject>3 &lt;/ sub</dc:subject>
          <dc:subject>benzene ring</dc:subject>
          <dc:subject>reduce defects</dc:subject>
          <dc:subject>nitro (−</dc:subject>
          <dc:subject>efficient htl</dc:subject>
          <dc:subject>perovskite ’</dc:subject>
          <dc:subject>perovskite solution</dc:subject>
          <dc:subject>perovskite films</dc:subject>
          <dc:subject>term durability</dc:subject>
          <dc:subject>straightforward method</dc:subject>
          <dc:subject>significant improvement</dc:subject>
          <dc:subject>retain 87</dc:subject>
          <dc:subject>investigations reveal</dc:subject>
          <dc:subject>hydrophobic properties</dc:subject>
          <dc:subject>gained interest</dc:subject>
          <dc:subject>free mapbi</dc:subject>
          <dc:subject>fabricate inexpensive</dc:subject>
          <dc:subject>dinitrobenzoic acid</dc:subject>
          <dc:subject>device efficiency</dc:subject>
          <dc:subject>cpscs treated</dc:subject>
          <dc:subject>based htl</dc:subject>
          <dc:subject>22 days</dc:subject>
          <dc:subject>11 %.</dc:subject>
          <dc:subject>1 mg</dc:subject>
          <dc:description>Hybrid perovskite solar cells have gained interest for
their high
solar energy efficiency and low-temperature solution processing properties.
However, severe surface defects at perovskite grain boundaries still
hinder improvements in device efficiency and performance. Here, we
effectively introduced organic compound 3,5-dinitrobenzoic acid (DNBZ)
as an additive to the perovskite solution. The DNBZ additive containing
a benzene ring and carboxyl (−COOH) and nitro (−NO&lt;sub&gt;2&lt;/sub&gt;) functional groups effectively reacts with uncoordinated
lead ions (Pb&lt;sup&gt;2+&lt;/sup&gt;) to reduce defects/traps in perovskite
films, improving their film quality, minimizing nonradiative recombination,
and enhancing charge transportation and the efficiency of CPSCs. Furthermore,
the hydrophobic properties of the benzene ring limit the perovskite’s
interaction with water, improving the moisture stability of CPSCs.
Interestingly, 1 mg-DNBZ added carbon counter electrode-based HTL-free
MAPbI&lt;sub&gt;3&lt;/sub&gt; perovskite solar cells (CPSCs) have a power conversion
efficiency (PCE) enhanced from 8.36 to 10.11%. Furthermore, after
being kept for 22 days, the PCE of CPSCs treated with 1 mg-DNBZ can
retain 87% of its initial PCE (under the condition of 30 °C and
RH = 50 ± 5%), indicating a significant improvement in long-term
durability. Our investigations reveal that the DNBZ additive strategy
improves the stability, efficiency, performance, and quality of perovskite
films. The present work provides a straightforward method to fabricate
inexpensive and highly efficient CPSCs.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acs.langmuir.6c00500.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/3_5-Dinitrobenzoic_Acid_Enables_Stable_and_Efficient_HTL-Free_MAPbI_sub_3_sub_Perovskite_Solar_Cells/32149363</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:figshare.com:article/32149360</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_1</setSpec>
        <setSpec>category_4</setSpec>
        <setSpec>category_8</setSpec>
        <setSpec>category_12</setSpec>
        <setSpec>category_16</setSpec>
        <setSpec>category_61</setSpec>
        <setSpec>category_132</setSpec>
        <setSpec>category_134</setSpec>
        <setSpec>category_135</setSpec>
        <setSpec>category_873</setSpec>
        <setSpec>category_915</setSpec>
        <setSpec>portal_63</setSpec>
        <setSpec>item_type_6</setSpec>
        <setSpec>month_year_05_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Synthesis of Polymers Consisting of Urea and 3,5-Hydantoin
Moieties in an Alternating Manner Based on a Phosgene-Free Method
and Their Thermal Properties</dc:title>
          <dc:creator>Tomoya Hayashi (5353106)</dc:creator>
          <dc:creator>Haruto Minami (23828395)</dc:creator>
          <dc:creator>Yuji Kosugi (2426227)</dc:creator>
          <dc:creator>Yasuyuki Mori (3728023)</dc:creator>
          <dc:creator>Takehiro Kawauchi (1476997)</dc:creator>
          <dc:creator>Yoshio Furusho (2050327)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Microbiology</dc:subject>
          <dc:subject>Cell Biology</dc:subject>
          <dc:subject>Physiology</dc:subject>
          <dc:subject>Developmental Biology</dc:subject>
          <dc:subject>Infectious Diseases</dc:subject>
          <dc:subject>Virology</dc:subject>
          <dc:subject>Computational  Biology</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Physical Sciences not elsewhere classified</dc:subject>
          <dc:subject>unit model compound</dc:subject>
          <dc:subject>e ., polycondensation</dc:subject>
          <dc:subject>dsc analyses showed</dc:subject>
          <dc:subject>alternating manner based</dc:subject>
          <dc:subject>hydantoin moiety proceeded</dc:subject>
          <dc:subject>alternating manner</dc:subject>
          <dc:subject>ureidoacetate moiety</dc:subject>
          <dc:subject>utilizing dbu</dc:subject>
          <dc:subject>thermomechanical properties</dc:subject>
          <dc:subject>thermal properties</dc:subject>
          <dc:subject>synthetic method</dc:subject>
          <dc:subject>results obtained</dc:subject>
          <dc:subject>reaction using</dc:subject>
          <dc:subject>n &lt;/</dc:subject>
          <dc:subject>main chain</dc:subject>
          <dc:subject>ir spectroscopies</dc:subject>
          <dc:subject>investigated briefly</dc:subject>
          <dc:subject>hydantoin moieties</dc:subject>
          <dc:subject>free method</dc:subject>
          <dc:subject>first time</dc:subject>
          <dc:subject>catalyzed cyclization</dc:subject>
          <dc:subject>&gt;′- bis</dc:subject>
          <dc:description>We
developed a synthetic method for polymers consisting of urea
and 3,5-hydantoin moieties in an alternating manner by utilizing DBU-catalyzed
cyclization of the α-ureidoacetate moiety of polyureas, which
were prepared using Endo’s phosgene-free method, i.e., polycondensation
of &lt;i&gt;N&lt;/i&gt;,&lt;i&gt;N&lt;/i&gt;′-bis(phenoxycarbonyl)
derivatives of ornithine or lysine with diamines. Transformation of
the α-ureidoacetate moiety of the polyureas into the 3,5-hydantoin
moiety proceeded in DMSO to give the poly(urea-hydantoin)s quantitatively
without side reactions. Their structures were confirmed by NMR and
FT-IR spectroscopies in combination with results obtained from the
reaction using a unit model compound having α-ureidoacetate
moiety. Thus, we have achieved the synthesis of polymers with 3,5-hydantoin
in the main chain for the first time, whereas polymers bearing 1,3-hydantoin
are well-known. Furthermore, TGA and DSC analyses showed that the
poly(urea-hydantoin)s had much higher thermal stability than the corresponding
polyureas because of the rigidity of the 3,5-hydantoin moieties. Their
mechanical and thermomechanical properties were investigated briefly.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acs.macromol.5c03500.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Synthesis_of_Polymers_Consisting_of_Urea_and_3_5-Hydantoin_Moieties_in_an_Alternating_Manner_Based_on_a_Phosgene-Free_Method_and_Their_Thermal_Properties/32149360</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:figshare.com:article/32149357</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
        <setSpec>category_8</setSpec>
        <setSpec>category_24</setSpec>
        <setSpec>category_39</setSpec>
        <setSpec>category_132</setSpec>
        <setSpec>category_133</setSpec>
        <setSpec>category_134</setSpec>
        <setSpec>portal_63</setSpec>
        <setSpec>item_type_6</setSpec>
        <setSpec>month_year_05_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Herbivore-Induced
Volatiles Orchestrate Oviposition
Plasticity in Geometrid Moths to Counteract Direct Resistance in Tea
Plants</dc:title>
          <dc:creator>Yu-Yu Huang (7328012)</dc:creator>
          <dc:creator>Zi-Jun Luo (21838127)</dc:creator>
          <dc:creator>Ying-Jie Zhao (12469257)</dc:creator>
          <dc:creator>Xiao-Ming Cai (2549698)</dc:creator>
          <dc:creator>Zong-Xiu Luo (2549701)</dc:creator>
          <dc:creator>Lei Bian (1894600)</dc:creator>
          <dc:creator>Chun-Li Xiu (17091697)</dc:creator>
          <dc:creator>Nan-Xia Fu (23828392)</dc:creator>
          <dc:creator>Man-Qun Wang (482845)</dc:creator>
          <dc:creator>Zhao-Qun Li (427978)</dc:creator>
          <dc:creator>Zong-Mao Chen (2549704)</dc:creator>
          <dc:subject>Microbiology</dc:subject>
          <dc:subject>Evolutionary Biology</dc:subject>
          <dc:subject>Ecology</dc:subject>
          <dc:subject>Infectious Diseases</dc:subject>
          <dc:subject>Plant Biology</dc:subject>
          <dc:subject>Virology</dc:subject>
          <dc:subject>specific defensive metabolites</dc:subject>
          <dc:subject>mediated metabolomic changes</dc:subject>
          <dc:subject>counteract direct resistance</dc:subject>
          <dc:subject>coevolutionary arms race</dc:subject>
          <dc:subject>avoid defended hosts</dc:subject>
          <dc:subject>integrated defense cascade</dc:subject>
          <dc:subject>ectropis grisescens ).</dc:subject>
          <dc:subject>insect behavioral responses</dc:subject>
          <dc:subject>insect behavioral ecology</dc:subject>
          <dc:subject>coordinated signaling leads</dc:subject>
          <dc:subject>2 +&lt;/ sup</dc:subject>
          <dc:subject>synchronized defense</dc:subject>
          <dc:subject>grisescens females</dc:subject>
          <dc:subject>volatiles serve</dc:subject>
          <dc:subject>vitexin ),</dc:subject>
          <dc:subject>transgenerational plasticity</dc:subject>
          <dc:subject>selective pressure</dc:subject>
          <dc:subject>reciprocal adaptations</dc:subject>
          <dc:subject>reciprocal adaptation</dc:subject>
          <dc:subject>novel paradigm</dc:subject>
          <dc:subject>mapk activation</dc:subject>
          <dc:subject>jasmonate biosynthesis</dc:subject>
          <dc:subject>involving ca</dc:subject>
          <dc:subject>intergenerational coevolution</dc:subject>
          <dc:subject>gravid e</dc:subject>
          <dc:subject>geometrid moths</dc:subject>
          <dc:subject>geometrid moth</dc:subject>
          <dc:subject>enabling females</dc:subject>
          <dc:subject>e &lt;/</dc:subject>
          <dc:subject>dynamic equilibrium</dc:subject>
          <dc:subject>counterdefense dynamic</dc:subject>
          <dc:subject>camellia sinensis</dc:subject>
          <dc:subject>&gt;)- β</dc:subject>
          <dc:description>The coevolutionary arms race between plants and herbivores
drives
the diversification of reciprocal adaptations. However, the transgenerational
plasticity of insect behavioral responses to induced plant defenses
remains poorly understood. Here, we elucidate a synchronized defense-counterdefense
dynamic between tea plants (Camellia sinensis) and the geometrid moth (Ectropis grisescens). We found that larval herbivory rapidly triggers an integrated
defense cascade in tea plants, involving Ca&lt;sup&gt;2+&lt;/sup&gt; signaling,
MAPK activation, and jasmonate biosynthesis. This coordinated signaling
leads to the accumulation of specific defensive metabolites (luteoloside,
galangin, rhofolin, and vitexin), which collectively impair larval
growth. Crucially, this herbivore-induced chemical defense creates
a selective pressure that drives a reciprocal adaptation in the insect.
Gravid E. grisescens females have evolved
the ability to detect two characteristic volatiles, (&lt;i&gt;E&lt;/i&gt;)-β-ocimene and linalool, emitted by attacked plants. These
volatiles serve as reliable oviposition deterrent signals, enabling
females to avoid defended hosts and thereby enhance offspring fitness.
Our study integrates plant physiological signaling, phytohormone-mediated
metabolomic changes, and insect behavioral ecology to reveal a novel
paradigm of intergenerational coevolution. It demonstrates how plant
induced defenses directly shape insect oviposition strategies, sustaining
a dynamic equilibrium in agroecosystems.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
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          <dc:identifier>10.1021/acs.jafc.5c13887.s004</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Herbivore-Induced_Volatiles_Orchestrate_Oviposition_Plasticity_in_Geometrid_Moths_to_Counteract_Direct_Resistance_in_Tea_Plants/32149357</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
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        <identifier>oai:figshare.com:article/32149354</identifier>
        <datestamp>2026-05-03T00:00:00Z</datestamp>
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        <setSpec>month_year_05_2026</setSpec>
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      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Freeze-Induced Structural
Stabilization of Hydrogel
Scaffolds for Dense 3D Printed Ceramics</dc:title>
          <dc:creator>Ge Wang (56838)</dc:creator>
          <dc:creator>Xiaohang Wang (4862665)</dc:creator>
          <dc:creator>Haoqin Ma (10114816)</dc:creator>
          <dc:creator>Shuai Yang (645019)</dc:creator>
          <dc:creator>Xinghua Sheng (21585988)</dc:creator>
          <dc:creator>Sheng Bi (320166)</dc:creator>
          <dc:creator>Nan Sun (788187)</dc:creator>
          <dc:creator>Dongchen Tan (10467371)</dc:creator>
          <dc:creator>Chengming Jiang (1658248)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Molecular Biology</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Sociology</dc:subject>
          <dc:subject>Infectious Diseases</dc:subject>
          <dc:subject>Computational  Biology</dc:subject>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Astronomical and Space Sciences not elsewhere classified</dc:subject>
          <dc:subject>Chemical Sciences not elsewhere classified</dc:subject>
          <dc:subject>preventing structural shrinkage</dc:subject>
          <dc:subject>induced structural stabilization</dc:subject>
          <dc:subject>conventional vat photopolymerization</dc:subject>
          <dc:subject>advanced engineering applications</dc:subject>
          <dc:subject>complex ceramic structures</dc:subject>
          <dc:subject>advanced ceramic materials</dc:subject>
          <dc:subject>specific photocurable resins</dc:subject>
          <dc:subject>metal precursors within</dc:subject>
          <dc:subject>manufacturing complex architectures</dc:subject>
          <dc:subject>high structural fidelity</dc:subject>
          <dc:subject>ceramic precursor incorporation</dc:subject>
          <dc:subject>decoupling structural fabrication</dc:subject>
          <dc:subject>ceramic densification</dc:subject>
          <dc:subject>precursor infiltration</dc:subject>
          <dc:subject>high viscosity</dc:subject>
          <dc:subject>filled resins</dc:subject>
          <dc:subject>adsorption within</dc:subject>
          <dc:subject>additive manufacturing</dc:subject>
          <dc:subject>target geometry</dc:subject>
          <dc:subject>scalable route</dc:subject>
          <dc:subject>repeated optimization</dc:subject>
          <dc:subject>progressively increased</dc:subject>
          <dc:subject>powerful platform</dc:subject>
          <dc:subject>phase transition</dc:subject>
          <dc:subject>overall volume</dc:subject>
          <dc:subject>ordered microstructures</dc:subject>
          <dc:subject>microstructural compactness</dc:subject>
          <dc:subject>light scattering</dc:subject>
          <dc:subject>hydrogel scaffolds</dc:subject>
          <dc:subject>hydrogel network</dc:subject>
          <dc:subject>hydrogel framework</dc:subject>
          <dc:subject>frozen tofu</dc:subject>
          <dc:subject>ceramics provides</dc:subject>
          <dc:subject>assisted hydrogel</dc:subject>
          <dc:description>Three dimensional (3D) printing of ceramics provides
a powerful
platform for manufacturing complex architectures for advanced engineering
applications. However, conventional vat photopolymerization-based
ceramic printing relies on particle-filled resins, where light scattering,
high viscosity, and material-specific formulation constraints significantly
limit printing precision and material versatility. Here we report
a freeze-assisted hydrogel-derived ceramic manufacturing method that
enables the fabrication of dense 3D ceramic architectures while decoupling
structural fabrication from ceramic precursor incorporation. In this
approach, a photocured hydrogel scaffold first defines the target
geometry, followed by precursor infiltration and a repeated soak–freeze–dry
cycle inspired by the formation mechanism of frozen tofu. During freezing,
the phase transition of water generates ice crystals that stabilize
the hydrogel network and preserve its overall volume, preventing structural
shrinkage and collapse. Simultaneously, ice-crystal growth produces
interconnected porous channels that significantly enhance precursor
transport and adsorption within the scaffold. Through repeated infiltration–freezing
cycles, the concentration of metal precursors within the hydrogel
framework is progressively increased, enabling the formation of dense
and structurally stable ceramic architectures after calcination. This
method effectively improves precursor distribution and ceramic densification
while eliminating the need for repeated optimization of material-specific
photocurable resins. As a result, a variety of complex ceramic structures
can be fabricated with high structural fidelity and ordered microstructures.
The resulting ceramics exhibit improved densification and microstructural
compactness, demonstrating a versatile and scalable route for the
additive manufacturing of advanced ceramic materials.</dc:description>
          <dc:date>2026-05-03T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Journal contribution</dc:type>
          <dc:identifier>10.1021/acsaenm.6c00311.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Freeze-Induced_Structural_Stabilization_of_Hydrogel_Scaffolds_for_Dense_3D_Printed_Ceramics/32149354</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
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